id	sid	tid	token	lemma	pos
alkej-16	1	1	final1	final1	NOUN
alkej-16	1	2	١	١	NUM
alkej-16	1	3	al	al	PROPN
alkej-16	1	4	-	-	PUNCT
alkej-16	1	5	khwarizmi	khwarizmi	PROPN
alkej-16	1	6	engineering	engineering	PROPN
alkej-16	1	7	journal	journal	PROPN
alkej-16	1	8	al	al	PROPN
alkej-16	1	9	-	-	PUNCT
alkej-16	1	10	khwarizmi	khwarizmi	PROPN
alkej-16	1	11	engineering	engineering	NOUN
alkej-16	1	12	journal	journal	PROPN
alkej-16	1	13	,	,	PUNCT
alkej-16	1	14	vol.1	vol.1	PROPN
alkej-16	1	15	,	,	PUNCT
alkej-16	1	16	no.1,pp	no.1,pp	AUX
alkej-16	1	17	1	1	NUM
alkej-16	1	18	-	-	SYM
alkej-16	1	19	18	18	NUM
alkej-16	1	20	,	,	PUNCT
alkej-16	1	21	(	(	PUNCT
alkej-16	1	22	2005	2005	NUM
alkej-16	1	23	)	)	PUNCT
alkej-16	1	24	neuro	neuro	NOUN
alkej-16	1	25	-	-	PUNCT
alkej-16	1	26	self	self	NOUN
alkej-16	1	27	tuning	tune	VERB
alkej-16	1	28	adaptive	adaptive	ADJ
alkej-16	1	29	controller	controller	NOUN
alkej-16	1	30	for	for	ADP
alkej-16	1	31	non	non	ADJ
alkej-16	1	32	-	-	ADJ
alkej-16	1	33	linear	linear	ADJ
alkej-16	1	34	dynamical	dynamical	ADJ
alkej-16	1	35	systems	system	NOUN
alkej-16	1	36	ahmed	ahmed	PROPN
alkej-16	1	37	sabah	sabah	PROPN
alkej-16	1	38	abdul	abdul	PROPN
alkej-16	1	39	ameer	ameer	PROPN
alkej-16	1	40	al	al	PROPN
alkej-16	1	41	-	-	PUNCT
alkej-16	1	42	araji	araji	PROPN
alkej-16	1	43	university	university	PROPN
alkej-16	1	44	of	of	ADP
alkej-16	1	45	technology	technology	NOUN
alkej-16	1	46	abstract	abstract	NOUN
alkej-16	1	47	:	:	PUNCT
alkej-16	1	48	in	in	ADP
alkej-16	1	49	this	this	DET
alkej-16	1	50	paper	paper	NOUN
alkej-16	1	51	,	,	PUNCT
alkej-16	1	52	a	a	DET
alkej-16	1	53	self	self	NOUN
alkej-16	1	54	-	-	PUNCT
alkej-16	1	55	tuning	tune	VERB
alkej-16	1	56	adaptive	adaptive	ADJ
alkej-16	1	57	neural	neural	ADJ
alkej-16	1	58	controller	controller	NOUN
alkej-16	1	59	strategy	strategy	NOUN
alkej-16	1	60	for	for	ADP
alkej-16	1	61	unknown	unknown	ADJ
alkej-16	1	62	nonlinear	nonlinear	ADJ
alkej-16	1	63	system	system	NOUN
alkej-16	1	64	is	be	AUX
alkej-16	1	65	presented	present	VERB
alkej-16	1	66	.	.	PUNCT
alkej-16	2	1	the	the	DET
alkej-16	2	2	system	system	NOUN
alkej-16	2	3	considered	consider	VERB
alkej-16	2	4	is	be	AUX
alkej-16	2	5	described	describe	VERB
alkej-16	2	6	by	by	ADP
alkej-16	2	7	an	an	DET
alkej-16	2	8	unknown	unknown	ADJ
alkej-16	2	9	narma	narma	NOUN
alkej-16	2	10	-	-	PUNCT
alkej-16	2	11	l2	l2	NOUN
alkej-16	2	12	model	model	NOUN
alkej-16	2	13	and	and	CCONJ
alkej-16	2	14	a	a	DET
alkej-16	2	15	feedforward	feedforward	ADJ
alkej-16	2	16	neural	neural	ADJ
alkej-16	2	17	network	network	NOUN
alkej-16	2	18	is	be	AUX
alkej-16	2	19	used	use	VERB
alkej-16	2	20	to	to	PART
alkej-16	2	21	learn	learn	VERB
alkej-16	2	22	the	the	DET
alkej-16	2	23	model	model	NOUN
alkej-16	2	24	with	with	ADP
alkej-16	2	25	two	two	NUM
alkej-16	2	26	stages	stage	NOUN
alkej-16	2	27	.	.	PUNCT
alkej-16	3	1	the	the	DET
alkej-16	3	2	first	first	ADJ
alkej-16	3	3	stage	stage	NOUN
alkej-16	3	4	is	be	AUX
alkej-16	3	5	learned	learn	VERB
alkej-16	3	6	off	off	ADP
alkej-16	3	7	-	-	PUNCT
alkej-16	3	8	line	line	NOUN
alkej-16	3	9	with	with	ADP
alkej-16	3	10	two	two	NUM
alkej-16	3	11	configuration	configuration	NOUN
alkej-16	3	12	serial	serial	ADJ
alkej-16	3	13	-	-	PUNCT
alkej-16	3	14	parallel	parallel	NOUN
alkej-16	3	15	model	model	NOUN
alkej-16	3	16	&	&	CCONJ
alkej-16	3	17	parallel	parallel	ADJ
alkej-16	3	18	model	model	NOUN
alkej-16	3	19	to	to	PART
alkej-16	3	20	ensure	ensure	VERB
alkej-16	3	21	that	that	SCONJ
alkej-16	3	22	model	model	NOUN
alkej-16	3	23	output	output	NOUN
alkej-16	3	24	is	be	AUX
alkej-16	3	25	equal	equal	ADJ
alkej-16	3	26	to	to	ADP
alkej-16	3	27	actual	actual	ADJ
alkej-16	3	28	output	output	NOUN
alkej-16	3	29	of	of	ADP
alkej-16	3	30	the	the	DET
alkej-16	3	31	system	system	NOUN
alkej-16	3	32	&	&	CCONJ
alkej-16	3	33	to	to	PART
alkej-16	3	34	find	find	VERB
alkej-16	3	35	the	the	DET
alkej-16	3	36	jacobain	jacobain	NOUN
alkej-16	3	37	of	of	ADP
alkej-16	3	38	the	the	DET
alkej-16	3	39	system	system	NOUN
alkej-16	3	40	.	.	PUNCT
alkej-16	4	1	which	which	PRON
alkej-16	4	2	appears	appear	VERB
alkej-16	4	3	to	to	PART
alkej-16	4	4	be	be	AUX
alkej-16	4	5	of	of	ADP
alkej-16	4	6	critical	critical	ADJ
alkej-16	4	7	importance	importance	NOUN
alkej-16	4	8	parameter	parameter	NOUN
alkej-16	4	9	as	as	SCONJ
alkej-16	4	10	it	it	PRON
alkej-16	4	11	is	be	AUX
alkej-16	4	12	used	use	VERB
alkej-16	4	13	for	for	ADP
alkej-16	4	14	the	the	DET
alkej-16	4	15	feedback	feedback	NOUN
alkej-16	4	16	controller	controller	NOUN
alkej-16	4	17	and	and	CCONJ
alkej-16	4	18	the	the	DET
alkej-16	4	19	second	second	ADJ
alkej-16	4	20	stage	stage	NOUN
alkej-16	4	21	is	be	AUX
alkej-16	4	22	learned	learn	VERB
alkej-16	4	23	on	on	ADP
alkej-16	4	24	-	-	PUNCT
alkej-16	4	25	line	line	NOUN
alkej-16	4	26	to	to	PART
alkej-16	4	27	modify	modify	VERB
alkej-16	4	28	the	the	DET
alkej-16	4	29	weights	weight	NOUN
alkej-16	4	30	of	of	ADP
alkej-16	4	31	the	the	DET
alkej-16	4	32	model	model	NOUN
alkej-16	4	33	in	in	ADP
alkej-16	4	34	order	order	NOUN
alkej-16	4	35	to	to	PART
alkej-16	4	36	control	control	VERB
alkej-16	4	37	the	the	DET
alkej-16	4	38	variable	variable	ADJ
alkej-16	4	39	parameters	parameter	NOUN
alkej-16	4	40	that	that	PRON
alkej-16	4	41	will	will	AUX
alkej-16	4	42	occur	occur	VERB
alkej-16	4	43	to	to	ADP
alkej-16	4	44	the	the	DET
alkej-16	4	45	system	system	NOUN
alkej-16	4	46	.	.	PUNCT
alkej-16	5	1	a	a	DET
alkej-16	5	2	back	back	ADJ
alkej-16	5	3	propagation	propagation	NOUN
alkej-16	5	4	neural	neural	ADJ
alkej-16	5	5	network	network	NOUN
alkej-16	5	6	is	be	AUX
alkej-16	5	7	applied	apply	VERB
alkej-16	5	8	to	to	PART
alkej-16	5	9	learn	learn	VERB
alkej-16	5	10	the	the	DET
alkej-16	5	11	control	control	NOUN
alkej-16	5	12	structure	structure	NOUN
alkej-16	5	13	for	for	ADP
alkej-16	5	14	self	self	NOUN
alkej-16	5	15	-	-	PUNCT
alkej-16	5	16	tuning	tune	VERB
alkej-16	5	17	pid	pid	NOUN
alkej-16	5	18	type	type	NOUN
alkej-16	5	19	neurocontroller	neurocontroller	NOUN
alkej-16	5	20	.	.	PUNCT
alkej-16	6	1	where	where	SCONJ
alkej-16	6	2	the	the	DET
alkej-16	6	3	neural	neural	ADJ
alkej-16	6	4	network	network	NOUN
alkej-16	6	5	is	be	AUX
alkej-16	6	6	used	use	VERB
alkej-16	6	7	to	to	PART
alkej-16	6	8	minimize	minimize	VERB
alkej-16	6	9	the	the	DET
alkej-16	6	10	error	error	NOUN
alkej-16	6	11	function	function	NOUN
alkej-16	6	12	by	by	ADP
alkej-16	6	13	adjusting	adjust	VERB
alkej-16	6	14	the	the	DET
alkej-16	6	15	pid	pid	NOUN
alkej-16	6	16	gains	gain	NOUN
alkej-16	6	17	.	.	PUNCT
alkej-16	7	1	simulation	simulation	NOUN
alkej-16	7	2	results	result	NOUN
alkej-16	7	3	show	show	VERB
alkej-16	7	4	that	that	SCONJ
alkej-16	7	5	the	the	DET
alkej-16	7	6	self	self	NOUN
alkej-16	7	7	-	-	PUNCT
alkej-16	7	8	tuning	tune	VERB
alkej-16	7	9	pid	pid	NOUN
alkej-16	7	10	scheme	scheme	NOUN
alkej-16	7	11	can	can	AUX
alkej-16	7	12	deal	deal	VERB
alkej-16	7	13	with	with	ADP
alkej-16	7	14	a	a	DET
alkej-16	7	15	large	large	ADJ
alkej-16	7	16	unknown	unknown	ADJ
alkej-16	7	17	nonlinearity	nonlinearity	NOUN
alkej-16	7	18	.	.	PUNCT
alkej-16	8	1	keyword	keyword	NOUN
alkej-16	8	2	:	:	PUNCT
alkej-16	8	3	self	self	NOUN
alkej-16	8	4	-	-	PUNCT
alkej-16	8	5	tuning	tuning	NOUN
alkej-16	8	6	,	,	PUNCT
alkej-16	8	7	neural	neural	ADJ
alkej-16	8	8	network	network	NOUN
alkej-16	8	9	,	,	PUNCT
alkej-16	8	10	adaptive	adaptive	ADJ
alkej-16	8	11	controller	controller	NOUN
alkej-16	8	12	.	.	PUNCT
alkej-16	9	1	1	1	X
alkej-16	9	2	.	.	X
alkej-16	9	3	introduction	introduction	NOUN
alkej-16	9	4	:	:	PUNCT
alkej-16	9	5	in	in	ADP
alkej-16	9	6	many	many	ADJ
alkej-16	9	7	applications	application	NOUN
alkej-16	9	8	,	,	PUNCT
alkej-16	9	9	the	the	DET
alkej-16	9	10	control	control	NOUN
alkej-16	9	11	engineers	engineer	NOUN
alkej-16	9	12	face	face	VERB
alkej-16	9	13	a	a	DET
alkej-16	9	14	number	number	NOUN
alkej-16	9	15	of	of	ADP
alkej-16	9	16	practical	practical	ADJ
alkej-16	9	17	difficulties	difficulty	NOUN
alkej-16	9	18	.	.	PUNCT
alkej-16	10	1	the	the	DET
alkej-16	10	2	large	large	ADJ
alkej-16	10	3	dimensionality	dimensionality	NOUN
alkej-16	10	4	of	of	ADP
alkej-16	10	5	many	many	ADJ
alkej-16	10	6	processes	process	NOUN
alkej-16	10	7	&	&	CCONJ
alkej-16	10	8	the	the	DET
alkej-16	10	9	significant	significant	ADJ
alkej-16	10	10	interaction	interaction	NOUN
alkej-16	10	11	between	between	ADP
alkej-16	10	12	variables	variable	NOUN
alkej-16	10	13	from	from	ADP
alkej-16	10	14	the	the	DET
alkej-16	10	15	major	major	ADJ
alkej-16	10	16	obstacle	obstacle	NOUN
alkej-16	10	17	to	to	ADP
alkej-16	10	18	the	the	DET
alkej-16	10	19	successful	successful	ADJ
alkej-16	10	20	attempts	attempt	NOUN
alkej-16	10	21	of	of	ADP
alkej-16	10	22	extending	extend	VERB
alkej-16	10	23	the	the	DET
alkej-16	10	24	classical	classical	ADJ
alkej-16	10	25	techniques	technique	NOUN
alkej-16	10	26	for	for	ADP
alkej-16	10	27	the	the	DET
alkej-16	10	28	design	design	NOUN
alkej-16	10	29	of	of	ADP
alkej-16	10	30	controllers	controller	NOUN
alkej-16	10	31	for	for	ADP
alkej-16	10	32	monovaraible	monovaraible	ADJ
alkej-16	10	33	plants	plant	NOUN
alkej-16	10	34	to	to	ADP
alkej-16	10	35	multivariable	multivariable	ADJ
alkej-16	10	36	ones	one	NOUN
alkej-16	10	37	.	.	PUNCT
alkej-16	11	1	the	the	DET
alkej-16	11	2	development	development	NOUN
alkej-16	11	3	of	of	ADP
alkej-16	11	4	computer	computer	NOUN
alkej-16	11	5	-	-	PUNCT
alkej-16	11	6	aided	aid	VERB
alkej-16	11	7	techniques	technique	NOUN
alkej-16	11	8	to	to	PART
alkej-16	11	9	design	design	NOUN
alkej-16	11	10	controllers	controller	NOUN
alkej-16	11	11	aim	aim	VERB
alkej-16	11	12	to	to	PART
alkej-16	11	13	reduce	reduce	VERB
alkej-16	11	14	interaction	interaction	NOUN
alkej-16	11	15	before	before	ADP
alkej-16	11	16	applying	apply	VERB
alkej-16	11	17	classical	classical	ADJ
alkej-16	11	18	theory	theory	NOUN
alkej-16	11	19	to	to	ADP
alkej-16	11	20	the	the	DET
alkej-16	11	21	individual	individual	ADJ
alkej-16	11	22	loops	loop	NOUN
alkej-16	11	23	.	.	PUNCT
alkej-16	12	1	most	most	ADJ
alkej-16	12	2	existing	exist	VERB
alkej-16	12	3	techniques	technique	NOUN
alkej-16	12	4	are	be	AUX
alkej-16	12	5	based	base	VERB
alkej-16	12	6	on	on	ADP
alkej-16	12	7	the	the	DET
alkej-16	12	8	design	design	NOUN
alkej-16	12	9	of	of	ADP
alkej-16	12	10	tunable	tunable	ADJ
alkej-16	12	11	set	set	NOUN
alkej-16	12	12	-	-	PUNCT
alkej-16	12	13	point	point	NOUN
alkej-16	12	14	tracking	tracking	NOUN
alkej-16	12	15	controllers	controller	NOUN
alkej-16	12	16	with	with	ADP
alkej-16	12	17	the	the	DET
alkej-16	12	18	dominance	dominance	NOUN
alkej-16	12	19	pi	pi	NOUN
alkej-16	12	20	(	(	PUNCT
alkej-16	12	21	proportional	proportional	ADJ
alkej-16	12	22	,	,	PUNCT
alkej-16	12	23	integral	integral	ADJ
alkej-16	12	24	)	)	PUNCT
alkej-16	12	25	&	&	CCONJ
alkej-16	12	26	pid	pid	PROPN
alkej-16	12	27	(	(	PUNCT
alkej-16	12	28	proportional	proportional	ADJ
alkej-16	12	29	,	,	PUNCT
alkej-16	12	30	integral	integral	ADJ
alkej-16	12	31	,	,	PUNCT
alkej-16	12	32	derivative	derivative	ADJ
alkej-16	12	33	)	)	PUNCT
alkej-16	12	34	controllers	controller	NOUN
alkej-16	12	35	in	in	ADP
alkej-16	12	36	industry	industry	NOUN
alkej-16	12	37	&	&	CCONJ
alkej-16	12	38	certain	certain	ADJ
alkej-16	12	39	assumptions	assumption	NOUN
alkej-16	12	40	such	such	ADJ
alkej-16	12	41	as	as	ADP
alkej-16	12	42	linearity	linearity	NOUN
alkej-16	12	43	&	&	CCONJ
alkej-16	12	44	interactions	interaction	NOUN
alkej-16	12	45	with	with	ADP
alkej-16	12	46	in	in	ADP
alkej-16	12	47	the	the	DET
alkej-16	12	48	controlled	control	VERB
alkej-16	12	49	process	process	NOUN
alkej-16	12	50	have	have	VERB
alkej-16	12	51	to	to	PART
alkej-16	12	52	be	be	AUX
alkej-16	12	53	made	make	VERB
alkej-16	12	54	[	[	PUNCT
alkej-16	12	55	1,2	1,2	NUM
alkej-16	12	56	]	]	PUNCT
alkej-16	12	57	.	.	PUNCT
alkej-16	13	1	neural	neural	ADJ
alkej-16	13	2	networks	network	NOUN
alkej-16	13	3	have	have	VERB
alkej-16	13	4	broad	broad	ADJ
alkej-16	13	5	applicability	applicability	NOUN
alkej-16	13	6	to	to	ADP
alkej-16	13	7	real	real	ADJ
alkej-16	13	8	world	world	NOUN
alkej-16	13	9	problems	problem	NOUN
alkej-16	13	10	,	,	PUNCT
alkej-16	13	11	such	such	ADJ
alkej-16	13	12	as	as	ADP
alkej-16	13	13	in	in	ADP
alkej-16	13	14	pattern	pattern	NOUN
alkej-16	13	15	recognition	recognition	NOUN
alkej-16	13	16	,	,	PUNCT
alkej-16	13	17	diagnostic	diagnostic	ADJ
alkej-16	13	18	,	,	PUNCT
alkej-16	13	19	optimization	optimization	NOUN
alkej-16	13	20	,	,	PUNCT
alkej-16	13	21	system	system	NOUN
alkej-16	13	22	identification	identification	NOUN
alkej-16	13	23	&	&	CCONJ
alkej-16	13	24	control	control	PROPN
alkej-16	13	25	.	.	PUNCT
alkej-16	14	1	they	they	PRON
alkej-16	14	2	have	have	AUX
alkej-16	14	3	already	already	ADV
alkej-16	14	4	been	be	AUX
alkej-16	14	5	successfully	successfully	ADV
alkej-16	14	6	applied	apply	VERB
alkej-16	14	7	in	in	ADP
alkej-16	14	8	many	many	ADJ
alkej-16	14	9	industries	industry	NOUN
alkej-16	14	10	,	,	PUNCT
alkej-16	14	11	as	as	SCONJ
alkej-16	14	12	they	they	PRON
alkej-16	14	13	are	be	AUX
alkej-16	14	14	well	well	ADV
alkej-16	14	15	suited	suited	ADJ
alkej-16	14	16	for	for	ADP
alkej-16	14	17	predication	predication	NOUN
alkej-16	14	18	or	or	CCONJ
alkej-16	14	19	forecasting	forecasting	NOUN
alkej-16	14	20	because	because	SCONJ
alkej-16	14	21	of	of	ADP
alkej-16	14	22	their	their	PRON
alkej-16	14	23	abilities	ability	NOUN
alkej-16	14	24	in	in	ADP
alkej-16	14	25	identifying	identify	VERB
alkej-16	14	26	patterns	pattern	NOUN
alkej-16	14	27	or	or	CCONJ
alkej-16	14	28	trend	trend	NOUN
alkej-16	14	29	in	in	ADP
alkej-16	14	30	data	datum	NOUN
alkej-16	14	31	[	[	X
alkej-16	14	32	3,4	3,4	NUM
alkej-16	14	33	]	]	PUNCT
alkej-16	14	34	.	.	PUNCT
alkej-16	15	1	the	the	DET
alkej-16	15	2	neural	neural	ADJ
alkej-16	15	3	network	network	NOUN
alkej-16	15	4	model	model	NOUN
alkej-16	15	5	can	can	AUX
alkej-16	15	6	be	be	AUX
alkej-16	15	7	used	use	VERB
alkej-16	15	8	in	in	ADP
alkej-16	15	9	control	control	NOUN
alkej-16	15	10	strategies	strategy	NOUN
alkej-16	15	11	that	that	PRON
alkej-16	15	12	require	require	VERB
alkej-16	15	13	a	a	DET
alkej-16	15	14	global	global	ADJ
alkej-16	15	15	model	model	NOUN
alkej-16	15	16	of	of	ADP
alkej-16	15	17	the	the	DET
alkej-16	15	18	system	system	NOUN
alkej-16	15	19	forward	forward	ADV
alkej-16	15	20	or	or	CCONJ
alkej-16	15	21	inverse	inverse	NOUN
alkej-16	15	22	dynamics	dynamic	NOUN
alkej-16	15	23	,	,	PUNCT
alkej-16	15	24	and	and	CCONJ
alkej-16	15	25	these	these	DET
alkej-16	15	26	models	model	NOUN
alkej-16	15	27	are	be	AUX
alkej-16	15	28	available	available	ADJ
alkej-16	15	29	in	in	ADP
alkej-16	15	30	the	the	DET
alkej-16	15	31	form	form	NOUN
alkej-16	15	32	of	of	ADP
alkej-16	15	33	neural	neural	ADJ
alkej-16	15	34	networks	network	NOUN
alkej-16	15	35	,	,	PUNCT
alkej-16	15	36	which	which	PRON
alkej-16	15	37	have	have	AUX
alkej-16	15	38	been	be	AUX
alkej-16	15	39	trained	train	VERB
alkej-16	15	40	using	use	VERB
alkej-16	15	41	neural	neural	ADJ
alkej-16	15	42	based	base	VERB
alkej-16	15	43	system	system	NOUN
alkej-16	15	44	identification	identification	NOUN
alkej-16	15	45	techniques	technique	NOUN
alkej-16	15	46	.	.	PUNCT
alkej-16	16	1	papers	paper	NOUN
alkej-16	16	2	by	by	ADP
alkej-16	16	3	:	:	PUNCT
alkej-16	16	4	narandra	narandra	PROPN
alkej-16	16	5	&	&	CCONJ
alkej-16	16	6	parthasarathy	parthasarathy	PROPN
alkej-16	17	1	[	[	X
alkej-16	17	2	5,6	5,6	NUM
alkej-16	17	3	]	]	PUNCT
alkej-16	17	4	are	be	AUX
alkej-16	17	5	some	some	PRON
alkej-16	17	6	of	of	ADP
alkej-16	17	7	those	those	PRON
alkej-16	17	8	that	that	PRON
alkej-16	17	9	can	can	AUX
alkej-16	17	10	be	be	AUX
alkej-16	17	11	referred	refer	VERB
alkej-16	17	12	to	to	ADP
alkej-16	17	13	as	as	ADP
alkej-16	17	14	the	the	DET
alkej-16	17	15	application	application	NOUN
alkej-16	17	16	of	of	ADP
alkej-16	17	17	neural	neural	ADJ
alkej-16	17	18	networks	network	NOUN
alkej-16	17	19	for	for	ADP
alkej-16	17	20	ahmed	ahmed	PROPN
alkej-16	17	21	sabah	sabah	PROPN
alkej-16	17	22	abdul	abdul	PROPN
alkej-16	17	23	ameer	ameer	PROPN
alkej-16	17	24	/al	/al	PROPN
alkej-16	17	25	khwarizmi	khwarizmi	PROPN
alkej-16	17	26	engineering	engineering	PROPN
alkej-16	17	27	journal	journal	PROPN
alkej-16	17	28	,	,	PUNCT
alkej-16	17	29	vol	vol	NOUN
alkej-16	17	30	.	.	PROPN
alkej-16	17	31	1	1	NUM
alkej-16	17	32	,	,	PUNCT
alkej-16	17	33	no	no	INTJ
alkej-16	17	34	.	.	NOUN
alkej-16	17	35	1	1	NUM
alkej-16	17	36	,	,	PUNCT
alkej-16	17	37	pp	pp	ADV
alkej-16	17	38	1	1	NUM
alkej-16	17	39	-	-	SYM
alkej-16	17	40	18	18	NUM
alkej-16	17	41	(	(	PUNCT
alkej-16	17	42	2005	2005	NUM
alkej-16	17	43	)	)	PUNCT
alkej-16	17	44	٢	٢	PROPN
alkej-16	17	45	system	system	NOUN
alkej-16	17	46	identification	identification	NOUN
alkej-16	17	47	.	.	PUNCT
alkej-16	18	1	the	the	DET
alkej-16	18	2	generalized	generalized	ADJ
alkej-16	18	3	learning	learning	NOUN
alkej-16	18	4	method	method	NOUN
alkej-16	18	5	attempts	attempt	NOUN
alkej-16	18	6	to	to	PART
alkej-16	18	7	produce	produce	VERB
alkej-16	18	8	the	the	DET
alkej-16	18	9	inverse	inverse	NOUN
alkej-16	18	10	of	of	ADP
alkej-16	18	11	a	a	DET
alkej-16	18	12	plant	plant	NOUN
alkej-16	18	13	over	over	ADP
alkej-16	18	14	the	the	DET
alkej-16	18	15	entire	entire	ADJ
alkej-16	18	16	state	state	NOUN
alkej-16	18	17	space	space	NOUN
alkej-16	18	18	using	use	VERB
alkej-16	18	19	off	off	ADP
alkej-16	18	20	-	-	PUNCT
alkej-16	18	21	line	line	NOUN
alkej-16	18	22	training	training	NOUN
alkej-16	18	23	while	while	SCONJ
alkej-16	18	24	in	in	ADP
alkej-16	18	25	the	the	DET
alkej-16	18	26	specialized	specialized	ADJ
alkej-16	18	27	architecture	architecture	NOUN
alkej-16	18	28	the	the	DET
alkej-16	18	29	training	training	NOUN
alkej-16	18	30	is	be	AUX
alkej-16	18	31	on	on	ADP
alkej-16	18	32	-	-	PUNCT
alkej-16	18	33	line	line	NOUN
alkej-16	18	34	and	and	CCONJ
alkej-16	18	35	uses	use	VERB
alkej-16	18	36	error	error	NOUN
alkej-16	18	37	backpropagation	backpropagation	NOUN
alkej-16	18	38	through	through	ADP
alkej-16	18	39	the	the	DET
alkej-16	18	40	plant	plant	NOUN
alkej-16	18	41	to	to	PART
alkej-16	18	42	learn	learn	VERB
alkej-16	18	43	the	the	DET
alkej-16	18	44	plant	plant	NOUN
alkej-16	18	45	inverse	inverse	NOUN
alkej-16	18	46	dynamics	dynamic	NOUN
alkej-16	18	47	over	over	ADP
alkej-16	18	48	a	a	DET
alkej-16	18	49	small	small	ADJ
alkej-16	18	50	operating	operating	NOUN
alkej-16	18	51	region	region	NOUN
alkej-16	18	52	.	.	PUNCT
alkej-16	19	1	behera	behera	PROPN
alkej-16	19	2	et	et	PROPN
alkej-16	19	3	al	al	PROPN
alkej-16	20	1	[	[	X
alkej-16	20	2	7	7	X
alkej-16	20	3	]	]	PUNCT
alkej-16	20	4	in	in	ADP
alkej-16	20	5	their	their	PRON
alkej-16	20	6	paper	paper	NOUN
alkej-16	20	7	are	be	AUX
alkej-16	20	8	concerned	concern	VERB
alkej-16	20	9	with	with	ADP
alkej-16	20	10	the	the	DET
alkej-16	20	11	design	design	NOUN
alkej-16	20	12	of	of	ADP
alkej-16	20	13	a	a	DET
alkej-16	20	14	hybrid	hybrid	ADJ
alkej-16	20	15	controller	controller	NOUN
alkej-16	20	16	structure	structure	NOUN
alkej-16	20	17	consisting	consist	VERB
alkej-16	20	18	of	of	ADP
alkej-16	20	19	the	the	DET
alkej-16	20	20	adaptive	adaptive	ADJ
alkej-16	20	21	control	control	NOUN
alkej-16	20	22	law	law	NOUN
alkej-16	20	23	and	and	CCONJ
alkej-16	20	24	neural	neural	ADJ
alkej-16	20	25	network	network	NOUN
alkej-16	20	26	based	base	VERB
alkej-16	20	27	learning	learn	VERB
alkej-16	20	28	scheme	scheme	NOUN
alkej-16	20	29	for	for	ADP
alkej-16	20	30	adaptation	adaptation	NOUN
alkej-16	20	31	of	of	ADP
alkej-16	20	32	time	time	NOUN
alkej-16	20	33	varying	vary	VERB
alkej-16	20	34	controller	controller	NOUN
alkej-16	20	35	parameters	parameter	NOUN
alkej-16	20	36	.	.	PUNCT
alkej-16	21	1	the	the	DET
alkej-16	21	2	global	global	ADJ
alkej-16	21	3	stability	stability	NOUN
alkej-16	21	4	of	of	ADP
alkej-16	21	5	the	the	DET
alkej-16	21	6	closed	closed	ADJ
alkej-16	21	7	-	-	PUNCT
alkej-16	21	8	loop	loop	NOUN
alkej-16	21	9	feedback	feedback	NOUN
alkej-16	21	10	system	system	NOUN
alkej-16	21	11	is	be	AUX
alkej-16	21	12	guaranteed	guarantee	VERB
alkej-16	21	13	provided	provide	VERB
alkej-16	21	14	the	the	DET
alkej-16	21	15	structure	structure	NOUN
alkej-16	21	16	of	of	ADP
alkej-16	21	17	the	the	DET
alkej-16	21	18	robot	robot	NOUN
alkej-16	21	19	-	-	PUNCT
alkej-16	21	20	manipulator	manipulator	NOUN
alkej-16	21	21	dynamics	dynamic	NOUN
alkej-16	21	22	model	model	NOUN
alkej-16	21	23	is	be	AUX
alkej-16	21	24	exact	exact	ADJ
alkej-16	21	25	.	.	PUNCT
alkej-16	22	1	generalization	generalization	NOUN
alkej-16	22	2	of	of	ADP
alkej-16	22	3	the	the	DET
alkej-16	22	4	controller	controller	NOUN
alkej-16	22	5	over	over	ADP
alkej-16	22	6	the	the	DET
alkej-16	22	7	desired	desire	VERB
alkej-16	22	8	trajectory	trajectory	NOUN
alkej-16	22	9	space	space	NOUN
alkej-16	22	10	has	have	AUX
alkej-16	22	11	been	be	AUX
alkej-16	22	12	established	establish	VERB
alkej-16	22	13	using	use	VERB
alkej-16	22	14	an	an	DET
alkej-16	22	15	on	on	ADP
alkej-16	22	16	-	-	PUNCT
alkej-16	22	17	line	line	NOUN
alkej-16	22	18	weight	weight	NOUN
alkej-16	22	19	learning	learning	NOUN
alkej-16	22	20	scheme	scheme	NOUN
alkej-16	22	21	.	.	PUNCT
alkej-16	23	1	the	the	DET
alkej-16	23	2	advantage	advantage	NOUN
alkej-16	23	3	of	of	ADP
alkej-16	23	4	a	a	DET
alkej-16	23	5	neuron	neuron	NOUN
alkej-16	23	6	-	-	PUNCT
alkej-16	23	7	adaptive	adaptive	ADJ
alkej-16	23	8	hybrid	hybrid	NOUN
alkej-16	23	9	control	control	NOUN
alkej-16	23	10	scheme	scheme	NOUN
alkej-16	23	11	is	be	AUX
alkej-16	23	12	the	the	DET
alkej-16	23	13	high	high	ADJ
alkej-16	23	14	precision	precision	NOUN
alkej-16	23	15	and	and	CCONJ
alkej-16	23	16	better	well	ADJ
alkej-16	23	17	accuracy	accuracy	NOUN
alkej-16	23	18	and	and	CCONJ
alkej-16	23	19	computationally	computationally	ADV
alkej-16	23	20	less	less	ADV
alkej-16	23	21	intensive	intensive	ADJ
alkej-16	23	22	control	control	NOUN
alkej-16	23	23	scheme	scheme	NOUN
alkej-16	23	24	.	.	PUNCT
alkej-16	24	1	also	also	ADV
alkej-16	24	2	for	for	ADP
alkej-16	24	3	self	self	NOUN
alkej-16	24	4	-	-	PUNCT
alkej-16	24	5	tuning	tune	VERB
alkej-16	24	6	control	control	NOUN
alkej-16	24	7	(	(	PUNCT
alkej-16	24	8	stc	stc	PROPN
alkej-16	24	9	)	)	PUNCT
alkej-16	24	10	,	,	PUNCT
alkej-16	24	11	chen	chen	PROPN
alkej-16	25	1	[	[	X
alkej-16	25	2	8	8	NUM
alkej-16	25	3	]	]	PUNCT
alkej-16	25	4	used	use	VERB
alkej-16	25	5	back	back	ADJ
alkej-16	25	6	-	-	PUNCT
alkej-16	25	7	propagation	propagation	NOUN
alkej-16	25	8	trained	train	VERB
alkej-16	25	9	neural	neural	ADJ
alkej-16	25	10	network	network	NOUN
alkej-16	25	11	within	within	ADP
alkej-16	25	12	a	a	DET
alkej-16	25	13	self	self	NOUN
alkej-16	25	14	-	-	PUNCT
alkej-16	25	15	tuning	tune	VERB
alkej-16	25	16	control	control	NOUN
alkej-16	25	17	system	system	NOUN
alkej-16	25	18	to	to	PART
alkej-16	25	19	control	control	VERB
alkej-16	25	20	single	single	ADJ
alkej-16	25	21	-	-	PUNCT
alkej-16	25	22	input	input	NOUN
alkej-16	25	23	singleoutput	singleoutput	NOUN
alkej-16	25	24	(	(	PUNCT
alkej-16	25	25	siso	siso	NOUN
alkej-16	25	26	)	)	PUNCT
alkej-16	25	27	feedback	feedback	VERB
alkej-16	25	28	linearizable	linearizable	ADJ
alkej-16	25	29	system	system	NOUN
alkej-16	25	30	.	.	PUNCT
alkej-16	26	1	another	another	DET
alkej-16	26	2	approach	approach	NOUN
alkej-16	26	3	is	be	AUX
alkej-16	26	4	given	give	VERB
alkej-16	26	5	in	in	ADP
alkej-16	26	6	[	[	PUNCT
alkej-16	26	7	9	9	NUM
alkej-16	26	8	]	]	PUNCT
alkej-16	26	9	,	,	PUNCT
alkej-16	26	10	where	where	SCONJ
alkej-16	26	11	a	a	DET
alkej-16	26	12	neural	neural	ADJ
alkej-16	26	13	network	network	NOUN
alkej-16	26	14	is	be	AUX
alkej-16	26	15	used	use	VERB
alkej-16	26	16	to	to	PART
alkej-16	26	17	tune	tune	VERB
alkej-16	26	18	the	the	DET
alkej-16	26	19	parameters	parameter	NOUN
alkej-16	26	20	of	of	ADP
alkej-16	26	21	a	a	DET
alkej-16	26	22	conventional	conventional	ADJ
alkej-16	26	23	controller	controller	NOUN
alkej-16	26	24	in	in	ADP
alkej-16	26	25	an	an	DET
alkej-16	26	26	on	on	ADP
alkej-16	26	27	-	-	PUNCT
alkej-16	26	28	line	line	NOUN
alkej-16	26	29	way	way	NOUN
alkej-16	26	30	.	.	PUNCT
alkej-16	27	1	the	the	DET
alkej-16	27	2	organization	organization	NOUN
alkej-16	27	3	of	of	ADP
alkej-16	27	4	the	the	DET
alkej-16	27	5	paper	paper	NOUN
alkej-16	27	6	is	be	AUX
alkej-16	27	7	as	as	SCONJ
alkej-16	27	8	follows	follow	VERB
alkej-16	27	9	:	:	PUNCT
alkej-16	27	10	section	section	NOUN
alkej-16	27	11	two	two	NUM
alkej-16	27	12	describes	describe	VERB
alkej-16	27	13	the	the	DET
alkej-16	27	14	use	use	NOUN
alkej-16	27	15	of	of	ADP
alkej-16	27	16	fnns	fnn	NOUN
alkej-16	27	17	to	to	PART
alkej-16	27	18	learn	learn	VERB
alkej-16	27	19	to	to	PART
alkej-16	27	20	act	act	VERB
alkej-16	27	21	as	as	ADP
alkej-16	27	22	input	input	NOUN
alkej-16	27	23	-	-	PUNCT
alkej-16	27	24	output	output	NOUN
alkej-16	27	25	model	model	NOUN
alkej-16	27	26	.	.	PUNCT
alkej-16	28	1	model	model	NOUN
alkej-16	28	2	(	(	PUNCT
alkej-16	28	3	narma	narma	NOUN
alkej-16	28	4	-	-	PUNCT
alkej-16	28	5	l2	l2	NOUN
alkej-16	28	6	)	)	PUNCT
alkej-16	28	7	for	for	ADP
alkej-16	28	8	system	system	NOUN
alkej-16	28	9	identification	identification	NOUN
alkej-16	28	10	are	be	AUX
alkej-16	28	11	examined	examine	VERB
alkej-16	28	12	with	with	ADP
alkej-16	28	13	the	the	DET
alkej-16	28	14	corresponding	corresponding	ADJ
alkej-16	28	15	neural	neural	ADJ
alkej-16	28	16	nets	net	NOUN
alkej-16	28	17	and	and	CCONJ
alkej-16	28	18	learning	learn	VERB
alkej-16	28	19	mechanism	mechanism	NOUN
alkej-16	28	20	used	use	VERB
alkej-16	28	21	for	for	ADP
alkej-16	28	22	this	this	DET
alkej-16	28	23	purpose	purpose	NOUN
alkej-16	28	24	.	.	PUNCT
alkej-16	29	1	section	section	NOUN
alkej-16	29	2	three	three	NUM
alkej-16	29	3	represents	represent	VERB
alkej-16	29	4	the	the	DET
alkej-16	29	5	core	core	NOUN
alkej-16	29	6	of	of	ADP
alkej-16	29	7	the	the	DET
alkej-16	29	8	present	present	ADJ
alkej-16	29	9	paper	paper	NOUN
alkej-16	29	10	.	.	PUNCT
alkej-16	30	1	it	it	PRON
alkej-16	30	2	is	be	AUX
alkej-16	30	3	suggested	suggest	VERB
alkej-16	30	4	using	use	VERB
alkej-16	30	5	self	self	NOUN
alkej-16	30	6	-	-	PUNCT
alkej-16	30	7	tuning	tune	VERB
alkej-16	30	8	pid	pid	NOUN
alkej-16	30	9	neural	neural	ADJ
alkej-16	30	10	controller	controller	NOUN
alkej-16	30	11	.	.	PUNCT
alkej-16	31	1	illustrative	illustrative	ADJ
alkej-16	31	2	example	example	NOUN
alkej-16	31	3	that	that	PRON
alkej-16	31	4	clarify	clarify	VERB
alkej-16	31	5	the	the	DET
alkej-16	31	6	features	feature	NOUN
alkej-16	31	7	of	of	ADP
alkej-16	31	8	the	the	DET
alkej-16	31	9	proposed	propose	VERB
alkej-16	31	10	strategy	strategy	NOUN
alkej-16	31	11	are	be	AUX
alkej-16	31	12	given	give	VERB
alkej-16	31	13	in	in	ADP
alkej-16	31	14	section	section	NOUN
alkej-16	31	15	four	four	NUM
alkej-16	31	16	,	,	PUNCT
alkej-16	31	17	where	where	SCONJ
alkej-16	31	18	the	the	DET
alkej-16	31	19	example	example	NOUN
alkej-16	31	20	is	be	AUX
alkej-16	31	21	discussed	discuss	VERB
alkej-16	31	22	in	in	ADP
alkej-16	31	23	detail	detail	NOUN
alkej-16	31	24	.	.	PUNCT
alkej-16	32	1	finally	finally	ADV
alkej-16	32	2	,	,	PUNCT
alkej-16	32	3	section	section	NOUN
alkej-16	32	4	five	five	NUM
alkej-16	32	5	contains	contain	VERB
alkej-16	32	6	the	the	DET
alkej-16	32	7	conclusions	conclusion	NOUN
alkej-16	32	8	of	of	ADP
alkej-16	32	9	the	the	DET
alkej-16	32	10	entire	entire	ADJ
alkej-16	32	11	work	work	NOUN
alkej-16	32	12	.	.	PUNCT
alkej-16	33	1	2identification	2identification	NUM
alkej-16	33	2	of	of	ADP
alkej-16	33	3	dynamical	dynamical	ADJ
alkej-16	33	4	system	system	NOUN
alkej-16	33	5	:	:	PUNCT
alkej-16	33	6	the	the	DET
alkej-16	33	7	system	system	NOUN
alkej-16	33	8	identification	identification	NOUN
alkej-16	33	9	and	and	CCONJ
alkej-16	33	10	modeling	modeling	NOUN
alkej-16	33	11	is	be	AUX
alkej-16	33	12	a	a	DET
alkej-16	33	13	very	very	ADV
alkej-16	33	14	important	important	ADJ
alkej-16	33	15	step	step	NOUN
alkej-16	33	16	in	in	ADP
alkej-16	33	17	control	control	NOUN
alkej-16	33	18	applications	application	NOUN
alkej-16	33	19	since	since	SCONJ
alkej-16	33	20	it	it	PRON
alkej-16	33	21	is	be	AUX
alkej-16	33	22	a	a	DET
alkej-16	33	23	prerequisitic	prerequisitic	NOUN
alkej-16	33	24	for	for	ADP
alkej-16	33	25	analysis	analysis	NOUN
alkej-16	33	26	and	and	CCONJ
alkej-16	33	27	controller	controller	NOUN
alkej-16	33	28	design	design	NOUN
alkej-16	33	29	.	.	PUNCT
alkej-16	34	1	due	due	ADP
alkej-16	34	2	to	to	ADP
alkej-16	34	3	the	the	DET
alkej-16	34	4	nonlinear	nonlinear	ADJ
alkej-16	34	5	nature	nature	NOUN
alkej-16	34	6	of	of	ADP
alkej-16	34	7	most	most	ADJ
alkej-16	34	8	of	of	ADP
alkej-16	34	9	the	the	DET
alkej-16	34	10	processes	process	NOUN
alkej-16	34	11	encountered	encounter	VERB
alkej-16	34	12	in	in	ADP
alkej-16	34	13	many	many	ADJ
alkej-16	34	14	engineering	engineering	NOUN
alkej-16	34	15	applications	application	NOUN
alkej-16	34	16	there	there	PRON
alkej-16	34	17	has	have	AUX
alkej-16	34	18	been	be	AUX
alkej-16	34	19	extensive	extensive	ADJ
alkej-16	34	20	research	research	NOUN
alkej-16	34	21	covering	cover	VERB
alkej-16	34	22	the	the	DET
alkej-16	34	23	field	field	NOUN
alkej-16	34	24	of	of	ADP
alkej-16	34	25	nonlinear	nonlinear	ADJ
alkej-16	34	26	system	system	NOUN
alkej-16	34	27	identification	identification	NOUN
alkej-16	34	28	[	[	X
alkej-16	34	29	10	10	NUM
alkej-16	34	30	]	]	PUNCT
alkej-16	34	31	.	.	PUNCT
alkej-16	35	1	this	this	DET
alkej-16	35	2	section	section	NOUN
alkej-16	35	3	focuses	focus	VERB
alkej-16	35	4	on	on	ADP
alkej-16	35	5	nonlinear	nonlinear	ADJ
alkej-16	35	6	system	system	NOUN
alkej-16	35	7	identification	identification	NOUN
alkej-16	35	8	using	use	VERB
alkej-16	35	9	the	the	DET
alkej-16	35	10	model	model	NOUN
alkej-16	35	11	of	of	ADP
alkej-16	35	12	multilayered	multilayered	ADJ
alkej-16	35	13	feedforward	feedforward	ADJ
alkej-16	35	14	neural	neural	ADJ
alkej-16	35	15	network	network	NOUN
alkej-16	35	16	,	,	PUNCT
alkej-16	35	17	narma	narma	NOUN
alkej-16	35	18	-	-	PUNCT
alkej-16	35	19	l2	l2	NOUN
alkej-16	35	20	model	model	NOUN
alkej-16	35	21	.	.	PUNCT
alkej-16	36	1	the	the	DET
alkej-16	36	2	neural	neural	ADJ
alkej-16	36	3	network	network	NOUN
alkej-16	36	4	is	be	AUX
alkej-16	36	5	trained	train	VERB
alkej-16	36	6	using	use	VERB
alkej-16	36	7	backpropagation	backpropagation	NOUN
alkej-16	36	8	algorithm	algorithm	NOUN
alkej-16	36	9	.	.	PUNCT
alkej-16	37	1	to	to	PART
alkej-16	37	2	describe	describe	VERB
alkej-16	37	3	the	the	DET
alkej-16	37	4	process	process	NOUN
alkej-16	37	5	by	by	ADP
alkej-16	37	6	using	use	VERB
alkej-16	37	7	artificial	artificial	ADJ
alkej-16	37	8	neurons	neuron	NOUN
alkej-16	37	9	as	as	ADP
alkej-16	37	10	basic	basic	ADJ
alkej-16	37	11	building	building	NOUN
alkej-16	37	12	elements	element	NOUN
alkej-16	37	13	for	for	ADP
alkej-16	37	14	the	the	DET
alkej-16	37	15	development	development	NOUN
alkej-16	37	16	of	of	ADP
alkej-16	37	17	multi	multi	ADJ
alkej-16	37	18	-	-	ADJ
alkej-16	37	19	layered	layered	ADJ
alkej-16	37	20	and	and	CCONJ
alkej-16	37	21	higher	high	ADJ
alkej-16	37	22	order	order	NOUN
alkej-16	37	23	neural	neural	ADJ
alkej-16	37	24	network	network	NOUN
alkej-16	37	25	,	,	PUNCT
alkej-16	37	26	the	the	DET
alkej-16	37	27	feedforward	feedforward	ADJ
alkej-16	37	28	neural	neural	ADJ
alkej-16	37	29	networks	network	NOUN
alkej-16	37	30	are	be	AUX
alkej-16	37	31	widely	widely	ADV
alkej-16	37	32	used	use	VERB
alkej-16	37	33	.	.	PUNCT
alkej-16	38	1	the	the	DET
alkej-16	38	2	learning	learning	NOUN
alkej-16	38	3	scheme	scheme	NOUN
alkej-16	38	4	for	for	ADP
alkej-16	38	5	feedforward	feedforward	NOUN
alkej-16	38	6	neural	neural	ADJ
alkej-16	38	7	networks	network	NOUN
alkej-16	38	8	presented	present	VERB
alkej-16	38	9	in	in	ADP
alkej-16	38	10	this	this	DET
alkej-16	38	11	section	section	NOUN
alkej-16	38	12	includes	include	VERB
alkej-16	38	13	the	the	DET
alkej-16	38	14	generalized	generalized	ADJ
alkej-16	38	15	delta	delta	NOUN
alkej-16	38	16	rule	rule	NOUN
alkej-16	38	17	based	base	VERB
alkej-16	38	18	algorithms	algorithm	NOUN
alkej-16	38	19	for	for	ADP
alkej-16	38	20	error	error	NOUN
alkej-16	38	21	back	back	NOUN
alkej-16	38	22	propagation	propagation	NOUN
alkej-16	38	23	for	for	ADP
alkej-16	38	24	multi	multi	ADJ
alkej-16	38	25	-	-	ADJ
alkej-16	38	26	layers	layers	ADJ
alkej-16	38	27	neural	neural	ADJ
alkej-16	38	28	networks	network	NOUN
alkej-16	38	29	[	[	X
alkej-16	38	30	11	11	NUM
alkej-16	38	31	]	]	PUNCT
alkej-16	38	32	.	.	PUNCT
alkej-16	39	1	a	a	DET
alkej-16	39	2	feedforward	feedforward	ADJ
alkej-16	39	3	neural	neural	ADJ
alkej-16	39	4	network	network	NOUN
alkej-16	39	5	can	can	AUX
alkej-16	39	6	be	be	AUX
alkej-16	39	7	seen	see	VERB
alkej-16	39	8	as	as	ADP
alkej-16	39	9	a	a	DET
alkej-16	39	10	system	system	NOUN
alkej-16	39	11	transforming	transform	VERB
alkej-16	39	12	a	a	DET
alkej-16	39	13	set	set	NOUN
alkej-16	39	14	of	of	ADP
alkej-16	39	15	input	input	NOUN
alkej-16	39	16	patterns	pattern	NOUN
alkej-16	39	17	into	into	ADP
alkej-16	39	18	a	a	DET
alkej-16	39	19	set	set	NOUN
alkej-16	39	20	of	of	ADP
alkej-16	39	21	output	output	NOUN
alkej-16	39	22	patterns	pattern	NOUN
alkej-16	39	23	,	,	PUNCT
alkej-16	39	24	and	and	CCONJ
alkej-16	39	25	such	such	DET
alkej-16	39	26	a	a	DET
alkej-16	39	27	network	network	NOUN
alkej-16	39	28	can	can	AUX
alkej-16	39	29	be	be	AUX
alkej-16	39	30	trained	train	VERB
alkej-16	39	31	to	to	PART
alkej-16	39	32	provide	provide	VERB
alkej-16	39	33	a	a	DET
alkej-16	39	34	desired	desire	VERB
alkej-16	39	35	response	response	NOUN
alkej-16	39	36	to	to	ADP
alkej-16	39	37	a	a	DET
alkej-16	39	38	given	give	VERB
alkej-16	39	39	input	input	NOUN
alkej-16	39	40	.	.	PUNCT
alkej-16	40	1	the	the	DET
alkej-16	40	2	network	network	NOUN
alkej-16	40	3	achieves	achieve	VERB
alkej-16	40	4	such	such	DET
alkej-16	40	5	a	a	DET
alkej-16	40	6	behavior	behavior	NOUN
alkej-16	40	7	by	by	ADP
alkej-16	40	8	adapting	adapt	VERB
alkej-16	40	9	its	its	PRON
alkej-16	40	10	weights	weight	NOUN
alkej-16	40	11	during	during	ADP
alkej-16	40	12	the	the	DET
alkej-16	40	13	learning	learning	NOUN
alkej-16	40	14	phase	phase	NOUN
alkej-16	40	15	on	on	ADP
alkej-16	40	16	the	the	DET
alkej-16	40	17	basis	basis	NOUN
alkej-16	40	18	of	of	ADP
alkej-16	40	19	some	some	DET
alkej-16	40	20	learning	learning	NOUN
alkej-16	40	21	rules	rule	NOUN
alkej-16	40	22	.	.	PUNCT
alkej-16	41	1	the	the	DET
alkej-16	41	2	training	training	NOUN
alkej-16	41	3	of	of	ADP
alkej-16	41	4	feedforward	feedforward	ADJ
alkej-16	41	5	neural	neural	ADJ
alkej-16	41	6	networks	network	NOUN
alkej-16	41	7	often	often	ADV
alkej-16	41	8	requires	require	VERB
alkej-16	41	9	the	the	DET
alkej-16	41	10	existence	existence	NOUN
alkej-16	41	11	of	of	ADP
alkej-16	41	12	a	a	DET
alkej-16	41	13	set	set	NOUN
alkej-16	41	14	of	of	ADP
alkej-16	41	15	input	input	NOUN
alkej-16	41	16	and	and	CCONJ
alkej-16	41	17	output	output	NOUN
alkej-16	41	18	patterns	pattern	NOUN
alkej-16	41	19	called	call	VERB
alkej-16	41	20	the	the	DET
alkej-16	41	21	training	training	NOUN
alkej-16	41	22	set	set	NOUN
alkej-16	41	23	[	[	X
alkej-16	41	24	11	11	NUM
alkej-16	41	25	]	]	PUNCT
alkej-16	41	26	and	and	CCONJ
alkej-16	41	27	this	this	DET
alkej-16	41	28	kind	kind	NOUN
alkej-16	41	29	of	of	ADP
alkej-16	41	30	learning	learning	NOUN
alkej-16	41	31	is	be	AUX
alkej-16	41	32	called	call	VERB
alkej-16	41	33	supervised	supervised	ADJ
alkej-16	41	34	learning	learning	NOUN
alkej-16	41	35	.	.	PUNCT
alkej-16	42	1	the	the	DET
alkej-16	42	2	feedforward	feedforward	ADJ
alkej-16	42	3	network	network	NOUN
alkej-16	42	4	used	use	VERB
alkej-16	42	5	here	here	ADV
alkej-16	42	6	has	have	VERB
alkej-16	42	7	two	two	NUM
alkej-16	42	8	layers	layer	NOUN
alkej-16	42	9	,	,	PUNCT
alkej-16	42	10	the	the	DET
alkej-16	42	11	first	first	ADJ
alkej-16	42	12	is	be	AUX
alkej-16	42	13	the	the	DET
alkej-16	42	14	hidden	hidden	ADJ
alkej-16	42	15	layer	layer	NOUN
alkej-16	42	16	and	and	CCONJ
alkej-16	42	17	the	the	DET
alkej-16	42	18	second	second	NOUN
alkej-16	42	19	is	be	AUX
alkej-16	42	20	the	the	DET
alkej-16	42	21	output	output	NOUN
alkej-16	42	22	layer	layer	NOUN
alkej-16	42	23	where	where	SCONJ
alkej-16	42	24	ahmed	ahmed	PROPN
alkej-16	42	25	sabah	sabah	PROPN
alkej-16	42	26	abdul	abdul	PROPN
alkej-16	42	27	ameer	ameer	PROPN
alkej-16	42	28	/al	/al	PROPN
alkej-16	42	29	khwarizmi	khwarizmi	PROPN
alkej-16	42	30	engineering	engineering	PROPN
alkej-16	42	31	journal	journal	PROPN
alkej-16	42	32	,	,	PUNCT
alkej-16	42	33	vol	vol	NOUN
alkej-16	42	34	.	.	PROPN
alkej-16	43	1	1	1	NUM
alkej-16	43	2	,	,	PUNCT
alkej-16	43	3	no	no	INTJ
alkej-16	43	4	.	.	NOUN
alkej-16	43	5	1	1	NUM
alkej-16	43	6	,	,	PUNCT
alkej-16	43	7	pp	pp	ADV
alkej-16	43	8	1	1	NUM
alkej-16	43	9	-	-	SYM
alkej-16	43	10	18	18	NUM
alkej-16	43	11	(	(	PUNCT
alkej-16	43	12	2005	2005	NUM
alkej-16	43	13	)	)	PUNCT
alkej-16	43	14	٣	٣	NUM
alkej-16	43	15	each	each	DET
alkej-16	43	16	unit	unit	NOUN
alkej-16	43	17	in	in	ADP
alkej-16	43	18	the	the	DET
alkej-16	43	19	hidden	hide	VERB
alkej-16	43	20	layer	layer	NOUN
alkej-16	43	21	has	have	VERB
alkej-16	43	22	a	a	DET
alkej-16	43	23	continuous	continuous	ADJ
alkej-16	43	24	sigmoidal	sigmoidal	NOUN
alkej-16	43	25	nonlinearity	nonlinearity	NOUN
alkej-16	43	26	[	[	X
alkej-16	43	27	12	12	NUM
alkej-16	43	28	]	]	PUNCT
alkej-16	43	29	and	and	CCONJ
alkej-16	43	30	the	the	DET
alkej-16	43	31	output	output	NOUN
alkej-16	43	32	node	node	NOUN
alkej-16	43	33	has	have	VERB
alkej-16	43	34	linear	linear	ADJ
alkej-16	43	35	activation	activation	NOUN
alkej-16	43	36	function	function	NOUN
alkej-16	43	37	.	.	PUNCT
alkej-16	44	1	narma	narma	NOUN
alkej-16	44	2	-	-	PUNCT
alkej-16	44	3	l2	l2	NOUN
alkej-16	44	4	model	model	NOUN
alkej-16	44	5	identification	identification	NOUN
alkej-16	44	6	:	:	PUNCT
alkej-16	44	7	nonlinear	nonlinear	ADJ
alkej-16	44	8	input	input	NOUN
alkej-16	44	9	-	-	PUNCT
alkej-16	44	10	output	output	NOUN
alkej-16	44	11	behavior	behavior	NOUN
alkej-16	44	12	can	can	AUX
alkej-16	44	13	be	be	AUX
alkej-16	44	14	well	well	ADV
alkej-16	44	15	approximated	approximate	VERB
alkej-16	44	16	by	by	ADP
alkej-16	44	17	narma	narma	NOUN
alkej-16	44	18	-	-	PUNCT
alkej-16	44	19	l2	l2	NOUN
alkej-16	44	20	(	(	PUNCT
alkej-16	44	21	nonlinear	nonlinear	ADJ
alkej-16	44	22	auto	auto	NOUN
alkej-16	44	23	regressive	regressive	ADJ
alkej-16	44	24	moving	move	VERB
alkej-16	44	25	average	average	ADJ
alkej-16	44	26	-	-	PUNCT
alkej-16	44	27	linear	linear	NOUN
alkej-16	44	28	)	)	PUNCT
alkej-16	44	29	two	two	NUM
alkej-16	44	30	model	model	NOUN
alkej-16	44	31	which	which	PRON
alkej-16	44	32	can	can	AUX
alkej-16	44	33	be	be	AUX
alkej-16	44	34	expressed	express	VERB
alkej-16	44	35	as	as	ADP
alkej-16	44	36	[	[	X
alkej-16	44	37	13	13	NUM
alkej-16	44	38	]	]	NUM
alkej-16	44	39	:	:	PUNCT
alkej-16	44	40	)	)	PUNCT
alkej-16	45	1	]	]	X
alkej-16	45	2	1(),	1(),	NUM
alkej-16	45	3	...	...	PUNCT
alkej-16	45	4	,1(),1(),	,1(),1(),	PUNCT
alkej-16	45	5	...	...	PUNCT
alkej-16	45	6	,([)1	,([)1	PUNCT
alkej-16	45	7	(	(	PUNCT
alkej-16	45	8	+	+	ADV
alkej-16	45	9	−−+−=+	−−+−=+	INTJ
alkej-16	45	10	nkukunkykyfky	nkukunkykyfky	ADJ
alkej-16	45	11	ppp	ppp	PROPN
alkej-16	45	12	)	)	PUNCT
alkej-16	45	13	k(u)]1nk(u),	k(u)]1nk(u),	PROPN
alkej-16	45	14	...	...	PUNCT
alkej-16	45	15	,1k(u),1nk(y),	,1k(u),1nk(y),	PUNCT
alkej-16	45	16	...	...	PUNCT
alkej-16	45	17	k(y[g	k(y[g	X
alkej-16	46	1	pp	pp	ADV
alkej-16	46	2	×+−−+−+	×+−−+−+	PROPN
alkej-16	46	3	...	...	PUNCT
alkej-16	46	4	(	(	PUNCT
alkej-16	46	5	1	1	X
alkej-16	46	6	)	)	PUNCT
alkej-16	46	7	where	where	SCONJ
alkej-16	46	8	n	n	PRON
alkej-16	46	9	is	be	AUX
alkej-16	46	10	the	the	DET
alkej-16	46	11	order	order	NOUN
alkej-16	46	12	of	of	ADP
alkej-16	46	13	the	the	DET
alkej-16	46	14	system	system	NOUN
alkej-16	46	15	.	.	PUNCT
alkej-16	47	1	the	the	DET
alkej-16	47	2	narma	narma	NOUN
alkej-16	47	3	-	-	PUNCT
alkej-16	47	4	l2	l2	NOUN
alkej-16	47	5	model	model	NOUN
alkej-16	47	6	requires	require	VERB
alkej-16	47	7	only	only	ADV
alkej-16	47	8	two	two	NUM
alkej-16	47	9	neural	neural	ADJ
alkej-16	47	10	networks	network	NOUN
alkej-16	47	11	to	to	PART
alkej-16	47	12	approximate	approximate	VERB
alkej-16	47	13	the	the	DET
alkej-16	47	14	function	function	NOUN
alkej-16	47	15	f	f	PROPN
alkej-16	47	16	and	and	CCONJ
alkej-16	47	17	g.	g.	PROPN
alkej-16	47	18	each	each	PRON
alkej-16	47	19	of	of	ADP
alkej-16	47	20	the	the	DET
alkej-16	47	21	two	two	NUM
alkej-16	47	22	.	.	PUNCT
alkej-16	48	1	functions	function	NOUN
alkej-16	48	2	,	,	PUNCT
alkej-16	48	3	however	however	ADV
alkej-16	48	4	has	have	VERB
alkej-16	48	5	(	(	PUNCT
alkej-16	48	6	2n-1	2n-1	NOUN
alkej-16	48	7	)	)	PUNCT
alkej-16	48	8	inputs	input	NOUN
alkej-16	48	9	by	by	ADP
alkej-16	48	10	using	use	VERB
alkej-16	48	11	narma	narma	NOUN
alkej-16	48	12	-	-	PUNCT
alkej-16	48	13	l2	l2	NOUN
alkej-16	48	14	model	model	NOUN
alkej-16	48	15	the	the	DET
alkej-16	48	16	weights	weight	NOUN
alkej-16	48	17	of	of	ADP
alkej-16	48	18	the	the	DET
alkej-16	48	19	neural	neural	ADJ
alkej-16	48	20	networks	network	NOUN
alkej-16	48	21	are	be	AUX
alkej-16	48	22	adjusted	adjust	VERB
alkej-16	48	23	in	in	ADP
alkej-16	48	24	a	a	DET
alkej-16	48	25	similar	similar	ADJ
alkej-16	48	26	manner	manner	NOUN
alkej-16	48	27	when	when	SCONJ
alkej-16	48	28	using	use	VERB
alkej-16	48	29	the	the	DET
alkej-16	48	30	narma	narma	NOUN
alkej-16	48	31	model	model	NOUN
alkej-16	48	32	.	.	PUNCT
alkej-16	48	33	)	)	PUNCT
alkej-16	49	1	]	]	X
alkej-16	49	2	1nk(u),	1nk(u),	X
alkej-16	49	3	...	...	PUNCT
alkej-16	49	4	k(u),1nk(y),	k(u),1nk(y),	PROPN
alkej-16	49	5	...	...	PUNCT
alkej-16	49	6	,k(y[f)1k(y	,k(y[f)1k(y	PUNCT
alkej-16	50	1	ppp	ppp	PROPN
alkej-16	50	2	+	+	PROPN
alkej-16	50	3	−+−=+	−+−=+	PROPN
alkej-16	50	4	…	…	PUNCT
alkej-16	50	5	(	(	PUNCT
alkej-16	50	6	2	2	NUM
alkej-16	50	7	)	)	PUNCT
alkej-16	50	8	the	the	DET
alkej-16	50	9	difference	difference	NOUN
alkej-16	50	10	between	between	ADP
alkej-16	50	11	them	they	PRON
alkej-16	50	12	is	be	AUX
alkej-16	50	13	that	that	SCONJ
alkej-16	50	14	narma	narma	NOUN
alkej-16	50	15	-	-	PUNCT
alkej-16	50	16	l2	l2	NOUN
alkej-16	50	17	model	model	NOUN
alkej-16	50	18	consists	consist	VERB
alkej-16	50	19	of	of	ADP
alkej-16	50	20	two	two	NUM
alkej-16	50	21	functions	function	NOUN
alkej-16	50	22	f[-	f[-	NOUN
alkej-16	50	23	]	]	PUNCT
alkej-16	50	24	and	and	CCONJ
alkej-16	50	25	g[-	g[-	PROPN
alkej-16	50	26	]	]	PUNCT
alkej-16	50	27	in	in	ADP
alkej-16	50	28	equation	equation	NOUN
alkej-16	50	29	(	(	PUNCT
alkej-16	50	30	1	1	X
alkej-16	50	31	)	)	PUNCT
alkej-16	50	32	while	while	SCONJ
alkej-16	50	33	one	one	NUM
alkej-16	50	34	neural	neural	ADJ
alkej-16	50	35	network	network	NOUN
alkej-16	50	36	is	be	AUX
alkej-16	50	37	needed	need	VERB
alkej-16	50	38	for	for	ADP
alkej-16	50	39	narma	narma	NOUN
alkej-16	50	40	model	model	NOUN
alkej-16	50	41	.	.	PUNCT
alkej-16	51	1	the	the	DET
alkej-16	51	2	first	first	ADJ
alkej-16	51	3	step	step	NOUN
alkej-16	51	4	in	in	ADP
alkej-16	51	5	the	the	DET
alkej-16	51	6	identification	identification	NOUN
alkej-16	51	7	procedure	procedure	NOUN
alkej-16	51	8	using	use	VERB
alkej-16	51	9	feedforward	feedforward	ADJ
alkej-16	51	10	neural	neural	ADJ
alkej-16	51	11	network	network	NOUN
alkej-16	51	12	is	be	AUX
alkej-16	51	13	quite	quite	ADV
alkej-16	51	14	straightforward	straightforward	ADJ
alkej-16	51	15	with	with	ADP
alkej-16	51	16	serial	serial	ADJ
alkej-16	51	17	parallel	parallel	ADJ
alkej-16	51	18	model	model	NOUN
alkej-16	51	19	and	and	CCONJ
alkej-16	51	20	at	at	ADP
alkej-16	51	21	each	each	DET
alkej-16	51	22	instant	instant	NOUN
alkej-16	51	23	of	of	ADP
alkej-16	51	24	time	time	NOUN
alkej-16	51	25	.	.	PUNCT
alkej-16	52	1	the	the	DET
alkej-16	52	2	past	past	ADJ
alkej-16	52	3	inputs	input	NOUN
alkej-16	52	4	and	and	CCONJ
alkej-16	52	5	the	the	DET
alkej-16	52	6	past	past	ADJ
alkej-16	52	7	outputs	output	NOUN
alkej-16	52	8	of	of	ADP
alkej-16	52	9	the	the	DET
alkej-16	52	10	system	system	NOUN
alkej-16	52	11	are	be	AUX
alkej-16	52	12	fed	feed	VERB
alkej-16	52	13	into	into	ADP
alkej-16	52	14	the	the	DET
alkej-16	52	15	neural	neural	ADJ
alkej-16	52	16	network	network	NOUN
alkej-16	52	17	as	as	SCONJ
alkej-16	52	18	shown	show	VERB
alkej-16	52	19	fig	fig	NOUN
alkej-16	52	20	(	(	PUNCT
alkej-16	52	21	1	1	NUM
alkej-16	52	22	)	)	PUNCT
alkej-16	52	23	.	.	PUNCT
alkej-16	53	1	plant	plant	NOUN
alkej-16	53	2	h	h	NOUN
alkej-16	53	3	h	h	NOUN
alkej-16	54	1	l	l	PROPN
alkej-16	54	2	n1=	n1=	PUNCT
alkej-16	54	3	]	]	PUNCT
alkej-16	54	4	[	[	PUNCT
alkej-16	54	5	−	−	PROPN
alkej-16	54	6	∧	∧	PROPN
alkej-16	54	7	f	f	PROPN
alkej-16	54	8	h	h	NOUN
alkej-16	54	9	h	h	NOUN
alkej-16	54	10	l	l	PROPN
alkej-16	54	11	n2=	n2=	PROPN
alkej-16	54	12	]	]	PUNCT
alkej-16	55	1	[	[	X
alkej-16	55	2	−	−	X
alkej-16	55	3	∧	∧	PROPN
alkej-16	55	4	g	g	PROPN
alkej-16	55	5	1z−	1z−	PROPN
alkej-16	55	6	1nz	1nz	NOUN
alkej-16	55	7	+	+	ADP
alkej-16	55	8	−	−	NOUN
alkej-16	55	9	y2	y2	ADJ
alkej-16	55	10	y1	y1	NOUN
alkej-16	55	11	training	training	NOUN
alkej-16	55	12	mechanism	mechanism	NOUN
alkej-16	55	13	+	+	X
alkej-16	55	14	+	+	CCONJ
alkej-16	55	15	+	+	CCONJ
alkej-16	55	16	1nz	1nz	ADJ
alkej-16	55	17	+	+	ADJ
alkej-16	55	18	−	−	PROPN
alkej-16	55	19	1z−	1z−	PROPN
alkej-16	55	20	u(k	u(k	PROPN
alkej-16	55	21	)	)	PUNCT
alkej-16	55	22	y	y	PROPN
alkej-16	55	23	m	m	PROPN
alkej-16	55	24	(	(	PUNCT
alkej-16	55	25	k+1	k+1	X
alkej-16	55	26	)	)	PUNCT
alkej-16	55	27	y	y	PROPN
alkej-16	55	28	p	p	PROPN
alkej-16	55	29	(	(	PUNCT
alkej-16	55	30	k+1	k+1	NOUN
alkej-16	55	31	)	)	PUNCT
alkej-16	55	32	fig	fig	NOUN
alkej-16	55	33	(	(	PUNCT
alkej-16	55	34	1	1	NUM
alkej-16	55	35	):	):	PUNCT
alkej-16	55	36	narma	narma	NOUN
alkej-16	55	37	-	-	PUNCT
alkej-16	55	38	l2	l2	NOUN
alkej-16	55	39	identification	identification	NOUN
alkej-16	55	40	model	model	NOUN
alkej-16	55	41	serial	serial	ADJ
alkej-16	55	42	-	-	PUNCT
alkej-16	55	43	parallel	parallel	ADJ
alkej-16	55	44	configuration	configuration	NOUN
alkej-16	55	45	×	×	NOUN
alkej-16	55	46	ahmed	ahmed	PROPN
alkej-16	55	47	sabah	sabah	PROPN
alkej-16	55	48	abdul	abdul	PROPN
alkej-16	55	49	ameer	ameer	PROPN
alkej-16	55	50	/al	/al	PROPN
alkej-16	55	51	khwarizmi	khwarizmi	PROPN
alkej-16	55	52	engineering	engineering	PROPN
alkej-16	55	53	journal	journal	PROPN
alkej-16	55	54	,	,	PUNCT
alkej-16	55	55	vol	vol	NOUN
alkej-16	55	56	.	.	PROPN
alkej-16	55	57	1	1	NUM
alkej-16	55	58	,	,	PUNCT
alkej-16	55	59	no	no	INTJ
alkej-16	55	60	.	.	NOUN
alkej-16	55	61	1	1	NUM
alkej-16	55	62	,	,	PUNCT
alkej-16	55	63	pp	pp	ADV
alkej-16	55	64	1	1	NUM
alkej-16	55	65	-	-	SYM
alkej-16	55	66	18	18	NUM
alkej-16	55	67	(	(	PUNCT
alkej-16	55	68	2005	2005	NUM
alkej-16	55	69	)	)	PUNCT
alkej-16	55	70	٤	٤	PROPN
alkej-16	55	71	the	the	DET
alkej-16	55	72	network	network	NOUN
alkej-16	55	73	’s	’s	PART
alkej-16	55	74	output	output	NOUN
alkej-16	55	75	yields	yield	VERB
alkej-16	55	76	the	the	DET
alkej-16	55	77	prediction	prediction	NOUN
alkej-16	55	78	error	error	NOUN
alkej-16	55	79	:	:	PUNCT
alkej-16	55	80	)	)	PUNCT
alkej-16	56	1	1k(y)1k(y)1k(e	1k(y)1k(y)1k(e	NUM
alkej-16	56	2	mp	mp	NOUN
alkej-16	56	3	+	+	NOUN
alkej-16	56	4	−+=+	−+=+	NOUN
alkej-16	56	5	…	…	PUNCT
alkej-16	56	6	(	(	PUNCT
alkej-16	56	7	3	3	X
alkej-16	56	8	)	)	PUNCT
alkej-16	56	9	the	the	DET
alkej-16	56	10	identification	identification	NOUN
alkej-16	56	11	model	model	NOUN
alkej-16	56	12	for	for	ADP
alkej-16	56	13	the	the	DET
alkej-16	56	14	narma	narma	NOUN
alkej-16	56	15	-	-	PUNCT
alkej-16	56	16	l2	l2	NOUN
alkej-16	56	17	model	model	NOUN
alkej-16	56	18	can	can	AUX
alkej-16	56	19	be	be	AUX
alkej-16	56	20	better	well	ADV
alkej-16	56	21	illustrated	illustrate	VERB
alkej-16	56	22	as	as	ADP
alkej-16	56	23	fig.1	fig.1	PROPN
alkej-16	56	24	,	,	PUNCT
alkej-16	56	25	where	where	SCONJ
alkej-16	56	26	x	x	PRON
alkej-16	56	27	represents	represent	VERB
alkej-16	56	28	the	the	DET
alkej-16	56	29	input	input	NOUN
alkej-16	56	30	vector	vector	NOUN
alkej-16	56	31	of	of	ADP
alkej-16	56	32	the	the	DET
alkej-16	56	33	networks	network	NOUN
alkej-16	56	34	n1	n1	PROPN
alkej-16	56	35	and	and	CCONJ
alkej-16	56	36	n2	n2	PROPN
alkej-16	56	37	(	(	PUNCT
alkej-16	56	38	the	the	DET
alkej-16	56	39	argument	argument	NOUN
alkej-16	56	40	of	of	ADP
alkej-16	56	41	]	]	PUNCT
alkej-16	57	1	[	[	X
alkej-16	57	2	f	f	X
alkej-16	57	3	−	−	PROPN
alkej-16	57	4	∧	∧	PROPN
alkej-16	57	5	and	and	CCONJ
alkej-16	57	6	]	]	PUNCT
alkej-16	57	7	[	[	X
alkej-16	57	8	g	g	X
alkej-16	57	9	−	−	PROPN
alkej-16	57	10	∧	∧	PROPN
alkej-16	57	11	)	)	PUNCT
alkej-16	57	12	.	.	PUNCT
alkej-16	58	1	the	the	DET
alkej-16	58	2	learning	learning	NOUN
alkej-16	58	3	(	(	PUNCT
alkej-16	58	4	training	training	NOUN
alkej-16	58	5	)	)	PUNCT
alkej-16	58	6	algorithm	algorithm	NOUN
alkej-16	58	7	is	be	AUX
alkej-16	58	8	usually	usually	ADV
alkej-16	58	9	based	base	VERB
alkej-16	58	10	on	on	ADP
alkej-16	58	11	the	the	DET
alkej-16	58	12	minimization	minimization	NOUN
alkej-16	58	13	(	(	PUNCT
alkej-16	58	14	with	with	ADP
alkej-16	58	15	respect	respect	NOUN
alkej-16	58	16	to	to	ADP
alkej-16	58	17	the	the	DET
alkej-16	58	18	network	network	NOUN
alkej-16	58	19	weights	weight	NOUN
alkej-16	58	20	)	)	PUNCT
alkej-16	58	21	of	of	ADP
alkej-16	58	22	the	the	DET
alkej-16	58	23	following	follow	VERB
alkej-16	58	24	objective	objective	ADJ
alkej-16	58	25	cost	cost	NOUN
alkej-16	58	26	function	function	NOUN
alkej-16	58	27	:	:	PUNCT
alkej-16	58	28	∑	∑	PUNCT
alkej-16	58	29	∑	∑	PUNCT
alkej-16	58	30	=	=	PUNCT
alkej-16	58	31	=	=	PUNCT
alkej-16	59	1	+	+	NOUN
alkej-16	59	2	−+=+=	−+=+=	NOUN
alkej-16	60	1	np	np	INTJ
alkej-16	60	2	i	i	PRON
alkej-16	61	1	np	np	INTJ
alkej-16	61	2	i	i	PRON
alkej-16	62	1	i	i	PRON
alkej-16	62	2	m	m	VERB
alkej-16	63	1	i	i	PRON
alkej-16	63	2	p	p	X
alkej-16	64	1	i	i	PRON
alkej-16	64	2	kykykee	kykykee	VERB
alkej-16	64	3	1	1	NUM
alkej-16	64	4	1	1	NUM
alkej-16	64	5	22	22	NUM
alkej-16	64	6	)	)	PUNCT
alkej-16	64	7	)	)	PUNCT
alkej-16	65	1	1()1	1()1	NUM
alkej-16	65	2	(	(	PUNCT
alkej-16	65	3	(	(	PUNCT
alkej-16	65	4	2	2	NUM
alkej-16	65	5	1))1	1))1	NUM
alkej-16	65	6	(	(	PUNCT
alkej-16	65	7	(	(	PUNCT
alkej-16	65	8	2	2	NUM
alkej-16	65	9	1	1	NUM
alkej-16	65	10	…	…	PUNCT
alkej-16	65	11	(	(	PUNCT
alkej-16	65	12	4	4	NUM
alkej-16	65	13	)	)	PUNCT
alkej-16	65	14	where	where	SCONJ
alkej-16	65	15	np	np	PRON
alkej-16	65	16	is	be	AUX
alkej-16	65	17	number	number	NOUN
alkej-16	65	18	of	of	ADP
alkej-16	65	19	patterns	pattern	NOUN
alkej-16	65	20	,	,	PUNCT
alkej-16	65	21	ie	ie	X
alkej-16	65	22	is	be	VERB
alkej-16	65	23	the	the	DET
alkej-16	65	24	error	error	NOUN
alkej-16	65	25	of	of	ADP
alkej-16	65	26	each	each	DET
alkej-16	65	27	step	step	NOUN
alkej-16	65	28	,	,	PUNCT
alkej-16	65	29	i	i	PRON
alkej-16	65	30	py	py	VERB
alkej-16	65	31	is	be	AUX
alkej-16	65	32	the	the	DET
alkej-16	65	33	actual	actual	ADJ
alkej-16	65	34	output	output	NOUN
alkej-16	65	35	of	of	ADP
alkej-16	65	36	the	the	DET
alkej-16	65	37	plant	plant	NOUN
alkej-16	65	38	of	of	ADP
alkej-16	65	39	each	each	DET
alkej-16	65	40	step	step	NOUN
alkej-16	65	41	and	and	CCONJ
alkej-16	65	42	i	i	PRON
alkej-16	65	43	my	my	PRON
alkej-16	65	44	is	be	AUX
alkej-16	65	45	the	the	DET
alkej-16	65	46	model	model	NOUN
alkej-16	65	47	output	output	NOUN
alkej-16	65	48	of	of	ADP
alkej-16	65	49	the	the	DET
alkej-16	65	50	plant	plant	NOUN
alkej-16	65	51	of	of	ADP
alkej-16	65	52	each	each	DET
alkej-16	65	53	step	step	NOUN
alkej-16	65	54	.	.	PUNCT
alkej-16	66	1	from	from	ADP
alkej-16	66	2	fig.1	fig.1	PROPN
alkej-16	66	3	,	,	PUNCT
alkej-16	66	4	it	it	PRON
alkej-16	66	5	is	be	AUX
alkej-16	66	6	important	important	ADJ
alkej-16	66	7	to	to	PART
alkej-16	66	8	note	note	VERB
alkej-16	66	9	that	that	SCONJ
alkej-16	66	10	the	the	DET
alkej-16	66	11	error	error	NOUN
alkej-16	66	12	between	between	ADP
alkej-16	66	13	the	the	DET
alkej-16	66	14	desired	desire	VERB
alkej-16	66	15	output	output	NOUN
alkej-16	66	16	and	and	CCONJ
alkej-16	66	17	the	the	DET
alkej-16	66	18	estimated	estimate	VERB
alkej-16	66	19	neural	neural	ADJ
alkej-16	66	20	network	network	NOUN
alkej-16	66	21	output	output	NOUN
alkej-16	66	22	needed	need	VERB
alkej-16	66	23	to	to	PART
alkej-16	66	24	apply	apply	VERB
alkej-16	66	25	a	a	DET
alkej-16	66	26	supervised	supervised	ADJ
alkej-16	66	27	learning	learning	NOUN
alkej-16	66	28	algorithm	algorithm	NOUN
alkej-16	66	29	which	which	PRON
alkej-16	66	30	is	be	AUX
alkej-16	66	31	not	not	PART
alkej-16	66	32	available	available	ADJ
alkej-16	66	33	at	at	ADP
alkej-16	66	34	the	the	DET
alkej-16	66	35	output	output	NOUN
alkej-16	66	36	n1	n1	NOUN
alkej-16	66	37	and	and	CCONJ
alkej-16	66	38	n2	n2	ADJ
alkej-16	66	39	.	.	PUNCT
alkej-16	67	1	hence	hence	ADV
alkej-16	67	2	,	,	PUNCT
alkej-16	67	3	a	a	DET
alkej-16	67	4	little	little	ADJ
alkej-16	67	5	modification	modification	NOUN
alkej-16	67	6	must	must	AUX
alkej-16	67	7	be	be	AUX
alkej-16	67	8	done	do	VERB
alkej-16	67	9	to	to	PART
alkej-16	67	10	fit	fit	VERB
alkej-16	67	11	the	the	DET
alkej-16	67	12	algorithm	algorithm	NOUN
alkej-16	67	13	to	to	ADP
alkej-16	67	14	our	our	PRON
alkej-16	67	15	case	case	NOUN
alkej-16	67	16	.	.	PUNCT
alkej-16	68	1	this	this	PRON
alkej-16	68	2	can	can	AUX
alkej-16	68	3	be	be	AUX
alkej-16	68	4	simply	simply	ADV
alkej-16	68	5	done	do	VERB
alkej-16	68	6	by	by	ADP
alkej-16	68	7	backpropagating	backpropagate	VERB
alkej-16	68	8	the	the	DET
alkej-16	68	9	error	error	NOUN
alkej-16	68	10	at	at	ADP
alkej-16	68	11	the	the	DET
alkej-16	68	12	output	output	NOUN
alkej-16	68	13	of	of	ADP
alkej-16	68	14	the	the	DET
alkej-16	68	15	narma	narma	NOUN
alkej-16	68	16	-	-	PUNCT
alkej-16	68	17	l2	l2	NOUN
alkej-16	68	18	model	model	NOUN
alkej-16	68	19	(	(	PUNCT
alkej-16	68	20	between	between	ADP
alkej-16	68	21	y	y	PROPN
alkej-16	68	22	p	p	PROPN
alkej-16	68	23	(	(	PUNCT
alkej-16	68	24	k+1	k+1	NOUN
alkej-16	68	25	)	)	PUNCT
alkej-16	68	26	and	and	CCONJ
alkej-16	68	27	y	y	PROPN
alkej-16	68	28	m	m	PROPN
alkej-16	68	29	(	(	PUNCT
alkej-16	68	30	k+1	k+1	NOUN
alkej-16	68	31	)	)	PUNCT
alkej-16	68	32	)	)	PUNCT
alkej-16	68	33	to	to	ADP
alkej-16	68	34	the	the	DET
alkej-16	68	35	output	output	NOUN
alkej-16	68	36	of	of	ADP
alkej-16	68	37	n2	n2	NOUN
alkej-16	68	38	after	after	ADP
alkej-16	68	39	multiplying	multiply	VERB
alkej-16	68	40	it	it	PRON
alkej-16	68	41	by	by	ADP
alkej-16	68	42	u(k	u(k	PROPN
alkej-16	68	43	)	)	PUNCT
alkej-16	68	44	and	and	CCONJ
alkej-16	68	45	to	to	ADP
alkej-16	68	46	the	the	DET
alkej-16	68	47	output	output	NOUN
alkej-16	68	48	of	of	ADP
alkej-16	68	49	n2	n2	NOUN
alkej-16	68	50	after	after	ADP
alkej-16	68	51	multiplying	multiply	VERB
alkej-16	68	52	it	it	PRON
alkej-16	68	53	by	by	ADP
alkej-16	68	54	u(k	u(k	PROPN
alkej-16	68	55	)	)	PUNCT
alkej-16	68	56	and	and	CCONJ
alkej-16	68	57	to	to	ADP
alkej-16	68	58	the	the	DET
alkej-16	68	59	output	output	NOUN
alkej-16	68	60	of	of	ADP
alkej-16	68	61	n1	n1	NOUN
alkej-16	68	62	directly	directly	ADV
alkej-16	68	63	.	.	PUNCT
alkej-16	69	1	the	the	DET
alkej-16	69	2	second	second	ADJ
alkej-16	69	3	step	step	NOUN
alkej-16	69	4	in	in	ADP
alkej-16	69	5	the	the	DET
alkej-16	69	6	identification	identification	NOUN
alkej-16	69	7	procedure	procedure	NOUN
alkej-16	69	8	using	use	VERB
alkej-16	69	9	the	the	DET
alkej-16	69	10	same	same	ADJ
alkej-16	69	11	feedforward	feedforward	ADJ
alkej-16	69	12	neural	neural	ADJ
alkej-16	69	13	network	network	NOUN
alkej-16	69	14	that	that	PRON
alkej-16	69	15	its	its	PRON
alkej-16	69	16	learned	learn	VERB
alkej-16	69	17	off	off	ADP
alkej-16	69	18	-	-	PUNCT
alkej-16	69	19	line	line	NOUN
alkej-16	69	20	with	with	ADP
alkej-16	69	21	serial	serial	ADJ
alkej-16	69	22	–	–	PUNCT
alkej-16	69	23	parallel	parallel	ADJ
alkej-16	69	24	model	model	NOUN
alkej-16	69	25	.	.	PUNCT
alkej-16	70	1	but	but	CCONJ
alkej-16	70	2	now	now	ADV
alkej-16	70	3	with	with	ADP
alkej-16	70	4	parallel	parallel	ADJ
alkej-16	70	5	model	model	NOUN
alkej-16	70	6	and	and	CCONJ
alkej-16	70	7	at	at	ADP
alkej-16	70	8	each	each	DET
alkej-16	70	9	instant	instant	NOUN
alkej-16	70	10	of	of	ADP
alkej-16	70	11	time	time	NOUN
alkej-16	70	12	,	,	PUNCT
alkej-16	70	13	the	the	DET
alkej-16	70	14	past	past	ADJ
alkej-16	70	15	inputs	input	NOUN
alkej-16	70	16	and	and	CCONJ
alkej-16	70	17	the	the	DET
alkej-16	70	18	past	past	ADJ
alkej-16	70	19	model	model	NOUN
alkej-16	70	20	outputs	output	NOUN
alkej-16	70	21	of	of	ADP
alkej-16	70	22	the	the	DET
alkej-16	70	23	neural	neural	ADJ
alkej-16	70	24	network	network	NOUN
alkej-16	70	25	are	be	AUX
alkej-16	70	26	fed	feed	VERB
alkej-16	70	27	into	into	ADP
alkej-16	70	28	the	the	DET
alkej-16	70	29	same	same	ADJ
alkej-16	70	30	neural	neural	ADJ
alkej-16	70	31	network	network	NOUN
alkej-16	70	32	as	as	SCONJ
alkej-16	70	33	shown	show	VERB
alkej-16	70	34	fig.2	fig.2	PROPN
alkej-16	70	35	.	.	PUNCT
alkej-16	71	1	in	in	ADP
alkej-16	71	2	order	order	NOUN
alkej-16	71	3	to	to	PART
alkej-16	71	4	minimize	minimize	VERB
alkej-16	71	5	the	the	DET
alkej-16	71	6	error	error	NOUN
alkej-16	71	7	between	between	ADP
alkej-16	71	8	the	the	DET
alkej-16	71	9	actual	actual	ADJ
alkej-16	71	10	output	output	NOUN
alkej-16	71	11	&	&	CCONJ
alkej-16	71	12	the	the	DET
alkej-16	71	13	model	model	NOUN
alkej-16	71	14	output	output	NOUN
alkej-16	71	15	and	and	CCONJ
alkej-16	71	16	is	be	AUX
alkej-16	71	17	equal	equal	ADJ
alkej-16	71	18	to	to	ADP
alkej-16	71	19	zero	zero	NUM
alkej-16	71	20	approximately	approximately	ADV
alkej-16	71	21	then	then	ADV
alkej-16	71	22	the	the	DET
alkej-16	71	23	model	model	NOUN
alkej-16	71	24	(	(	PUNCT
alkej-16	71	25	narma	narma	NOUN
alkej-16	71	26	-	-	PUNCT
alkej-16	71	27	l2	l2	NOUN
alkej-16	71	28	)	)	PUNCT
alkej-16	71	29	will	will	AUX
alkej-16	71	30	complete	complete	VERB
alkej-16	71	31	the	the	DET
alkej-16	71	32	same	same	ADJ
alkej-16	71	33	actual	actual	ADJ
alkej-16	71	34	output	output	NOUN
alkej-16	71	35	response	response	NOUN
alkej-16	71	36	.	.	PUNCT
alkej-16	72	1	when	when	SCONJ
alkej-16	72	2	identification	identification	NOUN
alkej-16	72	3	of	of	ADP
alkej-16	72	4	the	the	DET
alkej-16	72	5	plant	plant	NOUN
alkej-16	72	6	is	be	AUX
alkej-16	72	7	complete	complete	ADJ
alkej-16	72	8	then	then	ADV
alkej-16	72	9	g[-	g[-	PROPN
alkej-16	72	10	]	]	PUNCT
alkej-16	72	11	can	can	AUX
alkej-16	72	12	be	be	AUX
alkej-16	72	13	approximated	approximate	VERB
alkej-16	72	14	by	by	ADP
alkej-16	72	15	]	]	PUNCT
alkej-16	73	1	[	[	X
alkej-16	73	2	g	g	X
alkej-16	73	3	−	−	PROPN
alkej-16	73	4	∧	∧	PROPN
alkej-16	73	5	and	and	CCONJ
alkej-16	73	6	f[-	f[-	PROPN
alkej-16	73	7	]	]	PUNCT
alkej-16	73	8	by	by	ADP
alkej-16	73	9	]	]	PUNCT
alkej-16	74	1	[	[	X
alkej-16	74	2	f	f	X
alkej-16	74	3	−	−	PROPN
alkej-16	74	4	∧	∧	PROPN
alkej-16	74	5	and	and	CCONJ
alkej-16	74	6	the	the	DET
alkej-16	74	7	narma	narma	NOUN
alkej-16	74	8	-	-	PUNCT
alkej-16	74	9	l2	l2	NOUN
alkej-16	74	10	model	model	NOUN
alkej-16	74	11	of	of	ADP
alkej-16	74	12	the	the	DET
alkej-16	74	13	plant	plant	NOUN
alkej-16	74	14	can	can	AUX
alkej-16	74	15	be	be	AUX
alkej-16	74	16	described	describe	VERB
alkej-16	74	17	by	by	ADP
alkej-16	74	18	equation	equation	NOUN
alkej-16	74	19	(	(	PUNCT
alkej-16	74	20	5	5	NUM
alkej-16	74	21	)	)	PUNCT
alkej-16	74	22	below	below	ADP
alkej-16	74	23	:	:	PUNCT
alkej-16	74	24	)	)	PUNCT
alkej-16	75	1	]	]	X
alkej-16	75	2	1(),	1(),	NUM
alkej-16	75	3	...	...	PUNCT
alkej-16	75	4	,1(),1(),	,1(),1(),	PUNCT
alkej-16	75	5	...	...	PUNCT
alkej-16	75	6	,([)1	,([)1	PUNCT
alkej-16	75	7	(	(	PUNCT
alkej-16	75	8	+	+	ADV
alkej-16	75	9	−−+−=+	−−+−=+	PROPN
alkej-16	75	10	∧	∧	PROPN
alkej-16	75	11	nkukunkykyfky	nkukunkykyfky	NOUN
alkej-16	75	12	ppm	ppm	NOUN
alkej-16	75	13	)	)	PUNCT
alkej-16	75	14	(	(	PUNCT
alkej-16	75	15	)	)	PUNCT
alkej-16	76	1	]	]	X
alkej-16	76	2	1(),	1(),	NUM
alkej-16	76	3	...	...	PUNCT
alkej-16	76	4	,1(),1	,1(),1	PROPN
alkej-16	76	5	(	(	PUNCT
alkej-16	76	6	)	)	PUNCT
alkej-16	76	7	,	,	PUNCT
alkej-16	76	8	...	...	PUNCT
alkej-16	76	9	,	,	PUNCT
alkej-16	76	10	(	(	PUNCT
alkej-16	76	11	[	[	PUNCT
alkej-16	76	12	kunkukunkykyg	kunkukunkykyg	PROPN
alkej-16	76	13	pp	pp	ADV
alkej-16	76	14	×+−−+−+	×+−−+−+	PROPN
alkej-16	76	15	∧	∧	PROPN
alkej-16	76	16	…	…	PUNCT
alkej-16	76	17	(	(	PUNCT
alkej-16	76	18	5	5	NUM
alkej-16	76	19	)	)	PUNCT
alkej-16	76	20	likewise	likewise	ADV
alkej-16	76	21	if	if	SCONJ
alkej-16	76	22	]	]	X
alkej-16	76	23	[	[	X
alkej-16	76	24	g	g	X
alkej-16	76	25	−	−	PROPN
alkej-16	76	26	∧	∧	PROPN
alkej-16	76	27	is	be	AUX
alkej-16	76	28	sign	sign	VERB
alkej-16	76	29	definite	definite	ADJ
alkej-16	76	30	in	in	ADP
alkej-16	76	31	the	the	DET
alkej-16	76	32	operating	operating	NOUN
alkej-16	76	33	region	region	NOUN
alkej-16	76	34	then	then	ADV
alkej-16	76	35	the	the	DET
alkej-16	76	36	]	]	X
alkej-16	76	37	[	[	X
alkej-16	76	38	g	g	NOUN
alkej-16	76	39	−	−	PROPN
alkej-16	76	40	∧	∧	NOUN
alkej-16	76	41	network	network	NOUN
alkej-16	76	42	can	can	AUX
alkej-16	76	43	be	be	AUX
alkej-16	76	44	used	use	VERB
alkej-16	76	45	as	as	ADP
alkej-16	76	46	the	the	DET
alkej-16	76	47	jacobain	jacobain	NOUN
alkej-16	76	48	of	of	ADP
alkej-16	76	49	the	the	DET
alkej-16	76	50	plant	plant	NOUN
alkej-16	76	51	as	as	SCONJ
alkej-16	76	52	given	give	VERB
alkej-16	76	53	by	by	ADP
alkej-16	76	54	equation	equation	NOUN
alkej-16	76	55	(	(	PUNCT
alkej-16	76	56	6	6	NUM
alkej-16	76	57	)	)	PUNCT
alkej-16	76	58	.	.	PUNCT
alkej-16	76	59	)	)	PUNCT
alkej-16	77	1	]	]	X
alkej-16	77	2	1nk(u),	1nk(u),	NUM
alkej-16	77	3	...	...	PUNCT
alkej-16	77	4	,1k(u),1nk(y),	,1k(u),1nk(y),	PUNCT
alkej-16	77	5	...	...	PUNCT
alkej-16	77	6	,k(y[g	,k(y[g	PUNCT
alkej-16	77	7	pp	pp	ADP
alkej-16	77	8	+	+	ADV
alkej-16	77	9	−−+−	−−+−	X
alkej-16	77	10	∧	∧	NOUN
alkej-16	77	11	…	…	PUNCT
alkej-16	77	12	(	(	PUNCT
alkej-16	77	13	6	6	NUM
alkej-16	77	14	)	)	PUNCT
alkej-16	77	15	where	where	SCONJ
alkej-16	77	16	the	the	DET
alkej-16	77	17	jacobain	jacobain	NOUN
alkej-16	77	18	is	be	AUX
alkej-16	77	19	:	:	PUNCT
alkej-16	77	20	]	]	PUNCT
alkej-16	77	21	[	[	PUNCT
alkej-16	77	22	)	)	PUNCT
alkej-16	77	23	(	(	PUNCT
alkej-16	77	24	)	)	PUNCT
alkej-16	77	25	1	1	NUM
alkej-16	77	26	(	(	PUNCT
alkej-16	77	27	^	^	PUNCT
alkej-16	77	28	−=	−=	NOUN
alkej-16	77	29	∂	∂	NUM
alkej-16	77	30	+	+	NOUN
alkej-16	77	31	∂	∂	NOUN
alkej-16	77	32	=	=	SYM
alkej-16	77	33	g	g	PROPN
alkej-16	77	34	ku	ku	PROPN
alkej-16	77	35	ky	ky	PROPN
alkej-16	77	36	jacobain	jacobain	PROPN
alkej-16	77	37	p	p	PROPN
alkej-16	77	38	…	…	PUNCT
alkej-16	77	39	(	(	PUNCT
alkej-16	77	40	7	7	NUM
alkej-16	77	41	)	)	PUNCT
alkej-16	77	42	the	the	DET
alkej-16	77	43	sign	sign	NOUN
alkej-16	77	44	definiteness	definiteness	NOUN
alkej-16	77	45	of	of	ADP
alkej-16	77	46	]	]	PUNCT
alkej-16	77	47	[	[	X
alkej-16	77	48	g	g	X
alkej-16	77	49	−	−	PROPN
alkej-16	77	50	∧	∧	PROPN
alkej-16	77	51	in	in	ADP
alkej-16	77	52	the	the	DET
alkej-16	77	53	operating	operating	NOUN
alkej-16	77	54	region	region	NOUN
alkej-16	77	55	(	(	PUNCT
alkej-16	77	56	the	the	DET
alkej-16	77	57	region	region	NOUN
alkej-16	77	58	of	of	ADP
alkej-16	77	59	interest	interest	NOUN
alkej-16	77	60	)	)	PUNCT
alkej-16	77	61	ensures	ensure	VERB
alkej-16	77	62	the	the	DET
alkej-16	77	63	uniqueness	uniqueness	NOUN
alkej-16	77	64	of	of	ADP
alkej-16	77	65	the	the	DET
alkej-16	77	66	plant	plant	NOUN
alkej-16	77	67	inverse	inverse	NOUN
alkej-16	77	68	at	at	ADP
alkej-16	77	69	that	that	DET
alkej-16	77	70	operating	operating	NOUN
alkej-16	77	71	region	region	NOUN
alkej-16	78	1	[	[	X
alkej-16	78	2	14	14	NUM
alkej-16	78	3	]	]	PUNCT
alkej-16	78	4	.	.	PUNCT
alkej-16	79	1	now	now	ADV
alkej-16	79	2	by	by	ADP
alkej-16	79	3	using	use	VERB
alkej-16	79	4	equation	equation	NOUN
alkej-16	79	5	(	(	PUNCT
alkej-16	79	6	5	5	NUM
alkej-16	79	7	)	)	PUNCT
alkej-16	79	8	as	as	ADP
alkej-16	79	9	the	the	DET
alkej-16	79	10	model	model	NOUN
alkej-16	79	11	of	of	ADP
alkej-16	79	12	the	the	DET
alkej-16	79	13	plant	plant	NOUN
alkej-16	79	14	identifier	identifier	NOUN
alkej-16	79	15	and	and	CCONJ
alkej-16	79	16	equation	equation	NOUN
alkej-16	79	17	(	(	PUNCT
alkej-16	79	18	6	6	NUM
alkej-16	79	19	)	)	PUNCT
alkej-16	79	20	as	as	ADP
alkej-16	79	21	the	the	DET
alkej-16	79	22	jacobain	jacobain	NOUN
alkej-16	79	23	of	of	ADP
alkej-16	79	24	the	the	DET
alkej-16	79	25	plant	plant	NOUN
alkej-16	79	26	.	.	PUNCT
alkej-16	80	1	3the	3the	DET
alkej-16	80	2	controller	controller	NOUN
alkej-16	80	3	design	design	NOUN
alkej-16	80	4	:	:	PUNCT
alkej-16	80	5	the	the	DET
alkej-16	80	6	control	control	NOUN
alkej-16	80	7	of	of	ADP
alkej-16	80	8	nonlinear	nonlinear	ADJ
alkej-16	80	9	plants	plant	NOUN
alkej-16	80	10	is	be	AUX
alkej-16	80	11	considered	consider	VERB
alkej-16	80	12	in	in	ADP
alkej-16	80	13	this	this	DET
alkej-16	80	14	section	section	NOUN
alkej-16	80	15	.	.	PUNCT
alkej-16	81	1	the	the	DET
alkej-16	81	2	approach	approach	NOUN
alkej-16	81	3	used	use	VERB
alkej-16	81	4	to	to	PART
alkej-16	81	5	control	control	VERB
alkej-16	81	6	the	the	DET
alkej-16	81	7	plant	plant	NOUN
alkej-16	81	8	depends	depend	VERB
alkej-16	81	9	on	on	ADP
alkej-16	81	10	the	the	DET
alkej-16	81	11	information	information	NOUN
alkej-16	81	12	available	available	ADJ
alkej-16	81	13	about	about	ADP
alkej-16	81	14	the	the	DET
alkej-16	81	15	plant	plant	NOUN
alkej-16	81	16	and	and	CCONJ
alkej-16	81	17	the	the	DET
alkej-16	81	18	control	control	NOUN
alkej-16	81	19	objectives	objective	NOUN
alkej-16	81	20	.	.	PUNCT
alkej-16	82	1	the	the	DET
alkej-16	82	2	information	information	NOUN
alkej-16	82	3	of	of	ADP
alkej-16	82	4	the	the	DET
alkej-16	82	5	unknown	unknown	ADJ
alkej-16	82	6	nonlinear	nonlinear	ADJ
alkej-16	82	7	plant	plant	NOUN
alkej-16	82	8	can	can	AUX
alkej-16	82	9	be	be	AUX
alkej-16	82	10	known	know	VERB
alkej-16	82	11	by	by	ADP
alkej-16	82	12	the	the	DET
alkej-16	82	13	input	input	NOUN
alkej-16	82	14	-	-	PUNCT
alkej-16	82	15	output	output	NOUN
alkej-16	82	16	data	datum	NOUN
alkej-16	82	17	only	only	ADV
alkej-16	82	18	and	and	CCONJ
alkej-16	82	19	the	the	DET
alkej-16	82	20	plant	plant	NOUN
alkej-16	82	21	is	be	AUX
alkej-16	82	22	considered	consider	VERB
alkej-16	82	23	as	as	ADP
alkej-16	82	24	(	(	PUNCT
alkej-16	82	25	narma	narma	NOUN
alkej-16	82	26	-	-	PUNCT
alkej-16	82	27	l2	l2	NOUN
alkej-16	82	28	model	model	NOUN
alkej-16	82	29	)	)	PUNCT
alkej-16	82	30	.	.	PUNCT
alkej-16	83	1	the	the	DET
alkej-16	83	2	first	first	ADJ
alkej-16	83	3	step	step	NOUN
alkej-16	83	4	in	in	ADP
alkej-16	83	5	the	the	DET
alkej-16	83	6	procedure	procedure	NOUN
alkej-16	83	7	of	of	ADP
alkej-16	83	8	the	the	DET
alkej-16	83	9	control	control	NOUN
alkej-16	83	10	structure	structure	NOUN
alkej-16	83	11	is	be	AUX
alkej-16	83	12	the	the	DET
alkej-16	83	13	identification	identification	NOUN
alkej-16	83	14	of	of	ADP
alkej-16	83	15	the	the	DET
alkej-16	83	16	plant	plant	NOUN
alkej-16	83	17	from	from	ADP
alkej-16	83	18	the	the	DET
alkej-16	83	19	input	input	NOUN
alkej-16	83	20	-	-	PUNCT
alkej-16	83	21	output	output	NOUN
alkej-16	83	22	data	datum	NOUN
alkej-16	83	23	,	,	PUNCT
alkej-16	83	24	and	and	CCONJ
alkej-16	83	25	then	then	ADV
alkej-16	83	26	is	be	AUX
alkej-16	83	27	used	use	VERB
alkej-16	83	28	to	to	PART
alkej-16	83	29	ahmed	ahmed	PROPN
alkej-16	83	30	sabah	sabah	PROPN
alkej-16	83	31	abdul	abdul	PROPN
alkej-16	83	32	ameer	ameer	PROPN
alkej-16	83	33	/al	/al	PROPN
alkej-16	83	34	khwarizmi	khwarizmi	PROPN
alkej-16	83	35	engineering	engineering	PROPN
alkej-16	83	36	journal	journal	PROPN
alkej-16	83	37	,	,	PUNCT
alkej-16	83	38	vol	vol	NOUN
alkej-16	83	39	.	.	PROPN
alkej-16	84	1	1	1	NUM
alkej-16	84	2	,	,	PUNCT
alkej-16	84	3	no	no	INTJ
alkej-16	84	4	.	.	NOUN
alkej-16	84	5	1	1	NUM
alkej-16	84	6	,	,	PUNCT
alkej-16	84	7	pp	pp	ADV
alkej-16	84	8	1	1	NUM
alkej-16	84	9	-	-	SYM
alkej-16	84	10	18	18	NUM
alkej-16	84	11	(	(	PUNCT
alkej-16	84	12	2005	2005	NUM
alkej-16	84	13	)	)	PUNCT
alkej-16	84	14	٥	٥	NUM
alkej-16	84	15	find	find	VERB
alkej-16	84	16	the	the	DET
alkej-16	84	17	jacobain	jacobain	NOUN
alkej-16	84	18	of	of	ADP
alkej-16	84	19	the	the	DET
alkej-16	84	20	plant	plant	NOUN
alkej-16	84	21	as	as	ADP
alkej-16	84	22	in	in	ADP
alkej-16	84	23	section	section	NOUN
alkej-16	84	24	two	two	NUM
alkej-16	84	25	.	.	PUNCT
alkej-16	85	1	the	the	DET
alkej-16	85	2	feedback	feedback	NOUN
alkej-16	85	3	neural	neural	ADJ
alkej-16	85	4	controller	controller	NOUN
alkej-16	85	5	is	be	AUX
alkej-16	85	6	used	use	VERB
alkej-16	85	7	based	base	VERB
alkej-16	85	8	on	on	ADP
alkej-16	85	9	the	the	DET
alkej-16	85	10	minimization	minimization	NOUN
alkej-16	85	11	of	of	ADP
alkej-16	85	12	the	the	DET
alkej-16	85	13	error	error	NOUN
alkej-16	85	14	between	between	ADP
alkej-16	85	15	the	the	DET
alkej-16	85	16	desired	desire	VERB
alkej-16	85	17	“	"	PUNCT
alkej-16	85	18	set	set	VERB
alkej-16	85	19	-	-	PUNCT
alkej-16	85	20	point	point	NOUN
alkej-16	85	21	”	"	PUNCT
alkej-16	85	22	&	&	CCONJ
alkej-16	85	23	the	the	DET
alkej-16	85	24	actual	actual	ADJ
alkej-16	85	25	output	output	NOUN
alkej-16	85	26	plant	plant	NOUN
alkej-16	85	27	in	in	ADP
alkej-16	85	28	order	order	NOUN
alkej-16	85	29	to	to	PART
alkej-16	85	30	achieve	achieve	VERB
alkej-16	85	31	good	good	ADJ
alkej-16	85	32	tracking	tracking	NOUN
alkej-16	85	33	of	of	ADP
alkej-16	85	34	the	the	DET
alkej-16	85	35	reference	reference	NOUN
alkej-16	85	36	signal	signal	NOUN
alkej-16	85	37	and	and	CCONJ
alkej-16	85	38	to	to	PART
alkej-16	85	39	use	use	VERB
alkej-16	85	40	minimum	minimum	ADJ
alkej-16	85	41	effort	effort	NOUN
alkej-16	85	42	.	.	PUNCT
alkej-16	86	1	the	the	DET
alkej-16	86	2	integrated	integrate	VERB
alkej-16	86	3	control	control	NOUN
alkej-16	86	4	structure	structure	NOUN
alkej-16	86	5	that	that	PRON
alkej-16	86	6	consists	consist	VERB
alkej-16	86	7	of	of	ADP
alkej-16	86	8	the	the	DET
alkej-16	86	9	identifier	identifier	NOUN
alkej-16	86	10	of	of	ADP
alkej-16	86	11	the	the	DET
alkej-16	86	12	plant	plant	NOUN
alkej-16	86	13	and	and	CCONJ
alkej-16	86	14	a	a	DET
alkej-16	86	15	self	self	NOUN
alkej-16	86	16	-	-	PUNCT
alkej-16	86	17	tuning	tune	VERB
alkej-16	86	18	pid	pid	NOUN
alkej-16	86	19	controller	controller	NOUN
alkej-16	86	20	type	type	NOUN
alkej-16	86	21	neural	neural	ADJ
alkej-16	86	22	networks	network	NOUN
alkej-16	86	23	thus	thus	ADV
alkej-16	86	24	brings	bring	VERB
alkej-16	86	25	together	together	ADV
alkej-16	86	26	the	the	DET
alkej-16	86	27	advantages	advantage	NOUN
alkej-16	86	28	of	of	ADP
alkej-16	86	29	the	the	DET
alkej-16	86	30	neural	neural	ADJ
alkej-16	86	31	model	model	NOUN
alkej-16	86	32	with	with	ADP
alkej-16	86	33	the	the	DET
alkej-16	86	34	robustness	robustness	NOUN
alkej-16	86	35	of	of	ADP
alkej-16	86	36	feedback	feedback	NOUN
alkej-16	86	37	.	.	PUNCT
alkej-16	87	1	the	the	DET
alkej-16	87	2	general	general	ADJ
alkej-16	87	3	structure	structure	NOUN
alkej-16	87	4	of	of	ADP
alkej-16	87	5	the	the	DET
alkej-16	87	6	neural	neural	ADJ
alkej-16	87	7	controller	controller	NOUN
alkej-16	87	8	type	type	NOUN
alkej-16	87	9	can	can	AUX
alkej-16	87	10	be	be	AUX
alkej-16	87	11	given	give	VERB
alkej-16	87	12	in	in	ADP
alkej-16	87	13	the	the	DET
alkej-16	87	14	form	form	NOUN
alkej-16	87	15	of	of	ADP
alkej-16	87	16	the	the	DET
alkej-16	87	17	block	block	NOUN
alkej-16	87	18	diagram	diagram	NOUN
alkej-16	87	19	shown	show	VERB
alkej-16	87	20	in	in	ADP
alkej-16	87	21	fig	fig	NOUN
alkej-16	87	22	.	.	PUNCT
alkej-16	88	1	3.and	3.and	NUM
alkej-16	88	2	this	this	DET
alkej-16	88	3	structure	structure	NOUN
alkej-16	88	4	of	of	ADP
alkej-16	88	5	the	the	DET
alkej-16	88	6	proposed	propose	VERB
alkej-16	88	7	controller	controller	NOUN
alkej-16	88	8	can	can	AUX
alkej-16	88	9	be	be	AUX
alkej-16	88	10	applied	apply	VERB
alkej-16	88	11	to	to	ADP
alkej-16	88	12	the	the	DET
alkej-16	88	13	nonlinear	nonlinear	ADJ
alkej-16	88	14	plants.it	plants.it	PROPN
alkej-16	88	15	consists	consist	VERB
alkej-16	88	16	of	of	ADP
alkej-16	88	17	:	:	PUNCT
alkej-16	88	18	1	1	X
alkej-16	88	19	.	.	X
alkej-16	88	20	identifier	identifier	NOUN
alkej-16	88	21	as	as	ADP
alkej-16	88	22	feedforward	feedforward	NOUN
alkej-16	88	23	neural	neural	ADJ
alkej-16	88	24	networks	network	NOUN
alkej-16	88	25	(	(	PUNCT
alkej-16	88	26	narma	narma	NOUN
alkej-16	88	27	-	-	PUNCT
alkej-16	88	28	l2	l2	NOUN
alkej-16	88	29	)	)	PUNCT
alkej-16	88	30	model	model	NOUN
alkej-16	88	31	.	.	PUNCT
alkej-16	89	1	2	2	X
alkej-16	89	2	.	.	X
alkej-16	89	3	self	self	NOUN
alkej-16	89	4	-	-	PUNCT
alkej-16	89	5	tuning	tune	VERB
alkej-16	89	6	pid	pid	NOUN
alkej-16	89	7	feedback	feedback	NOUN
alkej-16	89	8	controller	controller	NOUN
alkej-16	89	9	type	type	NOUN
alkej-16	89	10	neuro	neuro	PROPN
alkej-16	89	11	controller	controller	NOUN
alkej-16	89	12	.	.	PUNCT
alkej-16	90	1	in	in	ADP
alkej-16	90	2	the	the	DET
alkej-16	90	3	following	follow	VERB
alkej-16	90	4	sections	section	NOUN
alkej-16	90	5	,	,	PUNCT
alkej-16	90	6	the	the	DET
alkej-16	90	7	proposed	propose	VERB
alkej-16	90	8	controller	controller	NOUN
alkej-16	90	9	will	will	AUX
alkej-16	90	10	be	be	AUX
alkej-16	90	11	explained	explain	VERB
alkej-16	90	12	in	in	ADP
alkej-16	90	13	detail	detail	NOUN
alkej-16	90	14	.	.	PUNCT
alkej-16	91	1	plant	plant	NOUN
alkej-16	91	2	h	h	NOUN
alkej-16	91	3	h	h	NOUN
alkej-16	92	1	l	l	PROPN
alkej-16	92	2	n1=	n1=	PUNCT
alkej-16	92	3	]	]	PUNCT
alkej-16	92	4	[	[	PUNCT
alkej-16	92	5	−	−	PROPN
alkej-16	92	6	∧	∧	PROPN
alkej-16	92	7	f	f	PROPN
alkej-16	92	8	h	h	NOUN
alkej-16	92	9	h	h	NOUN
alkej-16	92	10	l	l	PROPN
alkej-16	92	11	n2=	n2=	PROPN
alkej-16	92	12	]	]	PUNCT
alkej-16	93	1	[	[	X
alkej-16	93	2	−	−	X
alkej-16	93	3	∧	∧	PROPN
alkej-16	93	4	g	g	PROPN
alkej-16	93	5	1z−	1z−	PROPN
alkej-16	93	6	1nz	1nz	NOUN
alkej-16	93	7	+	+	ADP
alkej-16	93	8	−	−	NOUN
alkej-16	93	9	y2	y2	ADJ
alkej-16	93	10	y1	y1	NOUN
alkej-16	93	11	training	training	NOUN
alkej-16	93	12	mechanism	mechanism	NOUN
alkej-16	93	13	+	+	X
alkej-16	93	14	+	+	CCONJ
alkej-16	93	15	+	+	CCONJ
alkej-16	93	16	1nz	1nz	ADJ
alkej-16	93	17	+	+	ADJ
alkej-16	93	18	−	−	PROPN
alkej-16	93	19	1z−	1z−	PROPN
alkej-16	93	20	u(k	u(k	PROPN
alkej-16	93	21	)	)	PUNCT
alkej-16	93	22	y	y	PROPN
alkej-16	93	23	m	m	PROPN
alkej-16	93	24	(	(	PUNCT
alkej-16	93	25	k+1	k+1	X
alkej-16	93	26	)	)	PUNCT
alkej-16	93	27	y	y	PROPN
alkej-16	93	28	p	p	PROPN
alkej-16	93	29	(	(	PUNCT
alkej-16	93	30	k+1	k+1	NOUN
alkej-16	93	31	)	)	PUNCT
alkej-16	93	32	fig	fig	NOUN
alkej-16	93	33	(	(	PUNCT
alkej-16	93	34	2	2	NUM
alkej-16	93	35	):	):	PUNCT
alkej-16	93	36	narma	narma	NOUN
alkej-16	93	37	-	-	PUNCT
alkej-16	93	38	l2	l2	NOUN
alkej-16	93	39	identification	identification	NOUN
alkej-16	93	40	model	model	NOUN
alkej-16	93	41	parallel	parallel	NOUN
alkej-16	93	42	configuration	configuration	NOUN
alkej-16	93	43	×	×	NOUN
alkej-16	93	44	ahmed	ahmed	PROPN
alkej-16	93	45	sabah	sabah	PROPN
alkej-16	93	46	abdul	abdul	PROPN
alkej-16	93	47	ameer	ameer	PROPN
alkej-16	93	48	/al	/al	PROPN
alkej-16	93	49	khwarizmi	khwarizmi	PROPN
alkej-16	93	50	engineering	engineering	PROPN
alkej-16	93	51	journal	journal	PROPN
alkej-16	93	52	,	,	PUNCT
alkej-16	93	53	vol	vol	NOUN
alkej-16	93	54	.	.	PROPN
alkej-16	93	55	1	1	NUM
alkej-16	93	56	,	,	PUNCT
alkej-16	93	57	no	no	INTJ
alkej-16	93	58	.	.	NOUN
alkej-16	93	59	1	1	NUM
alkej-16	93	60	,	,	PUNCT
alkej-16	93	61	pp	pp	ADV
alkej-16	93	62	1	1	NUM
alkej-16	93	63	-	-	SYM
alkej-16	93	64	18	18	NUM
alkej-16	93	65	(	(	PUNCT
alkej-16	93	66	2005	2005	NUM
alkej-16	93	67	)	)	PUNCT
alkej-16	93	68	٦	٦	NUM
alkej-16	93	69	self	self	NOUN
alkej-16	93	70	-	-	PUNCT
alkej-16	93	71	tuning	tune	VERB
alkej-16	93	72	pid	pid	NOUN
alkej-16	93	73	type	type	NOUN
alkej-16	93	74	neurocontroller	neurocontroller	NOUN
alkej-16	93	75	:	:	PUNCT
alkej-16	93	76	the	the	DET
alkej-16	93	77	feedback	feedback	NOUN
alkej-16	93	78	neural	neural	ADJ
alkej-16	93	79	controller	controller	NOUN
alkej-16	93	80	is	be	AUX
alkej-16	93	81	very	very	ADV
alkej-16	93	82	important	important	ADJ
alkej-16	93	83	because	because	SCONJ
alkej-16	93	84	it	it	PRON
alkej-16	93	85	is	be	AUX
alkej-16	93	86	necessary	necessary	ADJ
alkej-16	93	87	to	to	PART
alkej-16	93	88	stabilize	stabilize	VERB
alkej-16	93	89	the	the	DET
alkej-16	93	90	tracking	tracking	NOUN
alkej-16	93	91	error	error	NOUN
alkej-16	93	92	dynamics	dynamic	NOUN
alkej-16	93	93	of	of	ADP
alkej-16	93	94	the	the	DET
alkej-16	93	95	system	system	NOUN
alkej-16	93	96	when	when	SCONJ
alkej-16	93	97	the	the	DET
alkej-16	93	98	output	output	NOUN
alkej-16	93	99	of	of	ADP
alkej-16	93	100	the	the	DET
alkej-16	93	101	plant	plant	NOUN
alkej-16	93	102	is	be	AUX
alkej-16	93	103	drifted	drift	VERB
alkej-16	93	104	from	from	ADP
alkej-16	93	105	the	the	DET
alkej-16	93	106	input	input	NOUN
alkej-16	93	107	reference	reference	NOUN
alkej-16	93	108	[	[	X
alkej-16	93	109	14	14	NUM
alkej-16	93	110	]	]	PUNCT
alkej-16	93	111	.	.	PUNCT
alkej-16	94	1	the	the	DET
alkej-16	94	2	adaptive	adaptive	ADJ
alkej-16	94	3	self	self	NOUN
alkej-16	94	4	-	-	PUNCT
alkej-16	94	5	tuning	tuning	NOUN
alkej-16	94	6	technique	technique	NOUN
alkej-16	94	7	is	be	AUX
alkej-16	94	8	to	to	PART
alkej-16	94	9	adjust	adjust	VERB
alkej-16	94	10	the	the	DET
alkej-16	94	11	parameters	parameter	NOUN
alkej-16	94	12	of	of	ADP
alkej-16	94	13	the	the	DET
alkej-16	94	14	pid	pid	NOUN
alkej-16	94	15	feedback	feedback	NOUN
alkej-16	94	16	controller	controller	NOUN
alkej-16	94	17	by	by	ADP
alkej-16	94	18	using	use	VERB
alkej-16	94	19	neural	neural	ADJ
alkej-16	94	20	networks	network	NOUN
alkej-16	94	21	,	,	PUNCT
alkej-16	94	22	so	so	SCONJ
alkej-16	94	23	that	that	SCONJ
alkej-16	94	24	,	,	PUNCT
alkej-16	94	25	the	the	DET
alkej-16	94	26	output	output	NOUN
alkej-16	94	27	of	of	ADP
alkej-16	94	28	the	the	DET
alkej-16	94	29	plant	plant	NOUN
alkej-16	94	30	follows	follow	VERB
alkej-16	94	31	the	the	DET
alkej-16	94	32	output	output	NOUN
alkej-16	94	33	of	of	ADP
alkej-16	94	34	the	the	DET
alkej-16	94	35	predefined	predefine	VERB
alkej-16	94	36	desired	desire	VERB
alkej-16	94	37	model	model	NOUN
alkej-16	94	38	.	.	PUNCT
alkej-16	95	1	in	in	ADP
alkej-16	95	2	the	the	DET
alkej-16	95	3	following	following	ADJ
alkej-16	95	4	section	section	NOUN
alkej-16	95	5	,	,	PUNCT
alkej-16	95	6	a	a	DET
alkej-16	95	7	self	self	NOUN
alkej-16	95	8	-	-	PUNCT
alkej-16	95	9	tuning	tune	VERB
alkej-16	95	10	neuro	neuro	NOUN
alkej-16	95	11	control	control	NOUN
alkej-16	95	12	scheme	scheme	NOUN
alkej-16	95	13	is	be	AUX
alkej-16	95	14	discussed	discuss	VERB
alkej-16	95	15	in	in	ADP
alkej-16	95	16	which	which	PRON
alkej-16	95	17	a	a	DET
alkej-16	95	18	neural	neural	ADJ
alkej-16	95	19	network	network	NOUN
alkej-16	95	20	is	be	AUX
alkej-16	95	21	used	use	VERB
alkej-16	95	22	to	to	PART
alkej-16	95	23	tune	tune	VERB
alkej-16	95	24	the	the	DET
alkej-16	95	25	parameters	parameter	NOUN
alkej-16	95	26	of	of	ADP
alkej-16	95	27	a	a	DET
alkej-16	95	28	pid	pid	NOUN
alkej-16	95	29	controller	controller	NOUN
alkej-16	95	30	referred	refer	VERB
alkej-16	95	31	to	to	ADP
alkej-16	95	32	as	as	ADP
alkej-16	95	33	the	the	DET
alkej-16	95	34	self	self	NOUN
alkej-16	95	35	-	-	PUNCT
alkej-16	95	36	tuning	tune	VERB
alkej-16	95	37	pid	pid	NOUN
alkej-16	95	38	neuro	neuro	NOUN
alkej-16	95	39	-	-	PUNCT
alkej-16	95	40	control	control	NOUN
alkej-16	95	41	scheme	scheme	NOUN
alkej-16	95	42	.	.	PUNCT
alkej-16	96	1	the	the	DET
alkej-16	96	2	pid	pid	PROPN
alkej-16	96	3	control	control	NOUN
alkej-16	96	4	configuration	configuration	NOUN
alkej-16	96	5	is	be	AUX
alkej-16	96	6	illustrated	illustrate	VERB
alkej-16	96	7	in	in	ADP
alkej-16	96	8	fig	fig	NOUN
alkej-16	96	9	.	.	PUNCT
alkej-16	97	1	4	4	NUM
alkej-16	97	2	,	,	PUNCT
alkej-16	97	3	where	where	SCONJ
alkej-16	97	4	kp	kp	PROPN
alkej-16	97	5	is	be	AUX
alkej-16	97	6	the	the	DET
alkej-16	97	7	proportional	proportional	ADJ
alkej-16	97	8	gain	gain	NOUN
alkej-16	97	9	,	,	PUNCT
alkej-16	97	10	ki	ki	PROPN
alkej-16	97	11	is	be	AUX
alkej-16	97	12	an	an	DET
alkej-16	97	13	integral	integral	ADJ
alkej-16	97	14	gain	gain	NOUN
alkej-16	97	15	,	,	PUNCT
alkej-16	97	16	&	&	CCONJ
alkej-16	97	17	kd	kd	PROPN
alkej-16	97	18	is	be	AUX
alkej-16	97	19	the	the	DET
alkej-16	97	20	derivative	derivative	ADJ
alkej-16	97	21	gain	gain	NOUN
alkej-16	97	22	,	,	PUNCT
alkej-16	97	23	which	which	PRON
alkej-16	97	24	are	be	AUX
alkej-16	97	25	adjusted	adjust	VERB
alkej-16	97	26	to	to	PART
alkej-16	97	27	achieve	achieve	VERB
alkej-16	97	28	the	the	DET
alkej-16	97	29	desired	desire	VERB
alkej-16	97	30	output.the	output.the	DET
alkej-16	97	31	control	control	NOUN
alkej-16	97	32	input	input	NOUN
alkej-16	97	33	u(k	u(k	PROPN
alkej-16	97	34	)	)	PUNCT
alkej-16	97	35	of	of	ADP
alkej-16	97	36	the	the	DET
alkej-16	97	37	pid	pid	NOUN
alkej-16	97	38	controller	controller	NOUN
alkej-16	97	39	is	be	AUX
alkej-16	97	40	given	give	VERB
alkej-16	97	41	by	by	ADP
alkej-16	97	42	equation	equation	NOUN
alkej-16	97	43	(	(	PUNCT
alkej-16	97	44	8)	8)	NUM
alkej-16	97	45	:	:	PUNCT
alkej-16	97	46	desy	desy	PROPN
alkej-16	97	47	fig	fig	NOUN
alkej-16	97	48	(	(	PUNCT
alkej-16	97	49	3	3	NUM
alkej-16	97	50	):	):	PUNCT
alkej-16	97	51	the	the	DET
alkej-16	97	52	general	general	ADJ
alkej-16	97	53	structure	structure	NOUN
alkej-16	97	54	of	of	ADP
alkej-16	97	55	the	the	DET
alkej-16	97	56	proposed	propose	VERB
alkej-16	97	57	controller	controller	NOUN
alkej-16	97	58	+	+	CCONJ
alkej-16	97	59	_	_	PUNCT
alkej-16	98	1	+	+	PUNCT
alkej-16	99	1	_	_	PUNCT
alkej-16	100	1	u	u	NOUN
alkej-16	101	1	y	y	PROPN
alkej-16	101	2	p	p	X
alkej-16	101	3	y	y	PROPN
alkej-16	101	4	m	m	PROPN
alkej-16	101	5	∆	∆	PROPN
alkej-16	101	6	me	i	PRON
alkej-16	101	7	pid	pid	NOUN
alkej-16	101	8	controller	controller	PROPN
alkej-16	101	9	nonlinear	nonlinear	PROPN
alkej-16	101	10	plant	plant	NOUN
alkej-16	101	11	neural	neural	ADJ
alkej-16	101	12	network	network	NOUN
alkej-16	101	13	∆	∆	PROPN
alkej-16	101	14	neural	neural	ADJ
alkej-16	101	15	network	network	NOUN
alkej-16	101	16	identifier	identifier	NOUN
alkej-16	101	17	∆	∆	PROPN
alkej-16	101	18	∆	∆	X
alkej-16	102	1	e	e	X
alkej-16	102	2	kp	kp	PROPN
alkej-16	102	3	ki	ki	PROPN
alkej-16	102	4	kd	kd	PROPN
alkej-16	102	5	fig	fig	PROPN
alkej-16	102	6	(	(	PUNCT
alkej-16	102	7	4	4	NUM
alkej-16	102	8	):	):	PUNCT
alkej-16	102	9	general	general	ADJ
alkej-16	102	10	configuration	configuration	NOUN
alkej-16	102	11	of	of	ADP
alkej-16	102	12	pid	pid	NOUN
alkej-16	102	13	controller	controller	NOUN
alkej-16	102	14	⊕	⊕	PROPN
alkej-16	102	15	u	u	NOUN
alkej-16	102	16	e	e	ADP
alkej-16	102	17	kp	kp	PROPN
alkej-16	102	18	s	s	PROPN
alkej-16	102	19	ki	ki	PROPN
alkej-16	102	20	kds	kds	PROPN
alkej-16	102	21	ahmed	ahmed	PROPN
alkej-16	102	22	sabah	sabah	PROPN
alkej-16	102	23	abdul	abdul	PROPN
alkej-16	102	24	ameer	ameer	PROPN
alkej-16	102	25	/al	/al	PROPN
alkej-16	102	26	khwarizmi	khwarizmi	PROPN
alkej-16	102	27	engineering	engineering	PROPN
alkej-16	102	28	journal	journal	PROPN
alkej-16	102	29	,	,	PUNCT
alkej-16	102	30	vol	vol	NOUN
alkej-16	102	31	.	.	PROPN
alkej-16	102	32	1	1	NUM
alkej-16	102	33	,	,	PUNCT
alkej-16	102	34	no	no	INTJ
alkej-16	102	35	.	.	NOUN
alkej-16	102	36	1	1	NUM
alkej-16	102	37	,	,	PUNCT
alkej-16	102	38	pp	pp	ADV
alkej-16	102	39	1	1	NUM
alkej-16	102	40	-	-	SYM
alkej-16	102	41	18	18	NUM
alkej-16	102	42	(	(	PUNCT
alkej-16	102	43	2005	2005	NUM
alkej-16	102	44	)	)	PUNCT
alkej-16	102	45	٧	٧	NUM
alkej-16	102	46	∑	∑	PROPN
alkej-16	102	47	−−++=	−−++=	NUM
alkej-16	102	48	)	)	PUNCT
alkej-16	102	49	1	1	NUM
alkej-16	102	50	(	(	PUNCT
alkej-16	102	51	)	)	PUNCT
alkej-16	102	52	(	(	PUNCT
alkej-16	102	53	(	(	PUNCT
alkej-16	102	54	)	)	PUNCT
alkej-16	102	55	(	(	PUNCT
alkej-16	102	56	)	)	PUNCT
alkej-16	102	57	(	(	PUNCT
alkej-16	102	58	)	)	PUNCT
alkej-16	102	59	(	(	PUNCT
alkej-16	102	60	kekekdkekikkpeku	kekekdkekikkpeku	PROPN
alkej-16	102	61	(	(	PUNCT
alkej-16	102	62	8)	8)	NUM
alkej-16	102	63	the	the	DET
alkej-16	102	64	proposed	propose	VERB
alkej-16	102	65	control	control	NOUN
alkej-16	102	66	structure	structure	NOUN
alkej-16	102	67	for	for	ADP
alkej-16	102	68	the	the	DET
alkej-16	102	69	self	self	NOUN
alkej-16	102	70	-	-	PUNCT
alkej-16	102	71	tuning	tune	VERB
alkej-16	102	72	pid	pid	NOUN
alkej-16	102	73	learning	learning	NOUN
alkej-16	102	74	where	where	SCONJ
alkej-16	102	75	the	the	DET
alkej-16	102	76	network	network	NOUN
alkej-16	102	77	is	be	AUX
alkej-16	102	78	used	use	VERB
alkej-16	102	79	to	to	PART
alkej-16	102	80	minimize	minimize	VERB
alkej-16	102	81	the	the	DET
alkej-16	102	82	error	error	NOUN
alkej-16	102	83	function	function	NOUN
alkej-16	102	84	by	by	ADP
alkej-16	102	85	adjusting	adjust	VERB
alkej-16	102	86	the	the	DET
alkej-16	102	87	pid	pid	NOUN
alkej-16	102	88	gain	gain	NOUN
alkej-16	102	89	.	.	PUNCT
alkej-16	103	1	the	the	DET
alkej-16	103	2	discrete	discrete	ADJ
alkej-16	103	3	-	-	PUNCT
alkej-16	103	4	time	time	NOUN
alkej-16	103	5	version	version	NOUN
alkej-16	103	6	of	of	ADP
alkej-16	103	7	pid	pid	NOUN
alkej-16	103	8	controller	controller	NOUN
alkej-16	103	9	is	be	AUX
alkej-16	103	10	described	describe	VERB
alkej-16	103	11	by	by	ADP
alkej-16	103	12	:	:	PUNCT
alkej-16	103	13	2)]-e(k1)-2e(k	2)]-e(k1)-2e(k	NUM
alkej-16	103	14	-	-	PUNCT
alkej-16	103	15	kd[e(k	kd[e(k	PROPN
alkej-16	103	16	)	)	PUNCT
alkej-16	103	17	e(k	e(k	NOUN
alkej-16	103	18	)	)	PUNCT
alkej-16	103	19	ki1)]-e(k	ki1)]-e(k	PROPN
alkej-16	103	20	-	-	PUNCT
alkej-16	103	21	kp[e(k)1)-u(ku(k	kp[e(k)1)-u(ku(k	ADJ
alkej-16	103	22	)	)	PUNCT
alkej-16	104	1	+	+	PUNCT
alkej-16	105	1	+	+	X
alkej-16	105	2	+	+	ADJ
alkej-16	105	3	+	+	NOUN
alkej-16	105	4	=	=	X
alkej-16	105	5	(	(	PUNCT
alkej-16	105	6	9	9	NUM
alkej-16	105	7	)	)	PUNCT
alkej-16	105	8	where	where	SCONJ
alkej-16	105	9	kp	kp	PROPN
alkej-16	105	10	,	,	PUNCT
alkej-16	105	11	ki	ki	PROPN
alkej-16	105	12	,	,	PUNCT
alkej-16	105	13	&	&	CCONJ
alkej-16	105	14	kd	kd	PROPN
alkej-16	105	15	denote	denote	VERB
alkej-16	105	16	the	the	DET
alkej-16	105	17	pid	pid	NOUN
alkej-16	105	18	gains	gain	NOUN
alkej-16	105	19	.	.	PUNCT
alkej-16	106	1	e(k)=	e(k)=	PROPN
alkej-16	106	2	)	)	PUNCT
alkej-16	106	3	(	(	PUNCT
alkej-16	106	4	)	)	PUNCT
alkej-16	106	5	(	(	PUNCT
alkej-16	106	6	kyky	kyky	PROPN
alkej-16	106	7	mdes	mde	VERB
alkej-16	106	8	−	−	PROPN
alkej-16	106	9	(	(	PUNCT
alkej-16	106	10	10	10	NUM
alkej-16	106	11	)	)	PUNCT
alkej-16	106	12	)	)	PUNCT
alkej-16	106	13	(	(	PUNCT
alkej-16	106	14	kydes	kyde	NOUN
alkej-16	106	15	is	be	AUX
alkej-16	106	16	a	a	DET
alkej-16	106	17	desired	desire	VERB
alkej-16	106	18	output	output	NOUN
alkej-16	106	19	.	.	PUNCT
alkej-16	106	20	)	)	PUNCT
alkej-16	107	1	(	(	PUNCT
alkej-16	107	2	kym	kym	PROPN
alkej-16	107	3	is	be	AUX
alkej-16	107	4	the	the	DET
alkej-16	107	5	model	model	NOUN
alkej-16	107	6	output	output	NOUN
alkej-16	107	7	.	.	PUNCT
alkej-16	108	1	in	in	ADP
alkej-16	108	2	order	order	NOUN
alkej-16	108	3	to	to	PART
alkej-16	108	4	derive	derive	VERB
alkej-16	108	5	the	the	DET
alkej-16	108	6	self	self	NOUN
alkej-16	108	7	-	-	PUNCT
alkej-16	108	8	tuning	tune	VERB
alkej-16	108	9	algorithm	algorithm	NOUN
alkej-16	108	10	of	of	ADP
alkej-16	108	11	the	the	DET
alkej-16	108	12	pid	pid	NOUN
alkej-16	108	13	controller	controller	NOUN
alkej-16	108	14	,	,	PUNCT
alkej-16	108	15	a	a	DET
alkej-16	108	16	cost	cost	NOUN
alkej-16	108	17	function	function	NOUN
alkej-16	108	18	e	e	NOUN
alkej-16	108	19	should	should	AUX
alkej-16	108	20	be	be	AUX
alkej-16	108	21	minimize	minimize	VERB
alkej-16	108	22	and	and	CCONJ
alkej-16	108	23	it	it	PRON
alkej-16	108	24	is	be	AUX
alkej-16	108	25	defined	define	VERB
alkej-16	108	26	as	as	ADP
alkej-16	108	27	:	:	PUNCT
alkej-16	108	28	:	:	PUNCT
alkej-16	108	29	)	)	PUNCT
alkej-16	108	30	1	1	X
alkej-16	108	31	(	(	PUNCT
alkej-16	108	32	2	2	NUM
alkej-16	108	33	1	1	NUM
alkej-16	108	34	2	2	NUM
alkej-16	108	35	+	+	NOUN
alkej-16	108	36	=	=	PROPN
alkej-16	108	37	kee	kee	X
alkej-16	108	38	(	(	PUNCT
alkej-16	108	39	11	11	NUM
alkej-16	108	40	)	)	PUNCT
alkej-16	108	41	using	use	VERB
alkej-16	108	42	two	two	NUM
alkej-16	108	43	layers	layer	NOUN
alkej-16	108	44	neural	neural	ADJ
alkej-16	108	45	network	network	NOUN
alkej-16	108	46	as	as	SCONJ
alkej-16	108	47	shown	show	VERB
alkej-16	108	48	in	in	ADP
alkej-16	108	49	fig.5	fig.5	PROPN
alkej-16	108	50	,	,	PUNCT
alkej-16	108	51	that	that	PRON
alkej-16	108	52	will	will	AUX
alkej-16	108	53	realize	realize	VERB
alkej-16	108	54	the	the	DET
alkej-16	108	55	learning	learning	NOUN
alkej-16	108	56	rule	rule	NOUN
alkej-16	108	57	to	to	PART
alkej-16	108	58	find	find	VERB
alkej-16	108	59	the	the	DET
alkej-16	108	60	suitable	suitable	ADJ
alkej-16	108	61	pid	pid	NOUN
alkej-16	108	62	gains	gain	NOUN
alkej-16	108	63	.	.	PUNCT
alkej-16	109	1	the	the	DET
alkej-16	109	2	multi	multi	ADJ
alkej-16	109	3	-	-	ADJ
alkej-16	109	4	layered	layered	ADJ
alkej-16	109	5	feedforward	feedforward	NOUN
alkej-16	109	6	neural	neural	ADJ
alkej-16	109	7	network	network	NOUN
alkej-16	109	8	shown	show	VERB
alkej-16	109	9	in	in	ADP
alkej-16	109	10	fig.5	fig.5	PROPN
alkej-16	109	11	is	be	AUX
alkej-16	109	12	composed	compose	VERB
alkej-16	109	13	of	of	ADP
alkej-16	109	14	many	many	ADJ
alkej-16	109	15	interconnected	interconnected	ADJ
alkej-16	109	16	processing	processing	NOUN
alkej-16	109	17	units	unit	NOUN
alkej-16	109	18	called	call	VERB
alkej-16	109	19	neurons	neuron	NOUN
alkej-16	109	20	or	or	CCONJ
alkej-16	109	21	nodes	node	NOUN
alkej-16	109	22	[	[	X
alkej-16	109	23	10	10	NUM
alkej-16	109	24	]	]	PUNCT
alkej-16	109	25	.	.	PUNCT
alkej-16	110	1	where	where	SCONJ
alkej-16	110	2	:	:	PUNCT
alkej-16	110	3	v	v	NOUN
alkej-16	110	4	:	:	PUNCT
alkej-16	110	5	weight	weight	NOUN
alkej-16	110	6	matrix	matrix	NOUN
alkej-16	110	7	.	.	PUNCT
alkej-16	111	1	w	w	X
alkej-16	111	2	:	:	PUNCT
alkej-16	111	3	weight	weight	NOUN
alkej-16	111	4	matrix	matrix	NOUN
alkej-16	111	5	.	.	PUNCT
alkej-16	112	1	l	l	NOUN
alkej-16	112	2	:	:	PUNCT
alkej-16	112	3	denotes	denote	NOUN
alkej-16	112	4	linear	linear	PROPN
alkej-16	112	5	node	node	PROPN
alkej-16	112	6	.	.	PUNCT
alkej-16	113	1	h	h	NOUN
alkej-16	113	2	:	:	PUNCT
alkej-16	114	1	denotes	denote	NOUN
alkej-16	114	2	nonlinear	nonlinear	VERB
alkej-16	114	3	node	node	NOUN
alkej-16	114	4	with	with	ADP
alkej-16	114	5	sigmoidal	sigmoidal	NOUN
alkej-16	114	6	function	function	NOUN
alkej-16	114	7	.	.	PUNCT
alkej-16	115	1	as	as	SCONJ
alkej-16	115	2	can	can	AUX
alkej-16	115	3	be	be	AUX
alkej-16	115	4	seen	see	VERB
alkej-16	115	5	the	the	DET
alkej-16	115	6	net	net	NOUN
alkej-16	115	7	consists	consist	VERB
alkej-16	115	8	of	of	ADP
alkej-16	115	9	three	three	NUM
alkej-16	115	10	layers	layer	NOUN
alkej-16	115	11	:	:	PUNCT
alkej-16	115	12	an	an	DET
alkej-16	115	13	input	input	NOUN
alkej-16	115	14	layer	layer	NOUN
alkej-16	115	15	(	(	PUNCT
alkej-16	115	16	buffer	buffer	VERB
alkej-16	115	17	layer	layer	NOUN
alkej-16	115	18	)	)	PUNCT
alkej-16	115	19	,	,	PUNCT
alkej-16	115	20	a	a	DET
alkej-16	115	21	single	single	ADJ
alkej-16	115	22	hidden	hidden	ADJ
alkej-16	115	23	layer	layer	NOUN
alkej-16	115	24	with	with	ADP
alkej-16	115	25	biases	bias	NOUN
alkej-16	115	26	and	and	CCONJ
alkej-16	115	27	a	a	DET
alkej-16	115	28	linear	linear	ADJ
alkej-16	115	29	output	output	NOUN
alkej-16	115	30	layer	layer	NOUN
alkej-16	115	31	with	with	ADP
alkej-16	115	32	bias	bias	NOUN
alkej-16	115	33	too	too	ADV
alkej-16	115	34	.	.	PUNCT
alkej-16	116	1	the	the	DET
alkej-16	116	2	neurons	neuron	NOUN
alkej-16	116	3	in	in	ADP
alkej-16	116	4	the	the	DET
alkej-16	116	5	input	input	NOUN
alkej-16	116	6	layer	layer	NOUN
alkej-16	116	7	simply	simply	ADV
alkej-16	116	8	store	store	VERB
alkej-16	116	9	the	the	DET
alkej-16	116	10	scaled	scale	VERB
alkej-16	116	11	input	input	NOUN
alkej-16	116	12	values	value	NOUN
alkej-16	116	13	.	.	PUNCT
alkej-16	117	1	the	the	DET
alkej-16	117	2	hidden	hide	VERB
alkej-16	117	3	layer	layer	NOUN
alkej-16	117	4	neurons	neuron	NOUN
alkej-16	117	5	perform	perform	VERB
alkej-16	117	6	two	two	NUM
alkej-16	117	7	calculations	calculation	NOUN
alkej-16	117	8	.	.	PUNCT
alkej-16	118	1	to	to	PART
alkej-16	118	2	explain	explain	VERB
alkej-16	118	3	these	these	DET
alkej-16	118	4	calculations	calculation	NOUN
alkej-16	118	5	,	,	PUNCT
alkej-16	118	6	consider	consider	VERB
alkej-16	118	7	the	the	DET
alkej-16	118	8	general	general	ADJ
alkej-16	118	9	j’th	j’th	PROPN
alkej-16	118	10	neuron	neuron	PROPN
alkej-16	118	11	in	in	ADP
alkej-16	118	12	the	the	DET
alkej-16	118	13	hidden	hide	VERB
alkej-16	118	14	layer	layer	NOUN
alkej-16	118	15	shown	show	VERB
alkej-16	118	16	in	in	ADP
alkej-16	118	17	fig.6	fig.6	PROPN
alkej-16	118	18	.	.	PUNCT
alkej-16	119	1	the	the	DET
alkej-16	119	2	inputs	input	NOUN
alkej-16	119	3	to	to	ADP
alkej-16	119	4	this	this	DET
alkej-16	119	5	neuron	neuron	NOUN
alkej-16	119	6	consist	consist	VERB
alkej-16	119	7	of	of	ADP
alkej-16	119	8	an	an	DET
alkej-16	119	9	ni	ni	PROPN
alkej-16	119	10	–	–	PUNCT
alkej-16	119	11	dimensional	dimensional	ADJ
alkej-16	119	12	vector	vector	NOUN
alkej-16	119	13	x	x	X
alkej-16	119	14	(	(	PUNCT
alkej-16	119	15	ni	ni	PROPN
alkej-16	119	16	is	be	AUX
alkej-16	119	17	the	the	DET
alkej-16	119	18	number	number	NOUN
alkej-16	119	19	of	of	ADP
alkej-16	119	20	the	the	DET
alkej-16	119	21	input	input	NOUN
alkej-16	119	22	nodes	node	NOUN
alkej-16	119	23	)	)	PUNCT
alkej-16	119	24	and	and	CCONJ
alkej-16	119	25	a	a	DET
alkej-16	119	26	bias	bias	NOUN
alkej-16	119	27	whose	whose	DET
alkej-16	119	28	value	value	NOUN
alkej-16	119	29	is	be	AUX
alkej-16	119	30	“	"	PUNCT
alkej-16	119	31	-1”[10	-1”[10	NOUN
alkej-16	119	32	]	]	PUNCT
alkej-16	119	33	.	.	PUNCT
alkej-16	120	1	each	each	PRON
alkej-16	120	2	of	of	ADP
alkej-16	120	3	the	the	DET
alkej-16	120	4	inputs	input	NOUN
alkej-16	120	5	has	have	VERB
alkej-16	120	6	a	a	DET
alkej-16	120	7	weight	weight	NOUN
alkej-16	120	8	ijv	ijv	NOUN
alkej-16	120	9	,	,	PUNCT
alkej-16	120	10	associated	associate	VERB
alkej-16	120	11	with	with	ADP
alkej-16	120	12	it	it	PRON
alkej-16	120	13	.	.	PUNCT
alkej-16	121	1	the	the	DET
alkej-16	121	2	first	first	ADJ
alkej-16	121	3	calculation	calculation	NOUN
alkej-16	121	4	within	within	ADP
alkej-16	121	5	the	the	DET
alkej-16	121	6	neuron	neuron	NOUN
alkej-16	121	7	consists	consist	VERB
alkej-16	121	8	of	of	ADP
alkej-16	121	9	calculating	calculate	VERB
alkej-16	121	10	the	the	DET
alkej-16	121	11	weighted	weighted	ADJ
alkej-16	121	12	sum	sum	NOUN
alkej-16	121	13	jnet	jnet	NOUN
alkej-16	121	14	of	of	ADP
alkej-16	121	15	the	the	DET
alkej-16	121	16	inputs	input	NOUN
alkej-16	121	17	as	as	ADP
alkej-16	121	18	:	:	PUNCT
alkej-16	121	19	∑	∑	PUNCT
alkej-16	121	20	=	=	SYM
alkej-16	122	1	+	+	CCONJ
alkej-16	122	2	×+×=	×+×=	ADP
alkej-16	122	3	ni	ni	PROPN
alkej-16	123	1	i	i	PROPN
alkej-16	123	2	nijiijj	nijiijj	PROPN
alkej-16	123	3	biasvxvnet	biasvxvnet	PROPN
alkej-16	123	4	1	1	NUM
alkej-16	123	5	1	1	NUM
alkej-16	123	6	,	,	PUNCT
alkej-16	123	7	,	,	PUNCT
alkej-16	123	8	(	(	PUNCT
alkej-16	123	9	12	12	NUM
alkej-16	123	10	)	)	PUNCT
alkej-16	123	11	next	next	ADP
alkej-16	123	12	the	the	DET
alkej-16	123	13	output	output	NOUN
alkej-16	123	14	of	of	ADP
alkej-16	123	15	the	the	DET
alkej-16	123	16	neuron	neuron	NOUN
alkej-16	123	17	jh	jh	PROPN
alkej-16	123	18	is	be	AUX
alkej-16	123	19	calculated	calculate	VERB
alkej-16	123	20	as	as	ADP
alkej-16	123	21	the	the	DET
alkej-16	123	22	continuous	continuous	ADJ
alkej-16	123	23	sigmoid	sigmoid	NOUN
alkej-16	123	24	function	function	NOUN
alkej-16	123	25	of	of	ADP
alkej-16	123	26	the	the	DET
alkej-16	123	27	jnet	jnet	NOUN
alkej-16	123	28	as	as	ADP
alkej-16	123	29	:	:	PUNCT
alkej-16	123	30	jh	jh	PROPN
alkej-16	123	31	=	=	SYM
alkej-16	123	32	h	h	PROPN
alkej-16	123	33	(	(	PUNCT
alkej-16	123	34	jnet	jnet	PROPN
alkej-16	123	35	)	)	PUNCT
alkej-16	123	36	(	(	PUNCT
alkej-16	123	37	13	13	X
alkej-16	123	38	)	)	PUNCT
alkej-16	123	39	h	h	NOUN
alkej-16	123	40	(	(	PUNCT
alkej-16	123	41	jnet	jnet	NOUN
alkej-16	123	42	)	)	PUNCT
alkej-16	123	43	=	=	SYM
alkej-16	123	44	1	1	NUM
alkej-16	123	45	1	1	NUM
alkej-16	123	46	2	2	NUM
alkej-16	123	47	−	−	NOUN
alkej-16	123	48	+	+	CCONJ
alkej-16	123	49	−	−	PROPN
alkej-16	123	50	jnete	jnete	NOUN
alkej-16	123	51	(	(	PUNCT
alkej-16	123	52	14	14	NUM
alkej-16	123	53	)	)	PUNCT
alkej-16	123	54	ahmed	ahmed	PROPN
alkej-16	123	55	sabah	sabah	PROPN
alkej-16	123	56	abdul	abdul	PROPN
alkej-16	123	57	ameer	ameer	PROPN
alkej-16	123	58	/al	/al	PROPN
alkej-16	123	59	khwarizmi	khwarizmi	PROPN
alkej-16	123	60	engineering	engineering	PROPN
alkej-16	123	61	journal	journal	PROPN
alkej-16	123	62	,	,	PUNCT
alkej-16	123	63	vol	vol	NOUN
alkej-16	123	64	.	.	PROPN
alkej-16	123	65	1	1	NUM
alkej-16	123	66	,	,	PUNCT
alkej-16	123	67	no	no	INTJ
alkej-16	123	68	.	.	NOUN
alkej-16	123	69	1	1	NUM
alkej-16	123	70	,	,	PUNCT
alkej-16	123	71	pp	pp	ADV
alkej-16	123	72	1	1	NUM
alkej-16	123	73	-	-	SYM
alkej-16	123	74	18	18	NUM
alkej-16	123	75	(	(	PUNCT
alkej-16	123	76	2005	2005	NUM
alkej-16	123	77	)	)	PUNCT
alkej-16	123	78	٨	٨	NUM
alkej-16	124	1	once	once	SCONJ
alkej-16	124	2	the	the	DET
alkej-16	124	3	outputs	output	NOUN
alkej-16	124	4	of	of	ADP
alkej-16	124	5	the	the	DET
alkej-16	124	6	hidden	hide	VERB
alkej-16	124	7	layer	layer	NOUN
alkej-16	124	8	are	be	AUX
alkej-16	124	9	calculated	calculate	VERB
alkej-16	124	10	,	,	PUNCT
alkej-16	124	11	they	they	PRON
alkej-16	124	12	are	be	AUX
alkej-16	124	13	passed	pass	VERB
alkej-16	124	14	to	to	ADP
alkej-16	124	15	the	the	DET
alkej-16	124	16	output	output	NOUN
alkej-16	124	17	layer	layer	NOUN
alkej-16	124	18	.	.	PUNCT
alkej-16	125	1	in	in	ADP
alkej-16	125	2	the	the	DET
alkej-16	125	3	output	output	NOUN
alkej-16	125	4	layer	layer	NOUN
alkej-16	125	5	,	,	PUNCT
alkej-16	125	6	a	a	DET
alkej-16	125	7	single	single	ADJ
alkej-16	125	8	linear	linear	PROPN
alkej-16	125	9	neuron	neuron	NOUN
alkej-16	125	10	is	be	AUX
alkej-16	125	11	used	use	VERB
alkej-16	125	12	to	to	PART
alkej-16	125	13	calculate	calculate	VERB
alkej-16	125	14	the	the	DET
alkej-16	125	15	weighted	weighted	ADJ
alkej-16	125	16	sum	sum	NOUN
alkej-16	125	17	(	(	PUNCT
alkej-16	125	18	neto	neto	NOUN
alkej-16	125	19	)	)	PUNCT
alkej-16	125	20	of	of	ADP
alkej-16	125	21	its	its	PRON
alkej-16	125	22	inputs	input	NOUN
alkej-16	125	23	(	(	PUNCT
alkej-16	125	24	the	the	DET
alkej-16	125	25	output	output	NOUN
alkej-16	125	26	of	of	ADP
alkej-16	125	27	the	the	DET
alkej-16	125	28	hidden	hide	VERB
alkej-16	125	29	layer	layer	NOUN
alkej-16	125	30	as	as	ADP
alkej-16	125	31	in	in	ADP
alkej-16	125	32	equation(15	equation(15	NOUN
alkej-16	125	33	)	)	PUNCT
alkej-16	125	34	.	.	PUNCT
alkej-16	126	1	neto	neto	PROPN
alkej-16	126	2	k	k	PROPN
alkej-16	127	1	=	=	X
alkej-16	127	2	biaswhw	biaswhw	PROPN
alkej-16	127	3	nhk	nhk	PROPN
alkej-16	127	4	nh	nh	PROPN
alkej-16	127	5	j	j	PROPN
alkej-16	127	6	jkj	jkj	PROPN
alkej-16	127	7	×+×	×+×	NOUN
alkej-16	127	8	+	+	CCONJ
alkej-16	128	1	=	=	SYM
alkej-16	128	2	∑	∑	PUNCT
alkej-16	128	3	1	1	NUM
alkej-16	128	4	,	,	PUNCT
alkej-16	128	5	1	1	NUM
alkej-16	128	6	(	(	PUNCT
alkej-16	128	7	15	15	NUM
alkej-16	128	8	)	)	PUNCT
alkej-16	128	9	where	where	SCONJ
alkej-16	128	10	nh	nh	PROPN
alkej-16	128	11	is	be	AUX
alkej-16	128	12	the	the	DET
alkej-16	128	13	number	number	NOUN
alkej-16	128	14	of	of	ADP
alkej-16	128	15	the	the	DET
alkej-16	128	16	hidden	hide	VERB
alkej-16	128	17	neuro	neuro	NOUN
alkej-16	128	18	(	(	PUNCT
alkej-16	128	19	nodes	node	NOUN
alkej-16	128	20	)	)	PUNCT
alkej-16	128	21	and	and	CCONJ
alkej-16	128	22	kjw	kjw	PROPN
alkej-16	128	23	is	be	AUX
alkej-16	128	24	the	the	DET
alkej-16	128	25	weight	weight	NOUN
alkej-16	128	26	between	between	ADP
alkej-16	128	27	the	the	DET
alkej-16	128	28	hidden	hide	VERB
alkej-16	128	29	neuron	neuron	NOUN
alkej-16	128	30	jh	jh	PROPN
alkej-16	128	31	and	and	CCONJ
alkej-16	128	32	the	the	DET
alkej-16	128	33	output	output	NOUN
alkej-16	128	34	neuron.the	neuron.the	DET
alkej-16	128	35	single	single	ADJ
alkej-16	128	36	linear	linear	PROPN
alkej-16	128	37	neuron	neuron	NOUN
alkej-16	128	38	,	,	PUNCT
alkej-16	128	39	then	then	ADV
alkej-16	128	40	,	,	PUNCT
alkej-16	128	41	pass	pass	VERB
alkej-16	128	42	the	the	DET
alkej-16	128	43	sum	sum	NOUN
alkej-16	128	44	(	(	PUNCT
alkej-16	128	45	neto	neto	PROPN
alkej-16	128	46	k	k	PROPN
alkej-16	128	47	)	)	PUNCT
alkej-16	128	48	through	through	ADP
alkej-16	128	49	a	a	DET
alkej-16	128	50	linear	linear	ADJ
alkej-16	128	51	function	function	NOUN
alkej-16	128	52	of	of	ADP
alkej-16	128	53	slope	slope	NOUN
alkej-16	128	54	1	1	NUM
alkej-16	128	55	(	(	PUNCT
alkej-16	128	56	another	another	DET
alkej-16	128	57	slope	slope	NOUN
alkej-16	128	58	can	can	AUX
alkej-16	128	59	be	be	AUX
alkej-16	128	60	used	use	VERB
alkej-16	128	61	to	to	PART
alkej-16	128	62	scale	scale	VERB
alkej-16	128	63	the	the	DET
alkej-16	128	64	output	output	NOUN
alkej-16	128	65	)	)	PUNCT
alkej-16	128	66	as	as	ADP
alkej-16	128	67	:	:	PUNCT
alkej-16	128	68	)	)	PUNCT
alkej-16	128	69	(	(	PUNCT
alkej-16	128	70	kk	kk	PROPN
alkej-16	128	71	netolo	netolo	PROPN
alkej-16	128	72	=	=	PROPN
alkej-16	128	73	,	,	PUNCT
alkej-16	128	74	wherel(x)=x	wherel(x)=x	X
alkej-16	128	75	(	(	PUNCT
alkej-16	128	76	16	16	NUM
alkej-16	128	77	)	)	PUNCT
alkej-16	128	78	thus	thus	ADV
alkej-16	128	79	the	the	DET
alkej-16	128	80	outputs	output	NOUN
alkej-16	128	81	at	at	ADP
alkej-16	128	82	the	the	DET
alkej-16	128	83	output	output	NOUN
alkej-16	128	84	layer	layer	NOUN
alkej-16	128	85	are	be	AUX
alkej-16	128	86	kp	kp	PROPN
alkej-16	128	87	,	,	PUNCT
alkej-16	128	88	ki	ki	PROPN
alkej-16	128	89	,	,	PUNCT
alkej-16	128	90	&	&	CCONJ
alkej-16	128	91	kd	kd	PROPN
alkej-16	128	92	which	which	PRON
alkej-16	128	93	are	be	AUX
alkej-16	128	94	denoted	denote	VERB
alkej-16	128	95	by	by	ADP
alkej-16	128	96	o1	o1	NOUN
alkej-16	128	97	,	,	PUNCT
alkej-16	128	98	o2	o2	PROPN
alkej-16	128	99	,	,	PUNCT
alkej-16	128	100	&	&	CCONJ
alkej-16	128	101	o3	o3	PROPN
alkej-16	128	102	respectively	respectively	ADV
alkej-16	128	103	.	.	PUNCT
alkej-16	129	1	based	base	VERB
alkej-16	129	2	on	on	ADP
alkej-16	129	3	the	the	DET
alkej-16	129	4	steepest	steep	ADJ
alkej-16	129	5	descent	descent	NOUN
alkej-16	129	6	(	(	PUNCT
alkej-16	129	7	gradient	gradient	NOUN
alkej-16	129	8	)	)	PUNCT
alkej-16	129	9	method	method	NOUN
alkej-16	129	10	,	,	PUNCT
alkej-16	129	11	at	at	ADP
alkej-16	129	12	the	the	DET
alkej-16	129	13	output	output	NOUN
alkej-16	129	14	layer	layer	NOUN
alkej-16	129	15	:	:	PUNCT
alkej-16	129	16	fig	fig	NOUN
alkej-16	129	17	(	(	PUNCT
alkej-16	129	18	5	5	NUM
alkej-16	129	19	):	):	PUNCT
alkej-16	129	20	neural	neural	ADJ
alkej-16	129	21	network	network	NOUN
alkej-16	129	22	is	be	AUX
alkej-16	129	23	used	use	VERB
alkej-16	129	24	to	to	PART
alkej-16	129	25	determine	determine	VERB
alkej-16	129	26	the	the	DET
alkej-16	129	27	pid	pid	NOUN
alkej-16	129	28	gains	gain	NOUN
alkej-16	129	29	h	h	NOUN
alkej-16	129	30	l	l	PROPN
alkej-16	129	31	jiv	jiv	PROPN
alkej-16	129	32	kjw	kjw	PROPN
alkej-16	129	33	h	h	PROPN
alkej-16	129	34	h	h	PROPN
alkej-16	129	35	inputs	input	VERB
alkej-16	129	36	bias=	bias=	NUM
alkej-16	129	37	-1	-1	SYM
alkej-16	129	38	bias=	bias=	NUM
alkej-16	129	39	-1	-1	SYM
alkej-16	129	40	kp	kp	PROPN
alkej-16	129	41	=	=	NOUN
alkej-16	129	42	o1	o1	NOUN
alkej-16	129	43	inputs	input	NOUN
alkej-16	129	44	layer	layer	NOUN
alkej-16	129	45	hidden	hide	VERB
alkej-16	129	46	layer	layer	NOUN
alkej-16	129	47	output	output	NOUN
alkej-16	129	48	layer	layer	NOUN
alkej-16	129	49	l	l	PROPN
alkej-16	129	50	l	l	X
alkej-16	130	1	ki	ki	PROPN
alkej-16	130	2	=	=	PROPN
alkej-16	130	3	o2	o2	PROPN
alkej-16	130	4	kd	kd	PROPN
alkej-16	130	5	=	=	PROPN
alkej-16	130	6	o3	o3	PROPN
alkej-16	130	7	∑	∑	PROPN
alkej-16	130	8	h	h	PROPN
alkej-16	130	9	1,jv	1,jv	NUM
alkej-16	130	10	2,jv	2,jv	NUM
alkej-16	130	11	nijv	nijv	NOUN
alkej-16	130	12	,	,	PUNCT
alkej-16	130	13	,	,	PUNCT
alkej-16	130	14	+	+	CCONJ
alkej-16	130	15	nijv	nijv	PROPN
alkej-16	130	16	jh	jh	PROPN
alkej-16	131	1	x1	x1	PROPN
alkej-16	131	2	x2	x2	PROPN
alkej-16	131	3	xni	xni	PROPN
alkej-16	131	4	bias	bias	NOUN
alkej-16	131	5	=	=	SYM
alkej-16	131	6	-1	-1	NOUN
alkej-16	131	7	fig	fig	NOUN
alkej-16	131	8	(	(	PUNCT
alkej-16	131	9	6	6	NUM
alkej-16	131	10	):	):	PUNCT
alkej-16	131	11	neuron	neuron	PROPN
alkej-16	131	12	j	j	PROPN
alkej-16	131	13	in	in	ADP
alkej-16	131	14	the	the	DET
alkej-16	131	15	hidden	hide	VERB
alkej-16	131	16	layer	layer	NOUN
alkej-16	131	17	.	.	PUNCT
alkej-16	132	1	ahmed	ahmed	PROPN
alkej-16	132	2	sabah	sabah	PROPN
alkej-16	132	3	abdul	abdul	PROPN
alkej-16	132	4	ameer	ameer	PROPN
alkej-16	132	5	/al	/al	PROPN
alkej-16	132	6	khwarizmi	khwarizmi	PROPN
alkej-16	132	7	engineering	engineering	PROPN
alkej-16	132	8	journal	journal	PROPN
alkej-16	132	9	,	,	PUNCT
alkej-16	132	10	vol	vol	NOUN
alkej-16	132	11	.	.	PROPN
alkej-16	132	12	1	1	NUM
alkej-16	132	13	,	,	PUNCT
alkej-16	132	14	no	no	INTJ
alkej-16	132	15	.	.	NOUN
alkej-16	132	16	1	1	NUM
alkej-16	132	17	,	,	PUNCT
alkej-16	132	18	pp	pp	ADV
alkej-16	132	19	1	1	NUM
alkej-16	132	20	-	-	SYM
alkej-16	132	21	18	18	NUM
alkej-16	132	22	(	(	PUNCT
alkej-16	132	23	2005	2005	NUM
alkej-16	132	24	)	)	PUNCT
alkej-16	132	25	٩	٩	PROPN
alkej-16	133	1	kj	kj	PROPN
alkej-16	133	2	kj	kj	PROPN
alkej-16	133	3	kj	kj	PROPN
alkej-16	133	4	w	w	PROPN
alkej-16	133	5	w	w	PROPN
alkej-16	133	6	ekw	ekw	PROPN
alkej-16	133	7	∆+	∆+	NUM
alkej-16	133	8	∂	∂	NUM
alkej-16	133	9	∂	∂	NUM
alkej-16	133	10	−=+∆	−=+∆	ADJ
alkej-16	133	11	αη)1	αη)1	PROPN
alkej-16	133	12	(	(	PUNCT
alkej-16	133	13	(	(	PUNCT
alkej-16	133	14	17	17	NUM
alkej-16	133	15	)	)	PUNCT
alkej-16	133	16	kj	kj	PROPN
alkej-16	133	17	k	k	PROPN
alkej-16	133	18	kkj	kkj	PROPN
alkej-16	133	19	w	w	PROPN
alkej-16	133	20	net	net	ADJ
alkej-16	133	21	net	net	ADJ
alkej-16	133	22	e	e	PROPN
alkej-16	133	23	w	w	PROPN
alkej-16	133	24	e	e	PROPN
alkej-16	133	25	∂	∂	NUM
alkej-16	133	26	∂	∂	NUM
alkej-16	133	27	×	×	PROPN
alkej-16	133	28	∂	∂	NOUN
alkej-16	133	29	∂	∂	NUM
alkej-16	133	30	=	=	SYM
alkej-16	133	31	∂	∂	NUM
alkej-16	133	32	∂	∂	NUM
alkej-16	133	33	(	(	PUNCT
alkej-16	133	34	18	18	NUM
alkej-16	133	35	)	)	PUNCT
alkej-16	133	36	kj	kj	PROPN
alkej-16	134	1	k	k	PROPN
alkej-16	134	2	k	k	PROPN
alkej-16	135	1	k	k	PROPN
alkej-16	135	2	kkj	kkj	PROPN
alkej-16	135	3	w	w	PROPN
alkej-16	135	4	net	net	ADJ
alkej-16	135	5	net	net	ADJ
alkej-16	135	6	o	o	NOUN
alkej-16	135	7	o	o	X
alkej-16	135	8	e	e	X
alkej-16	135	9	w	w	PROPN
alkej-16	135	10	e	e	PROPN
alkej-16	135	11	∂	∂	NUM
alkej-16	135	12	∂	∂	NUM
alkej-16	135	13	×	×	PROPN
alkej-16	135	14	∂	∂	NUM
alkej-16	135	15	∂	∂	NUM
alkej-16	135	16	×	×	PROPN
alkej-16	135	17	∂	∂	NOUN
alkej-16	135	18	∂	∂	NUM
alkej-16	135	19	=	=	SYM
alkej-16	135	20	∂	∂	NUM
alkej-16	135	21	∂	∂	NUM
alkej-16	135	22	(	(	PUNCT
alkej-16	135	23	19	19	NUM
alkej-16	135	24	)	)	PUNCT
alkej-16	136	1	kj	kj	PROPN
alkej-16	137	1	k	k	PROPN
alkej-16	137	2	k	k	PROPN
alkej-16	137	3	k	k	PROPN
alkej-16	137	4	kkj	kkj	PROPN
alkej-16	137	5	w	w	PROPN
alkej-16	137	6	net	net	ADJ
alkej-16	137	7	net	net	ADJ
alkej-16	138	1	o	o	NOUN
alkej-16	138	2	o	o	X
alkej-16	138	3	ku	ku	PROPN
alkej-16	138	4	ku	ku	PROPN
alkej-16	138	5	e	e	PROPN
alkej-16	138	6	w	w	PROPN
alkej-16	138	7	e	e	PROPN
alkej-16	138	8	∂	∂	NUM
alkej-16	138	9	∂	∂	NUM
alkej-16	138	10	×	×	PROPN
alkej-16	138	11	∂	∂	NUM
alkej-16	138	12	∂	∂	NUM
alkej-16	138	13	×	×	PROPN
alkej-16	138	14	∂	∂	NUM
alkej-16	138	15	∂	∂	NUM
alkej-16	138	16	×	×	PROPN
alkej-16	138	17	∂	∂	NOUN
alkej-16	138	18	∂	∂	NUM
alkej-16	138	19	=	=	SYM
alkej-16	138	20	∂	∂	NUM
alkej-16	138	21	∂	∂	NUM
alkej-16	138	22	)	)	PUNCT
alkej-16	138	23	(	(	PUNCT
alkej-16	138	24	)	)	PUNCT
alkej-16	138	25	(	(	PUNCT
alkej-16	138	26	(	(	PUNCT
alkej-16	138	27	20	20	NUM
alkej-16	138	28	)	)	PUNCT
alkej-16	139	1	kj	kj	PROPN
alkej-16	140	1	k	k	PROPN
alkej-16	140	2	k	k	PROPN
alkej-16	141	1	k	k	PROPN
alkej-16	141	2	k	k	PROPN
alkej-16	141	3	m	m	PROPN
alkej-16	141	4	mkj	mkj	PROPN
alkej-16	141	5	w	w	PROPN
alkej-16	141	6	net	net	PROPN
alkej-16	141	7	net	net	ADJ
alkej-16	141	8	o	o	NOUN
alkej-16	141	9	o	o	X
alkej-16	141	10	ku	ku	PROPN
alkej-16	141	11	ku	ku	PROPN
alkej-16	141	12	ky	ky	PROPN
alkej-16	141	13	ky	ky	PROPN
alkej-16	141	14	e	e	PROPN
alkej-16	141	15	w	w	PROPN
alkej-16	141	16	e	e	PROPN
alkej-16	141	17	∂	∂	NUM
alkej-16	141	18	∂	∂	NUM
alkej-16	141	19	∂	∂	NUM
alkej-16	141	20	∂	∂	NUM
alkej-16	141	21	∂	∂	NUM
alkej-16	141	22	∂	∂	NUM
alkej-16	141	23	∂	∂	NUM
alkej-16	142	1	+	+	NUM
alkej-16	142	2	∂	∂	NUM
alkej-16	142	3	+	+	NUM
alkej-16	142	4	∂	∂	NUM
alkej-16	142	5	∂	∂	NUM
alkej-16	142	6	=	=	SYM
alkej-16	142	7	∂	∂	NUM
alkej-16	142	8	∂	∂	NUM
alkej-16	142	9	)	)	PUNCT
alkej-16	142	10	(	(	PUNCT
alkej-16	142	11	)	)	PUNCT
alkej-16	142	12	(	(	PUNCT
alkej-16	142	13	)	)	PUNCT
alkej-16	142	14	1	1	NUM
alkej-16	142	15	(	(	PUNCT
alkej-16	142	16	)	)	PUNCT
alkej-16	142	17	1	1	NUM
alkej-16	143	1	(	(	PUNCT
alkej-16	143	2	(	(	PUNCT
alkej-16	143	3	21	21	NUM
alkej-16	143	4	)	)	PUNCT
alkej-16	143	5	jk	jk	PROPN
alkej-16	144	1	k	k	PROPN
alkej-16	144	2	m	m	VERB
alkej-16	144	3	mkj	mkj	NOUN
alkej-16	144	4	onetf	onetf	ADJ
alkej-16	145	1	o	o	PROPN
alkej-16	145	2	ku	ku	PROPN
alkej-16	145	3	ku	ku	PROPN
alkej-16	145	4	ky	ky	PROPN
alkej-16	145	5	ky	ky	PROPN
alkej-16	145	6	e	e	PROPN
alkej-16	145	7	w	w	PROPN
alkej-16	145	8	e	e	PROPN
alkej-16	145	9	)	)	PUNCT
alkej-16	145	10	(	(	PUNCT
alkej-16	145	11	)	)	PUNCT
alkej-16	145	12	(	(	PUNCT
alkej-16	145	13	)	)	PUNCT
alkej-16	145	14	(	(	PUNCT
alkej-16	145	15	)	)	PUNCT
alkej-16	145	16	1	1	NUM
alkej-16	145	17	(	(	PUNCT
alkej-16	145	18	)	)	PUNCT
alkej-16	145	19	1	1	NUM
alkej-16	145	20	(	(	PUNCT
alkej-16	145	21	′	′	NUM
alkej-16	145	22	∂	∂	NOUN
alkej-16	145	23	∂	∂	NUM
alkej-16	145	24	∂	∂	NUM
alkej-16	146	1	+	+	NUM
alkej-16	146	2	∂	∂	NUM
alkej-16	146	3	+	+	NUM
alkej-16	146	4	∂	∂	NUM
alkej-16	146	5	∂	∂	NUM
alkej-16	146	6	=	=	SYM
alkej-16	146	7	∂	∂	NUM
alkej-16	146	8	∂	∂	NUM
alkej-16	146	9	(	(	PUNCT
alkej-16	146	10	22	22	NUM
alkej-16	146	11	)	)	PUNCT
alkej-16	147	1	]	]	PUNCT
alkej-16	147	2	[	[	PUNCT
alkej-16	147	3	)	)	PUNCT
alkej-16	147	4	(	(	PUNCT
alkej-16	147	5	)	)	PUNCT
alkej-16	147	6	1	1	NUM
alkej-16	147	7	(	(	PUNCT
alkej-16	147	8	^	^	PUNCT
alkej-16	147	9	−=	−=	NOUN
alkej-16	147	10	∂	∂	NUM
alkej-16	147	11	+	+	NOUN
alkej-16	147	12	∂	∂	NOUN
alkej-16	147	13	=	=	SYM
alkej-16	147	14	g	g	PROPN
alkej-16	147	15	tu	tu	PROPN
alkej-16	147	16	kyjacobain	kyjacobain	PROPN
alkej-16	147	17	m	m	PROPN
alkej-16	147	18	(	(	PUNCT
alkej-16	147	19	23	23	NUM
alkej-16	147	20	)	)	PUNCT
alkej-16	147	21	jk	jk	PROPN
alkej-16	147	22	kmkj	kmkj	PROPN
alkej-16	148	1	onetf	onetf	PROPN
alkej-16	149	1	o	o	PROPN
alkej-16	149	2	kug	kug	PROPN
alkej-16	149	3	ky	ky	PROPN
alkej-16	149	4	ke	ke	PROPN
alkej-16	149	5	ke	ke	PROPN
alkej-16	149	6	e	e	PROPN
alkej-16	149	7	w	w	PROPN
alkej-16	149	8	e	e	PROPN
alkej-16	149	9	×′×	×′×	PROPN
alkej-16	149	10	∂	∂	NUM
alkej-16	149	11	∂	∂	NUM
alkej-16	150	1	×−×	×−×	X
alkej-16	150	2	+	+	PUNCT
alkej-16	150	3	∂	∂	NUM
alkej-16	150	4	+	+	NUM
alkej-16	150	5	∂	∂	NOUN
alkej-16	150	6	×	×	NOUN
alkej-16	150	7	+	+	SYM
alkej-16	150	8	∂	∂	NUM
alkej-16	150	9	∂	∂	NUM
alkej-16	150	10	=	=	SYM
alkej-16	150	11	∂	∂	NUM
alkej-16	150	12	∂	∂	NUM
alkej-16	150	13	)	)	PUNCT
alkej-16	150	14	(	(	PUNCT
alkej-16	150	15	)	)	PUNCT
alkej-16	150	16	(	(	PUNCT
alkej-16	150	17	]	]	X
alkej-16	150	18	[	[	PUNCT
alkej-16	150	19	)	)	PUNCT
alkej-16	150	20	1	1	NUM
alkej-16	150	21	(	(	PUNCT
alkej-16	150	22	)	)	PUNCT
alkej-16	150	23	1	1	NUM
alkej-16	150	24	(	(	PUNCT
alkej-16	150	25	)	)	PUNCT
alkej-16	150	26	1	1	NUM
alkej-16	150	27	(	(	PUNCT
alkej-16	150	28	^	^	PUNCT
alkej-16	150	29	(	(	PUNCT
alkej-16	150	30	24	24	NUM
alkej-16	150	31	)	)	PUNCT
alkej-16	150	32	from	from	ADP
alkej-16	150	33	equation	equation	NOUN
alkej-16	150	34	(	(	PUNCT
alkej-16	150	35	10	10	NUM
alkej-16	150	36	&	&	CCONJ
alkej-16	150	37	11	11	NUM
alkej-16	150	38	)	)	PUNCT
alkej-16	150	39	substituted	substitute	VERB
alkej-16	150	40	in	in	ADP
alkej-16	150	41	equation	equation	NOUN
alkej-16	150	42	(	(	PUNCT
alkej-16	150	43	24	24	NUM
alkej-16	151	1	)	)	PUNCT
alkej-16	151	2	jk	jk	PROPN
alkej-16	151	3	k	k	PROPN
alkej-16	151	4	^	^	PUNCT
alkej-16	152	1	kj	kj	PROPN
alkej-16	152	2	o)net(f	o)net(f	NUM
alkej-16	152	3	o	o	NOUN
alkej-16	152	4	)	)	PUNCT
alkej-16	153	1	t(u	t(u	PROPN
alkej-16	154	1	]	]	X
alkej-16	155	1	[	[	X
alkej-16	155	2	g)1t(e	g)1t(e	PROPN
alkej-16	155	3	w	w	PROPN
alkej-16	155	4	e	e	PROPN
alkej-16	155	5	×′×	×′×	PROPN
alkej-16	155	6	∂	∂	NUM
alkej-16	155	7	∂	∂	NUM
alkej-16	155	8	×−×+−=	×−×+−=	PROPN
alkej-16	155	9	∂	∂	NUM
alkej-16	155	10	∂	∂	NUM
alkej-16	155	11	(	(	PUNCT
alkej-16	155	12	25	25	NUM
alkej-16	155	13	)	)	PUNCT
alkej-16	155	14	where	where	SCONJ
alkej-16	155	15	:	:	PUNCT
alkej-16	155	16	c)net(f	c)net(f	PROPN
alkej-16	155	17	k	k	NOUN
alkej-16	156	1	=	=	NOUN
alkej-16	157	1	′	′	NOUN
alkej-16	157	2	for	for	ADP
alkej-16	157	3	linear	linear	ADJ
alkej-16	157	4	activation	activation	NOUN
alkej-16	157	5	function	function	NOUN
alkej-16	157	6	with	with	ADP
alkej-16	157	7	gain	gain	NOUN
alkej-16	157	8	is	be	AUX
alkej-16	157	9	limited	limit	VERB
alkej-16	157	10	between	between	ADP
alkej-16	157	11	(	(	PUNCT
alkej-16	157	12	0	0	NUM
alkej-16	157	13	to	to	PART
alkej-16	157	14	1	1	NUM
alkej-16	157	15	)	)	PUNCT
alkej-16	157	16	.	.	PUNCT
alkej-16	158	1			PROPN
alkej-16	158	2			PROPN
alkej-16	158	3			PROPN
alkej-16	158	4			PROPN
alkej-16	158	5			PROPN
alkej-16	158	6			ADJ
alkej-16	158	7			ADJ
alkej-16	158	8			ADJ
alkej-16	158	9			NUM
alkej-16	158	10			NOUN
alkej-16	158	11	=	=	NOUN
alkej-16	158	12	−+−−	−+−−	NOUN
alkej-16	158	13	=	=	PUNCT
alkej-16	158	14	=	=	NOUN
alkej-16	158	15	−−	−−	NOUN
alkej-16	158	16	=	=	SYM
alkej-16	158	17	∂	∂	NUM
alkej-16	158	18	∂	∂	NUM
alkej-16	158	19	3)2()1(2	3)2()1(2	NUM
alkej-16	158	20	)	)	PUNCT
alkej-16	158	21	(	(	PUNCT
alkej-16	158	22	2	2	NUM
alkej-16	158	23	)	)	PUNCT
alkej-16	158	24	(	(	PUNCT
alkej-16	158	25	1)1	1)1	NUM
alkej-16	158	26	(	(	PUNCT
alkej-16	158	27	)	)	PUNCT
alkej-16	158	28	(	(	PUNCT
alkej-16	158	29	)	)	PUNCT
alkej-16	158	30	(	(	PUNCT
alkej-16	158	31	kkekeke	kkekeke	PROPN
alkej-16	158	32	kke	kke	PROPN
alkej-16	158	33	kkeke	kkeke	PROPN
alkej-16	158	34	o	o	PROPN
alkej-16	158	35	ku	ku	PROPN
alkej-16	158	36	k	k	PROPN
alkej-16	158	37	(	(	PUNCT
alkej-16	158	38	26	26	NUM
alkej-16	158	39	)	)	PUNCT
alkej-16	158	40	then	then	ADV
alkej-16	158	41	substituted	substitute	VERB
alkej-16	158	42	equation	equation	NOUN
alkej-16	158	43	(	(	PUNCT
alkej-16	158	44	25	25	NUM
alkej-16	158	45	)	)	PUNCT
alkej-16	158	46	in	in	ADP
alkej-16	158	47	equation	equation	NOUN
alkej-16	158	48	(	(	PUNCT
alkej-16	158	49	12	12	NUM
alkej-16	158	50	)	)	PUNCT
alkej-16	158	51	kjj	kjj	NOUN
alkej-16	158	52	k	k	PROPN
alkej-16	158	53	kj	kj	PROPN
alkej-16	158	54	woc	woc	PROPN
alkej-16	158	55	o	o	PROPN
alkej-16	158	56	kugkekw	kugkekw	PROPN
alkej-16	158	57	∆+×	∆+×	PROPN
alkej-16	158	58	∂	∂	NOUN
alkej-16	158	59	∂	∂	NOUN
alkej-16	158	60	−+=+∆	−+=+∆	NOUN
alkej-16	158	61	αη	αη	X
alkej-16	158	62	)	)	PUNCT
alkej-16	158	63	(	(	PUNCT
alkej-16	158	64	]	]	X
alkej-16	158	65	[	[	X
alkej-16	158	66	)	)	PUNCT
alkej-16	158	67	1()1	1()1	NUM
alkej-16	158	68	(	(	PUNCT
alkej-16	158	69	^	^	PUNCT
alkej-16	158	70	(	(	PUNCT
alkej-16	158	71	27	27	NUM
alkej-16	158	72	)	)	PUNCT
alkej-16	158	73	at	at	ADP
alkej-16	158	74	the	the	DET
alkej-16	158	75	hidden	hide	VERB
alkej-16	158	76	layer	layer	NOUN
alkej-16	158	77	:	:	PUNCT
alkej-16	159	1	ji	ji	PROPN
alkej-16	159	2	ji	ji	PROPN
alkej-16	160	1	ji	ji	PROPN
alkej-16	160	2	v	v	X
alkej-16	160	3	v	v	X
alkej-16	160	4	ekv	ekv	PROPN
alkej-16	160	5	∆+	∆+	NUM
alkej-16	160	6	∂	∂	NUM
alkej-16	160	7	∂	∂	NUM
alkej-16	160	8	−=+∆	−=+∆	ADJ
alkej-16	160	9	αη)1	αη)1	PROPN
alkej-16	160	10	(	(	PUNCT
alkej-16	160	11	(	(	PUNCT
alkej-16	160	12	28	28	NUM
alkej-16	160	13	)	)	PUNCT
alkej-16	160	14	ji	ji	PROPN
alkej-16	160	15	j	j	PROPN
alkej-16	160	16	jji	jji	VERB
alkej-16	160	17	v	v	PRON
alkej-16	160	18	net	net	ADJ
alkej-16	160	19	net	net	ADJ
alkej-16	160	20	e	e	PROPN
alkej-16	160	21	v	v	ADP
alkej-16	160	22	e	e	PROPN
alkej-16	160	23	∂	∂	NUM
alkej-16	160	24	∂	∂	NUM
alkej-16	160	25	×	×	PROPN
alkej-16	160	26	∂	∂	NOUN
alkej-16	160	27	∂	∂	NUM
alkej-16	160	28	=	=	SYM
alkej-16	160	29	∂	∂	NUM
alkej-16	160	30	∂	∂	NUM
alkej-16	161	1	(	(	PUNCT
alkej-16	161	2	29	29	NUM
alkej-16	161	3	)	)	PUNCT
alkej-16	161	4	j	j	PROPN
alkej-16	161	5	jji	jji	NOUN
alkej-16	161	6	o	o	PROPN
alkej-16	161	7	net	net	ADJ
alkej-16	161	8	e	e	PROPN
alkej-16	161	9	v	v	ADP
alkej-16	161	10	e	e	PROPN
alkej-16	161	11	×	×	PROPN
alkej-16	161	12	∂	∂	NOUN
alkej-16	161	13	∂	∂	NUM
alkej-16	161	14	=	=	SYM
alkej-16	161	15	∂	∂	NUM
alkej-16	161	16	∂	∂	NUM
alkej-16	161	17	(	(	PUNCT
alkej-16	161	18	30	30	NUM
alkej-16	161	19	)	)	PUNCT
alkej-16	162	1	j	j	PROPN
alkej-16	163	1	j	j	PROPN
alkej-16	163	2	k	k	PROPN
alkej-16	163	3	1k	1k	PROPN
alkej-16	163	4	j	j	PROPN
alkej-16	163	5	j	j	PROPN
alkej-16	163	6	ji	ji	PROPN
alkej-16	164	1	net	net	NOUN
alkej-16	165	1	o	o	X
alkej-16	165	2	o	o	X
alkej-16	165	3	eo	eo	INTJ
alkej-16	165	4	v	v	NUM
alkej-16	165	5	e	e	PROPN
alkej-16	165	6	∂	∂	NUM
alkej-16	165	7	∂	∂	NUM
alkej-16	165	8	×	×	PROPN
alkej-16	165	9	∂	∂	NUM
alkej-16	165	10	∂	∂	NUM
alkej-16	165	11	×=	×=	PROPN
alkej-16	165	12	∂	∂	NUM
alkej-16	165	13	∂	∂	NOUN
alkej-16	165	14	∑	∑	PROPN
alkej-16	165	15	=	=	SYM
alkej-16	165	16	(	(	PUNCT
alkej-16	165	17	31	31	NUM
alkej-16	165	18	)	)	PUNCT
alkej-16	166	1	j	j	PROPN
alkej-16	167	1	j	j	PROPN
alkej-16	167	2	j	j	PROPN
alkej-16	168	1	k	k	PROPN
alkej-16	168	2	k	k	PROPN
alkej-16	169	1	1k	1k	PROPN
alkej-16	169	2	k	k	PROPN
alkej-16	169	3	j	j	PROPN
alkej-16	169	4	ji	ji	PROPN
alkej-16	169	5	net	net	ADJ
alkej-16	169	6	o	o	PROPN
alkej-16	169	7	o	o	X
alkej-16	169	8	net	net	ADJ
alkej-16	169	9	net	net	NOUN
alkej-16	169	10	eo	eo	PROPN
alkej-16	169	11	v	v	NUM
alkej-16	169	12	e	e	PROPN
alkej-16	169	13	∂	∂	NUM
alkej-16	169	14	∂	∂	NUM
alkej-16	169	15	×	×	PROPN
alkej-16	169	16	∂	∂	NUM
alkej-16	169	17	∂	∂	NUM
alkej-16	169	18	×	×	PROPN
alkej-16	169	19	∂	∂	NOUN
alkej-16	169	20	∂	∂	NUM
alkej-16	169	21	×=	×=	PROPN
alkej-16	169	22	∂	∂	NUM
alkej-16	169	23	∂	∂	NOUN
alkej-16	169	24	∑	∑	PROPN
alkej-16	169	25	=	=	SYM
alkej-16	169	26	(	(	PUNCT
alkej-16	169	27	32	32	NUM
alkej-16	169	28	)	)	PUNCT
alkej-16	169	29	)	)	PUNCT
alkej-16	169	30	net(fw	net(fw	NOUN
alkej-16	169	31	net	net	NOUN
alkej-16	169	32	eo	eo	PROPN
alkej-16	169	33	v	v	NOUN
alkej-16	169	34	e	e	NOUN
alkej-16	169	35	jkj	jkj	NOUN
alkej-16	169	36	k	k	PROPN
alkej-16	170	1	1k	1k	PROPN
alkej-16	170	2	k	k	PROPN
alkej-16	170	3	j	j	PROPN
alkej-16	170	4	ji	ji	PROPN
alkej-16	170	5	′××	′××	PROPN
alkej-16	170	6	∂	∂	NUM
alkej-16	170	7	∂	∂	NUM
alkej-16	170	8	×=	×=	PROPN
alkej-16	170	9	∂	∂	NUM
alkej-16	170	10	∂	∂	NOUN
alkej-16	170	11	∑	∑	PROPN
alkej-16	170	12	=	=	SYM
alkej-16	170	13	(	(	PUNCT
alkej-16	170	14	33	33	NUM
alkej-16	170	15	)	)	PUNCT
alkej-16	170	16	from	from	ADP
alkej-16	170	17	the	the	DET
alkej-16	170	18	derives	derive	NOUN
alkej-16	170	19	of	of	ADP
alkej-16	170	20	knet	knet	NOUN
alkej-16	170	21	e	e	PROPN
alkej-16	170	22	∂	∂	NUM
alkej-16	170	23	∂	∂	NUM
alkej-16	170	24	in	in	ADP
alkej-16	170	25	equation	equation	NOUN
alkej-16	170	26	(	(	PUNCT
alkej-16	170	27	19	19	NUM
alkej-16	170	28	)	)	PUNCT
alkej-16	170	29	,	,	PUNCT
alkej-16	170	30	we	we	PRON
alkej-16	170	31	get	get	VERB
alkej-16	170	32	:	:	PUNCT
alkej-16	171	1	k	k	PROPN
alkej-16	172	1	k	k	PROPN
alkej-16	172	2	m	m	VERB
alkej-16	172	3	k	k	NOUN
alkej-16	172	4	o	o	NOUN
alkej-16	172	5	kunetf	kunetf	NOUN
alkej-16	172	6	ku	ku	PROPN
alkej-16	172	7	kyke	kyke	PROPN
alkej-16	172	8	net	net	PROPN
alkej-16	172	9	e	e	PROPN
alkej-16	172	10	∂	∂	NUM
alkej-16	172	11	∂	∂	NUM
alkej-16	172	12	×′×	×′×	PROPN
alkej-16	172	13	∂	∂	NUM
alkej-16	173	1	+	+	NUM
alkej-16	173	2	∂	∂	NOUN
alkej-16	173	3	×+−=	×+−=	NUM
alkej-16	173	4	∂	∂	NUM
alkej-16	173	5	∂	∂	NUM
alkej-16	173	6	)	)	PUNCT
alkej-16	174	1	(	(	PUNCT
alkej-16	174	2	)	)	PUNCT
alkej-16	174	3	(	(	PUNCT
alkej-16	174	4	)	)	PUNCT
alkej-16	174	5	(	(	PUNCT
alkej-16	174	6	)	)	PUNCT
alkej-16	174	7	1()1	1()1	NUM
alkej-16	174	8	(	(	PUNCT
alkej-16	174	9	(	(	PUNCT
alkej-16	174	10	34	34	NUM
alkej-16	174	11	)	)	PUNCT
alkej-16	174	12	from	from	ADP
alkej-16	174	13	equation	equation	NOUN
alkej-16	174	14	(	(	PUNCT
alkej-16	174	15	34	34	NUM
alkej-16	174	16	)	)	PUNCT
alkej-16	174	17	substituted	substitute	VERB
alkej-16	174	18	in	in	ADP
alkej-16	174	19	equation	equation	NOUN
alkej-16	174	20	(	(	PUNCT
alkej-16	174	21	37	37	NUM
alkej-16	174	22	)	)	PUNCT
alkej-16	174	23	∑	∑	PUNCT
alkej-16	174	24	=	=	NOUN
alkej-16	174	25	′	′	NUM
alkej-16	174	26	∂	∂	NUM
alkej-16	174	27	∂′	∂′	PROPN
alkej-16	174	28	∂	∂	NUM
alkej-16	174	29	+	+	NOUN
alkej-16	174	30	∂	∂	NUM
alkej-16	174	31	+	+	ADJ
alkej-16	174	32	−=	−=	NOUN
alkej-16	174	33	∂	∂	NUM
alkej-16	174	34	∂	∂	NOUN
alkej-16	174	35	k	k	PROPN
alkej-16	175	1	k	k	PROPN
alkej-16	175	2	jkj	jkj	PROPN
alkej-16	176	1	k	k	PROPN
alkej-16	176	2	k	k	PROPN
alkej-16	176	3	m	m	VERB
alkej-16	176	4	j	j	PROPN
alkej-16	176	5	ji	ji	PROPN
alkej-16	176	6	netfw	netfw	NOUN
alkej-16	176	7	o	o	PROPN
alkej-16	176	8	kunetf	kunetf	NOUN
alkej-16	176	9	ku	ku	PROPN
alkej-16	176	10	kykeo	kykeo	PROPN
alkej-16	176	11	v	v	PROPN
alkej-16	176	12	e	e	PROPN
alkej-16	176	13	1	1	NUM
alkej-16	176	14	)	)	PUNCT
alkej-16	176	15	(	(	PUNCT
alkej-16	176	16	)	)	PUNCT
alkej-16	176	17	(	(	PUNCT
alkej-16	176	18	)	)	PUNCT
alkej-16	176	19	(	(	PUNCT
alkej-16	176	20	)	)	PUNCT
alkej-16	176	21	(	(	PUNCT
alkej-16	176	22	)	)	PUNCT
alkej-16	176	23	1()1	1()1	NUM
alkej-16	176	24	(	(	PUNCT
alkej-16	176	25	(	(	PUNCT
alkej-16	176	26	35	35	NUM
alkej-16	176	27	)	)	PUNCT
alkej-16	176	28	then	then	ADV
alkej-16	176	29	equation	equation	NOUN
alkej-16	176	30	(	(	PUNCT
alkej-16	176	31	35	35	NUM
alkej-16	176	32	)	)	PUNCT
alkej-16	176	33	substituted	substitute	VERB
alkej-16	176	34	in	in	ADP
alkej-16	176	35	equation	equation	NOUN
alkej-16	176	36	(	(	PUNCT
alkej-16	176	37	28	28	NUM
alkej-16	176	38	)	)	PUNCT
alkej-16	176	39	∑	∑	PUNCT
alkej-16	176	40	=	=	NOUN
alkej-16	176	41	′	′	NUM
alkej-16	176	42	∂	∂	NUM
alkej-16	176	43	∂	∂	NOUN
alkej-16	176	44	−+=+∆	−+=+∆	NOUN
alkej-16	177	1	k	k	PROPN
alkej-16	177	2	k	k	PROPN
alkej-16	177	3	jkj	jkj	PROPN
alkej-16	177	4	k	k	PROPN
alkej-16	177	5	jji	jji	PROPN
alkej-16	177	6	netfw	netfw	NOUN
alkej-16	178	1	o	o	X
alkej-16	178	2	kucgkeokv	kucgkeokv	NOUN
alkej-16	178	3	1	1	NUM
alkej-16	178	4	^	^	SYM
alkej-16	178	5	)	)	PUNCT
alkej-16	178	6	(	(	PUNCT
alkej-16	178	7	)	)	PUNCT
alkej-16	178	8	(	(	PUNCT
alkej-16	178	9	]	]	X
alkej-16	178	10	[	[	X
alkej-16	178	11	)	)	PUNCT
alkej-16	178	12	1()1	1()1	NUM
alkej-16	178	13	(	(	PUNCT
alkej-16	178	14	η	η	X
alkej-16	178	15	jiv∆α+	jiv∆α+	X
alkej-16	178	16	(	(	PUNCT
alkej-16	178	17	36	36	NUM
alkej-16	178	18	)	)	PUNCT
alkej-16	178	19	ahmed	ahmed	PROPN
alkej-16	178	20	sabah	sabah	PROPN
alkej-16	178	21	abdul	abdul	PROPN
alkej-16	178	22	ameer	ameer	PROPN
alkej-16	178	23	/al	/al	PROPN
alkej-16	178	24	khwarizmi	khwarizmi	PROPN
alkej-16	178	25	engineering	engineering	PROPN
alkej-16	178	26	journal	journal	PROPN
alkej-16	178	27	,	,	PUNCT
alkej-16	178	28	vol	vol	NOUN
alkej-16	178	29	.	.	PROPN
alkej-16	178	30	1	1	NUM
alkej-16	178	31	,	,	PUNCT
alkej-16	178	32	no	no	INTJ
alkej-16	178	33	.	.	NOUN
alkej-16	178	34	1	1	NUM
alkej-16	178	35	,	,	PUNCT
alkej-16	178	36	pp	pp	ADV
alkej-16	178	37	1	1	NUM
alkej-16	178	38	-	-	SYM
alkej-16	178	39	18	18	NUM
alkej-16	178	40	(	(	PUNCT
alkej-16	178	41	2005	2005	NUM
alkej-16	178	42	)	)	PUNCT
alkej-16	178	43	١٠	١٠	NUM
alkej-16	178	44	4case	4case	NUM
alkej-16	178	45	study	study	NOUN
alkej-16	178	46	:	:	PUNCT
alkej-16	178	47	in	in	ADP
alkej-16	178	48	this	this	DET
alkej-16	178	49	section	section	NOUN
alkej-16	178	50	,	,	PUNCT
alkej-16	178	51	an	an	DET
alkej-16	178	52	example	example	NOUN
alkej-16	178	53	is	be	AUX
alkej-16	178	54	taken	take	VERB
alkej-16	178	55	to	to	PART
alkej-16	178	56	clarify	clarify	VERB
alkej-16	178	57	the	the	DET
alkej-16	178	58	features	feature	NOUN
alkej-16	178	59	of	of	ADP
alkej-16	178	60	the	the	DET
alkej-16	178	61	neural	neural	ADJ
alkej-16	178	62	controller	controller	NOUN
alkej-16	178	63	explained	explain	VERB
alkej-16	178	64	in	in	ADP
alkej-16	178	65	section	section	NOUN
alkej-16	178	66	three	three	NUM
alkej-16	178	67	.	.	PUNCT
alkej-16	179	1	in	in	ADP
alkej-16	179	2	this	this	DET
alkej-16	179	3	example	example	NOUN
alkej-16	179	4	,	,	PUNCT
alkej-16	179	5	the	the	DET
alkej-16	179	6	controller	controller	NOUN
alkej-16	179	7	structure	structure	NOUN
alkej-16	179	8	is	be	AUX
alkej-16	179	9	applied	apply	VERB
alkej-16	179	10	to	to	ADP
alkej-16	179	11	the	the	DET
alkej-16	179	12	plant	plant	NOUN
alkej-16	179	13	whose	whose	DET
alkej-16	179	14	difference	difference	NOUN
alkej-16	179	15	equation	equation	NOUN
alkej-16	179	16	is	be	AUX
alkej-16	179	17	:	:	PUNCT
alkej-16	179	18	)	)	PUNCT
alkej-16	179	19	(	(	PUNCT
alkej-16	179	20	2.1))(2(8.0)1	2.1))(2(8.0)1	NUM
alkej-16	179	21	(	(	PUNCT
alkej-16	179	22	kukysinky	kukysinky	ADJ
alkej-16	179	23	pp	pp	ADP
alkej-16	179	24	+	+	NOUN
alkej-16	179	25	=	=	NOUN
alkej-16	179	26	+	+	X
alkej-16	179	27	(	(	PUNCT
alkej-16	179	28	37	37	NUM
alkej-16	179	29	)	)	PUNCT
alkej-16	179	30	this	this	DET
alkej-16	179	31	plant	plant	NOUN
alkej-16	179	32	has	have	AUX
alkej-16	179	33	been	be	AUX
alkej-16	179	34	adopted	adopt	VERB
alkej-16	179	35	from	from	ADP
alkej-16	179	36	[	[	X
alkej-16	179	37	8	8	NUM
alkej-16	179	38	&	&	CCONJ
alkej-16	179	39	14	14	NUM
alkej-16	179	40	]	]	PUNCT
alkej-16	179	41	.	.	PUNCT
alkej-16	180	1	for	for	ADP
alkej-16	180	2	the	the	DET
alkej-16	180	3	open	open	ADJ
alkej-16	180	4	loop	loop	NOUN
alkej-16	180	5	response	response	NOUN
alkej-16	180	6	of	of	ADP
alkej-16	180	7	the	the	DET
alkej-16	180	8	plant	plant	NOUN
alkej-16	180	9	)	)	PUNCT
alkej-16	180	10	k(y	k(y	PROPN
alkej-16	181	1	p	p	NOUN
alkej-16	181	2	to	to	ADP
alkej-16	181	3	the	the	DET
alkej-16	181	4	input	input	NOUN
alkej-16	181	5	signal	signal	NOUN
alkej-16	181	6	u(k	u(k	PROPN
alkej-16	181	7	)	)	PUNCT
alkej-16	181	8	is	be	AUX
alkej-16	181	9	shown	show	VERB
alkej-16	181	10	in	in	ADP
alkej-16	181	11	fig	fig	NOUN
alkej-16	181	12	7	7	NUM
alkej-16	181	13	-	-	PUNCT
alkej-16	181	14	a	a	NOUN
alkej-16	181	15	and	and	CCONJ
alkej-16	181	16	b	b	NOUN
alkej-16	181	17	respectively	respectively	ADV
alkej-16	181	18	.	.	PUNCT
alkej-16	182	1	the	the	DET
alkej-16	182	2	plant	plant	NOUN
alkej-16	182	3	response	response	NOUN
alkej-16	182	4	is	be	AUX
alkej-16	182	5	very	very	ADV
alkej-16	182	6	oscillatory	oscillatory	ADJ
alkej-16	182	7	when	when	SCONJ
alkej-16	182	8	the	the	DET
alkej-16	182	9	input	input	NOUN
alkej-16	182	10	amplitude	amplitude	NOUN
alkej-16	182	11	4.0)k(u	4.0)k(u	NOUN
alkej-16	182	12	≥	≥	PROPN
alkej-16	182	13	.	.	PUNCT
alkej-16	183	1	to	to	PART
alkej-16	183	2	use	use	VERB
alkej-16	183	3	the	the	DET
alkej-16	183	4	proposed	propose	VERB
alkej-16	183	5	controller	controller	NOUN
alkej-16	183	6	first	first	ADV
alkej-16	183	7	a	a	DET
alkej-16	183	8	neural	neural	ADJ
alkej-16	183	9	network	network	NOUN
alkej-16	183	10	is	be	AUX
alkej-16	183	11	trained	train	VERB
alkej-16	183	12	for	for	ADP
alkej-16	183	13	the	the	DET
alkej-16	183	14	identification	identification	NOUN
alkej-16	183	15	the	the	DET
alkej-16	183	16	plant	plant	NOUN
alkej-16	183	17	dynamics	dynamic	NOUN
alkej-16	183	18	.	.	PUNCT
alkej-16	184	1	there	there	PRON
alkej-16	184	2	are	be	VERB
alkej-16	184	3	two	two	NUM
alkej-16	184	4	stages	stage	NOUN
alkej-16	184	5	the	the	DET
alkej-16	184	6	first	first	ADJ
alkej-16	184	7	is	be	AUX
alkej-16	184	8	a	a	DET
alkej-16	184	9	series	series	NOUN
alkej-16	184	10	-	-	PUNCT
alkej-16	184	11	parallel	parallel	ADJ
alkej-16	184	12	configuration	configuration	NOUN
alkej-16	184	13	narmal2	narmal2	NOUN
alkej-16	184	14	model	model	NOUN
alkej-16	184	15	identification	identification	NOUN
alkej-16	184	16	structure	structure	NOUN
alkej-16	184	17	as	as	SCONJ
alkej-16	184	18	that	that	PRON
alkej-16	184	19	in	in	ADP
alkej-16	184	20	fig.1	fig.1	PROPN
alkej-16	184	21	is	be	AUX
alkej-16	184	22	used	use	VERB
alkej-16	184	23	.	.	PUNCT
alkej-16	185	1	the	the	DET
alkej-16	185	2	model	model	NOUN
alkej-16	185	3	is	be	AUX
alkej-16	185	4	described	describe	VERB
alkej-16	185	5	by	by	ADP
alkej-16	185	6	:	:	PUNCT
alkej-16	185	7	+	+	PUNCT
alkej-16	185	8	=	=	NOUN
alkej-16	185	9	+	+	NUM
alkej-16	185	10	)	)	PUNCT
alkej-16	185	11	]	]	PUNCT
alkej-16	185	12	(	(	PUNCT
alkej-16	185	13	[	[	X
alkej-16	185	14	1)1	1)1	NUM
alkej-16	185	15	(	(	PUNCT
alkej-16	185	16	kynky	kynky	ADJ
alkej-16	185	17	pm	pm	NOUN
alkej-16	185	18	)	)	PUNCT
alkej-16	185	19	(	(	PUNCT
alkej-16	185	20	)	)	PUNCT
alkej-16	185	21	]	]	PUNCT
alkej-16	185	22	(	(	PUNCT
alkej-16	185	23	[	[	X
alkej-16	185	24	2	2	NUM
alkej-16	185	25	kukyn	kukyn	NOUN
alkej-16	185	26	p	p	NOUN
alkej-16	185	27	(	(	PUNCT
alkej-16	185	28	38	38	NUM
alkej-16	185	29	)	)	PUNCT
alkej-16	185	30	-1.8	-1.8	PROPN
alkej-16	185	31	-1.4	-1.4	PROPN
alkej-16	185	32	-1	-1	PROPN
alkej-16	185	33	-0.6	-0.6	X
alkej-16	185	34	-0.2	-0.2	NOUN
alkej-16	185	35	0.2	0.2	NUM
alkej-16	185	36	0.6	0.6	NUM
alkej-16	185	37	1	1	NUM
alkej-16	185	38	1.4	1.4	NUM
alkej-16	185	39	1.8	1.8	NUM
alkej-16	185	40	0	0	NUM
alkej-16	185	41	10	10	NUM
alkej-16	185	42	20	20	NUM
alkej-16	185	43	30	30	NUM
alkej-16	185	44	40	40	NUM
alkej-16	185	45	50	50	NUM
alkej-16	185	46	60	60	NUM
alkej-16	185	47	70	70	NUM
alkej-16	185	48	80	80	NUM
alkej-16	185	49	90	90	NUM
alkej-16	185	50	100	100	NUM
alkej-16	185	51	k	k	NOUN
alkej-16	185	52	yp	yp	PROPN
alkej-16	186	1	[	[	X
alkej-16	186	2	k	k	X
alkej-16	186	3	]	]	X
alkej-16	186	4	fig	fig	NOUN
alkej-16	186	5	(	(	PUNCT
alkej-16	186	6	7	7	NUM
alkej-16	186	7	-	-	PUNCT
alkej-16	186	8	a	a	NOUN
alkej-16	186	9	):	):	PUNCT
alkej-16	186	10	the	the	DET
alkej-16	186	11	open	open	ADJ
alkej-16	186	12	loop	loop	NOUN
alkej-16	186	13	response	response	NOUN
alkej-16	186	14	-1	-1	ADP
alkej-16	186	15	-0.8	-0.8	PROPN
alkej-16	186	16	-0.6	-0.6	X
alkej-16	186	17	-0.4	-0.4	X
alkej-16	186	18	-0.2	-0.2	PROPN
alkej-16	186	19	0	0	NUM
alkej-16	186	20	0.2	0.2	NUM
alkej-16	186	21	0.4	0.4	NUM
alkej-16	186	22	0.6	0.6	NUM
alkej-16	186	23	0.8	0.8	NUM
alkej-16	186	24	1	1	NUM
alkej-16	186	25	0	0	NUM
alkej-16	186	26	10	10	NUM
alkej-16	186	27	20	20	NUM
alkej-16	186	28	30	30	NUM
alkej-16	186	29	40	40	NUM
alkej-16	186	30	50	50	NUM
alkej-16	186	31	60	60	NUM
alkej-16	186	32	70	70	NUM
alkej-16	186	33	80	80	NUM
alkej-16	186	34	90	90	NUM
alkej-16	186	35	100	100	NUM
alkej-16	186	36	k	k	NOUN
alkej-16	186	37	u	u	PROPN
alkej-16	187	1	[	[	X
alkej-16	187	2	k	k	X
alkej-16	187	3	]	]	X
alkej-16	187	4	fig	fig	NOUN
alkej-16	187	5	(	(	PUNCT
alkej-16	187	6	7	7	NUM
alkej-16	187	7	-	-	PUNCT
alkej-16	187	8	b	b	NOUN
alkej-16	187	9	):	):	PUNCT
alkej-16	187	10	the	the	DET
alkej-16	187	11	corresponding	corresponding	ADJ
alkej-16	187	12	input	input	NOUN
alkej-16	187	13	signal	signal	NOUN
alkej-16	187	14	ahmed	ahmed	PROPN
alkej-16	187	15	sabah	sabah	PROPN
alkej-16	187	16	abdul	abdul	PROPN
alkej-16	187	17	ameer	ameer	PROPN
alkej-16	187	18	/al	/al	PROPN
alkej-16	187	19	khwarizmi	khwarizmi	PROPN
alkej-16	187	20	engineering	engineering	PROPN
alkej-16	187	21	journal	journal	PROPN
alkej-16	187	22	,	,	PUNCT
alkej-16	187	23	vol	vol	NOUN
alkej-16	187	24	.	.	PROPN
alkej-16	187	25	1	1	NUM
alkej-16	187	26	,	,	PUNCT
alkej-16	187	27	no	no	INTJ
alkej-16	187	28	.	.	NOUN
alkej-16	187	29	1	1	NUM
alkej-16	187	30	,	,	PUNCT
alkej-16	187	31	pp	pp	ADV
alkej-16	187	32	1	1	NUM
alkej-16	187	33	-	-	SYM
alkej-16	187	34	18	18	NUM
alkej-16	187	35	(	(	PUNCT
alkej-16	187	36	2005	2005	NUM
alkej-16	187	37	)	)	PUNCT
alkej-16	187	38	١١	١١	NUM
alkej-16	187	39	where	where	SCONJ
alkej-16	187	40	n1[-	n1[-	ADJ
alkej-16	187	41	]	]	PUNCT
alkej-16	187	42	and	and	CCONJ
alkej-16	187	43	n2[-	n2[-	NOUN
alkej-16	187	44	]	]	PUNCT
alkej-16	187	45	are	be	AUX
alkej-16	187	46	multilayered	multilayere	VERB
alkej-16	187	47	neural	neural	ADJ
alkej-16	187	48	networks	network	NOUN
alkej-16	187	49	which	which	PRON
alkej-16	187	50	approximate	approximate	VERB
alkej-16	187	51	]	]	PUNCT
alkej-16	187	52	[	[	X
alkej-16	187	53	f	f	X
alkej-16	187	54	^	^	PUNCT
alkej-16	187	55	−	−	PROPN
alkej-16	187	56	and	and	CCONJ
alkej-16	187	57	]	]	X
alkej-16	187	58	[	[	X
alkej-16	187	59	g	g	X
alkej-16	187	60	−	−	PROPN
alkej-16	187	61	∧	∧	PROPN
alkej-16	187	62	of	of	ADP
alkej-16	187	63	equation	equation	NOUN
alkej-16	187	64	(	(	PUNCT
alkej-16	187	65	5	5	NUM
alkej-16	187	66	)	)	PUNCT
alkej-16	187	67	,	,	PUNCT
alkej-16	187	68	respectively	respectively	ADV
alkej-16	187	69	.	.	PUNCT
alkej-16	188	1	since	since	SCONJ
alkej-16	188	2	each	each	PRON
alkej-16	188	3	of	of	ADP
alkej-16	188	4	n1[-	n1[-	PROPN
alkej-16	188	5	]	]	PUNCT
alkej-16	188	6	and	and	CCONJ
alkej-16	188	7	n2[-	n2[-	NOUN
alkej-16	188	8	]	]	PUNCT
alkej-16	188	9	has	have	VERB
alkej-16	188	10	three	three	NUM
alkej-16	188	11	inputs	input	NOUN
alkej-16	188	12	)	)	PUNCT
alkej-16	188	13	(	(	PUNCT
alkej-16	188	14	kyp	kyp	PROPN
alkej-16	188	15	(	(	PUNCT
alkej-16	188	16	see	see	VERB
alkej-16	188	17	equation	equation	NOUN
alkej-16	188	18	(	(	PUNCT
alkej-16	188	19	38	38	NUM
alkej-16	188	20	)	)	PUNCT
alkej-16	188	21	)	)	PUNCT
alkej-16	188	22	,	,	PUNCT
alkej-16	188	23	the	the	DET
alkej-16	188	24	initial	initial	ADJ
alkej-16	188	25	guess	guess	NOUN
alkej-16	188	26	of	of	ADP
alkej-16	188	27	the	the	DET
alkej-16	188	28	number	number	NOUN
alkej-16	188	29	of	of	ADP
alkej-16	188	30	hidden	hide	VERB
alkej-16	188	31	nodes	node	NOUN
alkej-16	188	32	is	be	AUX
alkej-16	188	33	three	three	NUM
alkej-16	188	34	for	for	ADP
alkej-16	188	35	each	each	DET
alkej-16	188	36	network	network	NOUN
alkej-16	188	37	.	.	PUNCT
alkej-16	189	1	using	use	VERB
alkej-16	189	2	a	a	DET
alkej-16	189	3	random	random	ADJ
alkej-16	189	4	input	input	NOUN
alkej-16	189	5	sequence	sequence	NOUN
alkej-16	189	6	u(k	u(k	PROPN
alkej-16	189	7	)	)	PUNCT
alkej-16	189	8	with	with	ADP
alkej-16	189	9	1	1	NUM
alkej-16	189	10	)	)	PUNCT
alkej-16	189	11	(	(	PUNCT
alkej-16	189	12	≤ku	≤ku	VERB
alkej-16	189	13	a	a	DET
alkej-16	189	14	training	training	NOUN
alkej-16	189	15	set	set	NOUN
alkej-16	189	16	of	of	ADP
alkej-16	189	17	100	100	NUM
alkej-16	189	18	patterns	pattern	NOUN
alkej-16	189	19	input	input	NOUN
alkej-16	189	20	-	-	PUNCT
alkej-16	189	21	output	output	NOUN
alkej-16	189	22	used	use	VERB
alkej-16	189	23	with	with	ADP
alkej-16	189	24	learning	learn	VERB
alkej-16	189	25	rate	rate	NOUN
alkej-16	189	26	1η	1η	NOUN
alkej-16	189	27	for	for	ADP
alkej-16	189	28	n1	n1	PROPN
alkej-16	189	29	and	and	CCONJ
alkej-16	189	30	2η	2η	PROPN
alkej-16	189	31	for	for	ADP
alkej-16	189	32	n2	n2	NOUN
alkej-16	189	33	and	and	CCONJ
alkej-16	189	34	both	both	PRON
alkej-16	189	35	were	be	AUX
alkej-16	189	36	taken	take	VERB
alkej-16	189	37	to	to	PART
alkej-16	189	38	be	be	AUX
alkej-16	189	39	equal	equal	ADJ
alkej-16	189	40	to	to	ADP
alkej-16	189	41	0.3	0.3	NUM
alkej-16	189	42	.	.	PUNCT
alkej-16	190	1	during	during	ADP
alkej-16	190	2	the	the	DET
alkej-16	190	3	training	training	NOUN
alkej-16	190	4	phase	phase	NOUN
alkej-16	190	5	,	,	PUNCT
alkej-16	190	6	the	the	DET
alkej-16	190	7	training	training	NOUN
alkej-16	190	8	set	set	NOUN
alkej-16	190	9	has	have	AUX
alkej-16	190	10	been	be	AUX
alkej-16	190	11	presented	present	VERB
alkej-16	190	12	to	to	ADP
alkej-16	190	13	the	the	DET
alkej-16	190	14	network	network	NOUN
alkej-16	190	15	many	many	ADJ
alkej-16	190	16	times	time	NOUN
alkej-16	190	17	.	.	PUNCT
alkej-16	191	1	a	a	DET
alkej-16	191	2	training	training	NOUN
alkej-16	191	3	event	event	NOUN
alkej-16	191	4	corresponding	correspond	VERB
alkej-16	191	5	to	to	ADP
alkej-16	191	6	a	a	DET
alkej-16	191	7	single	single	ADJ
alkej-16	191	8	pass	pass	NOUN
alkej-16	191	9	over	over	ADP
alkej-16	191	10	of	of	ADP
alkej-16	191	11	the	the	DET
alkej-16	191	12	entire	entire	ADJ
alkej-16	191	13	training	training	NOUN
alkej-16	191	14	set	set	NOUN
alkej-16	191	15	is	be	AUX
alkej-16	191	16	called	call	VERB
alkej-16	191	17	a	a	DET
alkej-16	191	18	training	training	NOUN
alkej-16	191	19	epoch	epoch	NOUN
alkej-16	191	20	or	or	CCONJ
alkej-16	191	21	training	training	NOUN
alkej-16	191	22	cycle	cycle	NOUN
alkej-16	191	23	.	.	PUNCT
alkej-16	192	1	however	however	ADV
alkej-16	192	2	,	,	PUNCT
alkej-16	192	3	for	for	ADP
alkej-16	192	4	this	this	DET
alkej-16	192	5	example	example	NOUN
alkej-16	192	6	after	after	ADP
alkej-16	192	7	2000	2000	NUM
alkej-16	192	8	epochs	epoch	VERB
alkej-16	192	9	the	the	DET
alkej-16	192	10	average	average	ADJ
alkej-16	192	11	system	system	NOUN
alkej-16	192	12	error	error	NOUN
alkej-16	192	13	(	(	PUNCT
alkej-16	192	14	ase	ase	NOUN
alkej-16	192	15	)	)	PUNCT
alkej-16	192	16	computed	compute	VERB
alkej-16	192	17	for	for	ADP
alkej-16	192	18	the	the	DET
alkej-16	192	19	latest	late	ADJ
alkej-16	192	20	epoch	epoch	NOUN
alkej-16	192	21	,	,	PUNCT
alkej-16	192	22	which	which	PRON
alkej-16	192	23	is	be	AUX
alkej-16	192	24	described	describe	VERB
alkej-16	192	25	by	by	ADP
alkej-16	192	26	equation	equation	NOUN
alkej-16	192	27	(	(	PUNCT
alkej-16	192	28	39	39	NUM
alkej-16	192	29	)	)	PUNCT
alkej-16	192	30	was	be	AUX
alkej-16	192	31	61077.2	61077.2	NUM
alkej-16	192	32	−×	−×	NOUN
alkej-16	192	33	.	.	PUNCT
alkej-16	193	1	(	(	PUNCT
alkej-16	193	2	)	)	PUNCT
alkej-16	193	3	∑	∑	PUNCT
alkej-16	193	4	=	=	SYM
alkej-16	194	1	+	+	NOUN
alkej-16	194	2	−+=	−+=	X
alkej-16	194	3	np	np	ADP
alkej-16	194	4	i	i	PRON
alkej-16	194	5	i	i	PRON
alkej-16	194	6	m	m	VERB
alkej-16	194	7	i	i	PRON
alkej-16	194	8	p	p	NOUN
alkej-16	194	9	kyky	kyky	PROPN
alkej-16	194	10	np	np	INTJ
alkej-16	194	11	ase	ase	PROPN
alkej-16	194	12	1	1	NUM
alkej-16	194	13	2	2	NUM
alkej-16	194	14	)	)	PUNCT
alkej-16	194	15	1()1	1()1	NUM
alkej-16	194	16	(	(	PUNCT
alkej-16	194	17	2	2	NUM
alkej-16	194	18	1	1	NUM
alkej-16	194	19	(	(	PUNCT
alkej-16	194	20	39	39	NUM
alkej-16	194	21	)	)	PUNCT
alkej-16	194	22	where	where	SCONJ
alkej-16	194	23	np	np	INTJ
alkej-16	194	24	total	total	ADJ
alkej-16	194	25	number	number	NOUN
alkej-16	194	26	of	of	ADP
alkej-16	194	27	patterns	pattern	NOUN
alkej-16	194	28	which	which	PRON
alkej-16	194	29	is	be	AUX
alkej-16	194	30	equal	equal	ADJ
alkej-16	194	31	to	to	ADP
alkej-16	194	32	100	100	NUM
alkej-16	194	33	here	here	ADV
alkej-16	194	34	.	.	PUNCT
alkej-16	195	1	fig.8	fig.8	PROPN
alkej-16	195	2	-	-	PUNCT
alkej-16	195	3	a	a	PRON
alkej-16	195	4	compares	compare	VERB
alkej-16	195	5	the	the	DET
alkej-16	195	6	time	time	NOUN
alkej-16	195	7	response	response	NOUN
alkej-16	195	8	of	of	ADP
alkej-16	195	9	the	the	DET
alkej-16	195	10	series	series	NOUN
alkej-16	195	11	-	-	PUNCT
alkej-16	195	12	parallel	parallel	ADJ
alkej-16	195	13	model	model	NOUN
alkej-16	195	14	of	of	ADP
alkej-16	195	15	equation	equation	NOUN
alkej-16	195	16	(	(	PUNCT
alkej-16	195	17	38	38	NUM
alkej-16	195	18	)	)	PUNCT
alkej-16	195	19	with	with	ADP
alkej-16	195	20	the	the	DET
alkej-16	195	21	actual	actual	ADJ
alkej-16	195	22	plant	plant	NOUN
alkej-16	195	23	output	output	NOUN
alkej-16	195	24	for	for	ADP
alkej-16	195	25	the	the	DET
alkej-16	195	26	input	input	NOUN
alkej-16	195	27	as	as	ADP
alkej-16	195	28	a	a	DET
alkej-16	195	29	learning	learning	NOUN
alkej-16	195	30	set	set	NOUN
alkej-16	195	31	.	.	PUNCT
alkej-16	196	1	while	while	SCONJ
alkej-16	196	2	fig.8	fig.8	PROPN
alkej-16	196	3	-	-	PUNCT
alkej-16	196	4	b	b	NOUN
alkej-16	196	5	compares	compare	VERB
alkej-16	196	6	the	the	DET
alkej-16	196	7	time	time	NOUN
alkej-16	196	8	response	response	NOUN
alkej-16	196	9	of	of	ADP
alkej-16	196	10	the	the	DET
alkej-16	196	11	series	series	NOUN
alkej-16	196	12	-	-	PUNCT
alkej-16	196	13	parallel	parallel	ADJ
alkej-16	196	14	model	model	NOUN
alkej-16	196	15	of	of	ADP
alkej-16	196	16	equation	equation	NOUN
alkej-16	196	17	(	(	PUNCT
alkej-16	196	18	38	38	NUM
alkej-16	196	19	)	)	PUNCT
alkej-16	196	20	with	with	ADP
alkej-16	196	21	the	the	DET
alkej-16	196	22	actual	actual	ADJ
alkej-16	196	23	plant	plant	NOUN
alkej-16	196	24	output	output	NOUN
alkej-16	196	25	for	for	ADP
alkej-16	196	26	the	the	DET
alkej-16	196	27	input	input	NOUN
alkej-16	196	28	applied	apply	VERB
alkej-16	196	29	as	as	ADP
alkej-16	196	30	testing	testing	NOUN
alkej-16	196	31	set	set	VERB
alkej-16	196	32	generated	generate	VERB
alkej-16	196	33	from	from	ADP
alkej-16	196	34	equation	equation	NOUN
alkej-16	196	35	(	(	PUNCT
alkej-16	196	36	40	40	NUM
alkej-16	196	37	)	)	PUNCT
alkej-16	196	38	.	.	PUNCT
alkej-16	196	39	)	)	PUNCT
alkej-16	197	1	20	20	NUM
alkej-16	197	2	2sin(5.0	2sin(5.0	NUM
alkej-16	197	3	)	)	PUNCT
alkej-16	197	4	10	10	NUM
alkej-16	197	5	2sin(5.0	2sin(5.0	NUM
alkej-16	197	6	)	)	PUNCT
alkej-16	197	7	(	(	PUNCT
alkej-16	197	8	kkku	kkku	NOUN
alkej-16	197	9	ππ	ππ	ADP
alkej-16	197	10	×+×=	×+×=	PROPN
alkej-16	197	11	(	(	PUNCT
alkej-16	197	12	40	40	NUM
alkej-16	197	13	)	)	PUNCT
alkej-16	197	14	the	the	DET
alkej-16	197	15	second	second	ADJ
alkej-16	197	16	stage	stage	NOUN
alkej-16	197	17	is	be	AUX
alkej-16	197	18	a	a	DET
alkej-16	197	19	parallel	parallel	ADJ
alkej-16	197	20	configuration	configuration	NOUN
alkej-16	197	21	narma	narma	NOUN
alkej-16	197	22	-	-	PUNCT
alkej-16	197	23	l2	l2	NOUN
alkej-16	197	24	model	model	NOUN
alkej-16	197	25	identification	identification	NOUN
alkej-16	197	26	structure	structure	NOUN
alkej-16	197	27	as	as	SCONJ
alkej-16	197	28	that	that	PRON
alkej-16	197	29	in	in	ADP
alkej-16	197	30	fig	fig	NOUN
alkej-16	197	31	2	2	NUM
alkej-16	197	32	is	be	AUX
alkej-16	197	33	used	use	VERB
alkej-16	197	34	.	.	PUNCT
alkej-16	198	1	to	to	PART
alkej-16	198	2	guarantee	guarantee	VERB
alkej-16	198	3	the	the	DET
alkej-16	198	4	model	model	NOUN
alkej-16	198	5	output	output	NOUN
alkej-16	198	6	is	be	AUX
alkej-16	198	7	equal	equal	ADJ
alkej-16	198	8	to	to	ADP
alkej-16	198	9	the	the	DET
alkej-16	198	10	actual	actual	ADJ
alkej-16	198	11	output	output	NOUN
alkej-16	198	12	and	and	CCONJ
alkej-16	198	13	also	also	ADV
alkej-16	198	14	to	to	PART
alkej-16	198	15	find	find	VERB
alkej-16	198	16	the	the	DET
alkej-16	198	17	jacobain	jacobain	NOUN
alkej-16	198	18	of	of	ADP
alkej-16	198	19	the	the	DET
alkej-16	198	20	plant	plant	NOUN
alkej-16	198	21	.	.	PUNCT
alkej-16	199	1	+	+	PUNCT
alkej-16	199	2	=	=	NOUN
alkej-16	199	3	+	+	NUM
alkej-16	199	4	)	)	PUNCT
alkej-16	199	5	]	]	PUNCT
alkej-16	199	6	(	(	PUNCT
alkej-16	199	7	[	[	X
alkej-16	199	8	1)1	1)1	NUM
alkej-16	199	9	(	(	PUNCT
alkej-16	199	10	kynky	kynky	ADJ
alkej-16	199	11	mm	mm	PROPN
alkej-16	199	12	)	)	PUNCT
alkej-16	199	13	(	(	PUNCT
alkej-16	199	14	)	)	PUNCT
alkej-16	199	15	]	]	PUNCT
alkej-16	199	16	(	(	PUNCT
alkej-16	199	17	[	[	X
alkej-16	199	18	2	2	NUM
alkej-16	199	19	kukyn	kukyn	NOUN
alkej-16	199	20	m	m	PROPN
alkej-16	199	21	(	(	PUNCT
alkej-16	199	22	41	41	NUM
alkej-16	199	23	)	)	PUNCT
alkej-16	199	24	where	where	SCONJ
alkej-16	199	25	n1[-	n1[-	ADJ
alkej-16	199	26	]	]	PUNCT
alkej-16	199	27	and	and	CCONJ
alkej-16	199	28	n2[-	n2[-	NOUN
alkej-16	199	29	]	]	PUNCT
alkej-16	199	30	are	be	AUX
alkej-16	199	31	multilayered	multilayere	VERB
alkej-16	199	32	neural	neural	ADJ
alkej-16	199	33	networks	network	NOUN
alkej-16	199	34	which	which	PRON
alkej-16	199	35	approximate	approximate	VERB
alkej-16	199	36	]	]	PUNCT
alkej-16	199	37	[	[	X
alkej-16	199	38	f	f	X
alkej-16	199	39	^	^	PUNCT
alkej-16	199	40	−	−	PROPN
alkej-16	199	41	and	and	CCONJ
alkej-16	199	42	]	]	X
alkej-16	199	43	[	[	X
alkej-16	199	44	g	g	X
alkej-16	199	45	−	−	PROPN
alkej-16	199	46	∧	∧	PROPN
alkej-16	199	47	of	of	ADP
alkej-16	199	48	equation	equation	NOUN
alkej-16	199	49	(	(	PUNCT
alkej-16	199	50	5	5	NUM
alkej-16	199	51	)	)	PUNCT
alkej-16	199	52	,	,	PUNCT
alkej-16	199	53	respectively	respectively	ADV
alkej-16	199	54	.	.	PUNCT
alkej-16	200	1	since	since	SCONJ
alkej-16	200	2	each	each	PRON
alkej-16	200	3	of	of	ADP
alkej-16	200	4	n1[-	n1[-	PROPN
alkej-16	200	5	]	]	PUNCT
alkej-16	200	6	and	and	CCONJ
alkej-16	200	7	n2[-	n2[-	NOUN
alkej-16	200	8	]	]	PUNCT
alkej-16	200	9	has	have	VERB
alkej-16	200	10	three	three	NUM
alkej-16	200	11	input	input	NOUN
alkej-16	200	12	)	)	PUNCT
alkej-16	200	13	(	(	PUNCT
alkej-16	200	14	ky	ky	NOUN
alkej-16	200	15	m	m	PROPN
alkej-16	200	16	(	(	PUNCT
alkej-16	200	17	see	see	VERB
alkej-16	200	18	equation	equation	NOUN
alkej-16	200	19	(	(	PUNCT
alkej-16	200	20	41	41	NUM
alkej-16	200	21	)	)	PUNCT
alkej-16	200	22	)	)	PUNCT
alkej-16	200	23	.	.	PUNCT
alkej-16	201	1	using	use	VERB
alkej-16	201	2	the	the	DET
alkej-16	201	3	same	same	ADJ
alkej-16	201	4	random	random	ADJ
alkej-16	201	5	input	input	NOUN
alkej-16	201	6	sequence	sequence	NOUN
alkej-16	201	7	u(k	u(k	PROPN
alkej-16	201	8	)	)	PUNCT
alkej-16	201	9	with	with	ADP
alkej-16	201	10	1)k(u	1)k(u	NUM
alkej-16	201	11	≤	≤	NOUN
alkej-16	201	12	a	a	DET
alkej-16	201	13	training	training	NOUN
alkej-16	201	14	set	set	NOUN
alkej-16	201	15	of	of	ADP
alkej-16	201	16	100	100	NUM
alkej-16	201	17	patterns	pattern	NOUN
alkej-16	201	18	input	input	NOUN
alkej-16	201	19	-	-	PUNCT
alkej-16	201	20	output	output	NOUN
alkej-16	201	21	used	use	VERB
alkej-16	201	22	on	on	ADP
alkej-16	201	23	the	the	DET
alkej-16	201	24	same	same	ADJ
alkej-16	201	25	the	the	DET
alkej-16	201	26	neural	neural	ADJ
alkej-16	201	27	networks	network	NOUN
alkej-16	201	28	n1[-	n1[-	PROPN
alkej-16	201	29	]	]	PUNCT
alkej-16	201	30	&	&	CCONJ
alkej-16	201	31	n2[-	n2[-	PROPN
alkej-16	201	32	]	]	PUNCT
alkej-16	201	33	that	that	SCONJ
alkej-16	201	34	there	there	PRON
alkej-16	201	35	are	be	AUX
alkej-16	201	36	learned	learn	VERB
alkej-16	201	37	off	off	ADP
alkej-16	201	38	-	-	PUNCT
alkej-16	201	39	line	line	NOUN
alkej-16	201	40	with	with	ADP
alkej-16	201	41	serialparallel	serialparallel	ADJ
alkej-16	201	42	identification	identification	NOUN
alkej-16	201	43	with	with	ADP
alkej-16	201	44	learning	learn	VERB
alkej-16	201	45	rate	rate	NOUN
alkej-16	201	46	1η	1η	NOUN
alkej-16	201	47	for	for	ADP
alkej-16	201	48	n1	n1	PROPN
alkej-16	201	49	and	and	CCONJ
alkej-16	201	50	2η	2η	PROPN
alkej-16	201	51	for	for	ADP
alkej-16	201	52	n2	n2	NOUN
alkej-16	201	53	and	and	CCONJ
alkej-16	201	54	both	both	PRON
alkej-16	201	55	were	be	AUX
alkej-16	201	56	taken	take	VERB
alkej-16	201	57	to	to	PART
alkej-16	201	58	be	be	AUX
alkej-16	201	59	equal	equal	ADJ
alkej-16	201	60	to	to	ADP
alkej-16	201	61	0.3	0.3	NUM
alkej-16	201	62	.	.	PUNCT
alkej-16	202	1	during	during	ADP
alkej-16	202	2	the	the	DET
alkej-16	202	3	training	training	NOUN
alkej-16	202	4	phase	phase	NOUN
alkej-16	202	5	,	,	PUNCT
alkej-16	202	6	the	the	DET
alkej-16	202	7	training	training	NOUN
alkej-16	202	8	set	set	NOUN
alkej-16	202	9	has	have	AUX
alkej-16	202	10	been	be	AUX
alkej-16	202	11	presented	present	VERB
alkej-16	202	12	to	to	ADP
alkej-16	202	13	the	the	DET
alkej-16	202	14	network	network	NOUN
alkej-16	202	15	many	many	ADJ
alkej-16	202	16	times	time	NOUN
alkej-16	202	17	.	.	PUNCT
alkej-16	203	1	however	however	ADV
alkej-16	203	2	,	,	PUNCT
alkej-16	203	3	for	for	ADP
alkej-16	203	4	this	this	DET
alkej-16	203	5	example	example	NOUN
alkej-16	203	6	after	after	SCONJ
alkej-16	203	7	5000	5000	NUM
alkej-16	203	8	epochs	epoch	VERB
alkej-16	203	9	the	the	DET
alkej-16	203	10	average	average	ADJ
alkej-16	203	11	system	system	NOUN
alkej-16	203	12	error	error	NOUN
alkej-16	203	13	(	(	PUNCT
alkej-16	203	14	ase	ase	NOUN
alkej-16	203	15	)	)	PUNCT
alkej-16	203	16	computed	compute	VERB
alkej-16	203	17	for	for	ADP
alkej-16	203	18	the	the	DET
alkej-16	203	19	latest	late	ADJ
alkej-16	203	20	epoch	epoch	NOUN
alkej-16	203	21	,	,	PUNCT
alkej-16	203	22	which	which	PRON
alkej-16	203	23	is	be	AUX
alkej-16	203	24	described	describe	VERB
alkej-16	203	25	by	by	ADP
alkej-16	203	26	equation	equation	NOUN
alkej-16	203	27	(	(	PUNCT
alkej-16	203	28	39	39	NUM
alkej-16	203	29	)	)	PUNCT
alkej-16	203	30	was	be	AUX
alkej-16	203	31	61013.1	61013.1	NUM
alkej-16	203	32	−×	−×	NOUN
alkej-16	203	33	.	.	PUNCT
alkej-16	204	1	fig.9	fig.9	PROPN
alkej-16	204	2	-	-	PUNCT
alkej-16	204	3	a	a	PRON
alkej-16	204	4	compares	compare	VERB
alkej-16	204	5	the	the	DET
alkej-16	204	6	time	time	NOUN
alkej-16	204	7	response	response	NOUN
alkej-16	204	8	of	of	ADP
alkej-16	204	9	the	the	DET
alkej-16	204	10	parallel	parallel	ADJ
alkej-16	204	11	model	model	NOUN
alkej-16	204	12	of	of	ADP
alkej-16	204	13	equation	equation	NOUN
alkej-16	204	14	(	(	PUNCT
alkej-16	204	15	41	41	NUM
alkej-16	204	16	)	)	PUNCT
alkej-16	204	17	with	with	ADP
alkej-16	204	18	the	the	DET
alkej-16	204	19	actual	actual	ADJ
alkej-16	204	20	plant	plant	NOUN
alkej-16	204	21	output	output	NOUN
alkej-16	204	22	for	for	ADP
alkej-16	204	23	the	the	DET
alkej-16	204	24	input	input	NOUN
alkej-16	204	25	as	as	ADP
alkej-16	204	26	a	a	DET
alkej-16	204	27	learning	learning	NOUN
alkej-16	204	28	set	set	NOUN
alkej-16	204	29	,	,	PUNCT
alkej-16	204	30	while	while	SCONJ
alkej-16	204	31	fig.9	fig.9	PROPN
alkej-16	204	32	-	-	PUNCT
alkej-16	204	33	b	b	NOUN
alkej-16	204	34	compares	compare	VERB
alkej-16	204	35	the	the	DET
alkej-16	204	36	time	time	NOUN
alkej-16	204	37	response	response	NOUN
alkej-16	204	38	of	of	ADP
alkej-16	204	39	the	the	DET
alkej-16	204	40	parallel	parallel	ADJ
alkej-16	204	41	model	model	NOUN
alkej-16	204	42	of	of	ADP
alkej-16	204	43	equation	equation	NOUN
alkej-16	204	44	(	(	PUNCT
alkej-16	204	45	36	36	NUM
alkej-16	204	46	)	)	PUNCT
alkej-16	204	47	with	with	ADP
alkej-16	204	48	the	the	DET
alkej-16	204	49	actual	actual	ADJ
alkej-16	204	50	plant	plant	NOUN
alkej-16	204	51	output	output	NOUN
alkej-16	204	52	for	for	ADP
alkej-16	204	53	the	the	DET
alkej-16	204	54	input	input	NOUN
alkej-16	204	55	u(k	u(k	PROPN
alkej-16	204	56	)	)	PUNCT
alkej-16	204	57	applied	apply	VERB
alkej-16	204	58	as	as	ADP
alkej-16	204	59	testing	testing	NOUN
alkej-16	204	60	set	set	VERB
alkej-16	204	61	generated	generate	VERB
alkej-16	204	62	from	from	ADP
alkej-16	204	63	equation	equation	NOUN
alkej-16	204	64	(	(	PUNCT
alkej-16	204	65	35	35	NUM
alkej-16	204	66	)	)	PUNCT
alkej-16	204	67	.	.	PUNCT
alkej-16	205	1	also	also	ADV
alkej-16	205	2	fig.10	fig.10	PRON
alkej-16	205	3	shows	show	VERB
alkej-16	205	4	a	a	DET
alkej-16	205	5	plot	plot	NOUN
alkej-16	205	6	of	of	ADP
alkej-16	205	7	the	the	DET
alkej-16	205	8	coefficient	coefficient	NOUN
alkej-16	205	9	of	of	ADP
alkej-16	205	10	u(k	u(k	PROPN
alkej-16	205	11	)	)	PUNCT
alkej-16	205	12	which	which	PRON
alkej-16	205	13	is	be	AUX
alkej-16	205	14	]	]	PUNCT
alkej-16	205	15	[	[	X
alkej-16	205	16	g	g	X
alkej-16	205	17	−	−	PROPN
alkej-16	205	18	∧	∧	PROPN
alkej-16	205	19	for	for	ADP
alkej-16	205	20	the	the	DET
alkej-16	205	21	narma	narma	NOUN
alkej-16	205	22	-	-	PUNCT
alkej-16	205	23	l2	l2	NOUN
alkej-16	205	24	models	model	NOUN
alkej-16	205	25	as	as	ADP
alkej-16	205	26	a	a	DET
alkej-16	205	27	function	function	NOUN
alkej-16	205	28	of	of	ADP
alkej-16	205	29	time	time	NOUN
alkej-16	205	30	with	with	ADP
alkej-16	205	31	values	value	NOUN
alkej-16	205	32	computed	compute	VERB
alkej-16	205	33	using	use	VERB
alkej-16	205	34	the	the	DET
alkej-16	205	35	corresponding	corresponding	ADJ
alkej-16	205	36	network	network	NOUN
alkej-16	205	37	)	)	PUNCT
alkej-16	205	38	(	(	PUNCT
alkej-16	205	39	)	)	PUNCT
alkej-16	205	40	]	]	PUNCT
alkej-16	205	41	(	(	PUNCT
alkej-16	205	42	[	[	X
alkej-16	205	43	2	2	NUM
alkej-16	205	44	kukyn	kukyn	NOUN
alkej-16	205	45	p	p	NOUN
alkej-16	205	46	,	,	PUNCT
alkej-16	205	47	when	when	SCONJ
alkej-16	205	48	a	a	DET
alkej-16	205	49	random	random	ADJ
alkej-16	205	50	input	input	NOUN
alkej-16	205	51	sequence	sequence	NOUN
alkej-16	205	52	u(k	u(k	PROPN
alkej-16	205	53	)	)	PUNCT
alkej-16	205	54	with	with	ADP
alkej-16	205	55	1)k(u	1)k(u	NUM
alkej-16	205	56	≤	≤	NOUN
alkej-16	205	57	has	have	AUX
alkej-16	205	58	been	be	AUX
alkej-16	205	59	applied	apply	VERB
alkej-16	205	60	to	to	ADP
alkej-16	205	61	the	the	DET
alkej-16	205	62	model	model	NOUN
alkej-16	205	63	.	.	PUNCT
alkej-16	206	1	as	as	SCONJ
alkej-16	206	2	shown	show	VERB
alkej-16	206	3	in	in	ADP
alkej-16	206	4	fig.10	fig.10	PRON
alkej-16	206	5	,	,	PUNCT
alkej-16	206	6	]	]	X
alkej-16	206	7	[	[	X
alkej-16	206	8	g	g	X
alkej-16	206	9	−	−	PROPN
alkej-16	206	10	∧	∧	PROPN
alkej-16	206	11	is	be	AUX
alkej-16	206	12	sign	sign	VERB
alkej-16	206	13	definite	definite	ADJ
alkej-16	206	14	in	in	ADP
alkej-16	206	15	the	the	DET
alkej-16	206	16	region	region	NOUN
alkej-16	206	17	of	of	ADP
alkej-16	206	18	interest	interest	NOUN
alkej-16	206	19	.	.	PUNCT
alkej-16	207	1	this	this	PRON
alkej-16	207	2	means	mean	VERB
alkej-16	207	3	that	that	SCONJ
alkej-16	207	4	the	the	DET
alkej-16	207	5	plant	plant	NOUN
alkej-16	207	6	is	be	AUX
alkej-16	207	7	invertable	invertable	ADJ
alkej-16	207	8	,	,	PUNCT
alkej-16	207	9	or	or	CCONJ
alkej-16	207	10	in	in	ADP
alkej-16	207	11	other	other	ADJ
alkej-16	207	12	words	word	NOUN
alkej-16	207	13	;	;	PUNCT
alkej-16	207	14	the	the	DET
alkej-16	207	15	model	model	NOUN
alkej-16	207	16	output	output	NOUN
alkej-16	207	17	)	)	PUNCT
alkej-16	207	18	1k(ym	1k(ym	PROPN
alkej-16	208	1	+	+	CCONJ
alkej-16	208	2	is	be	AUX
alkej-16	208	3	monotonic	monotonic	ADJ
alkej-16	208	4	with	with	ADP
alkej-16	208	5	respect	respect	NOUN
alkej-16	208	6	to	to	ADP
alkej-16	208	7	ahmed	ahmed	PROPN
alkej-16	208	8	sabah	sabah	PROPN
alkej-16	208	9	abdul	abdul	PROPN
alkej-16	208	10	ameer	ameer	PROPN
alkej-16	208	11	/al	/al	PROPN
alkej-16	208	12	khwarizmi	khwarizmi	PROPN
alkej-16	208	13	engineering	engineering	PROPN
alkej-16	208	14	journal	journal	PROPN
alkej-16	208	15	,	,	PUNCT
alkej-16	208	16	vol	vol	NOUN
alkej-16	208	17	.	.	PROPN
alkej-16	208	18	1	1	NUM
alkej-16	208	19	,	,	PUNCT
alkej-16	208	20	no	no	INTJ
alkej-16	208	21	.	.	NOUN
alkej-16	208	22	1	1	NUM
alkej-16	208	23	,	,	PUNCT
alkej-16	208	24	pp	pp	ADV
alkej-16	208	25	1	1	NUM
alkej-16	208	26	-	-	SYM
alkej-16	208	27	18	18	NUM
alkej-16	208	28	(	(	PUNCT
alkej-16	208	29	2005	2005	NUM
alkej-16	208	30	)	)	PUNCT
alkej-16	208	31	١٢	١٢	NUM
alkej-16	209	1	-2	-2	NOUN
alkej-16	209	2	-1.5	-1.5	NUM
alkej-16	209	3	-1	-1	PROPN
alkej-16	210	1	-0.5	-0.5	X
alkej-16	210	2	0	0	NUM
alkej-16	210	3	0.5	0.5	NUM
alkej-16	210	4	1	1	NUM
alkej-16	210	5	1.5	1.5	NUM
alkej-16	210	6	2	2	NUM
alkej-16	210	7	0	0	NUM
alkej-16	210	8	10	10	NUM
alkej-16	210	9	20	20	NUM
alkej-16	210	10	30	30	NUM
alkej-16	210	11	40	40	NUM
alkej-16	210	12	50	50	NUM
alkej-16	210	13	60	60	NUM
alkej-16	210	14	70	70	NUM
alkej-16	210	15	80	80	NUM
alkej-16	210	16	90	90	NUM
alkej-16	210	17	100	100	NUM
alkej-16	211	1	k	k	NOUN
alkej-16	211	2	ym	ym	PROPN
alkej-16	212	1	[	[	X
alkej-16	212	2	k	k	X
alkej-16	212	3	]	]	X
alkej-16	212	4	&	&	CCONJ
alkej-16	212	5	y	y	PROPN
alkej-16	212	6	p	p	X
alkej-16	212	7	[	[	PUNCT
alkej-16	212	8	k	k	X
alkej-16	212	9	]	]	X
alkej-16	212	10	fig	fig	NOUN
alkej-16	212	11	(	(	PUNCT
alkej-16	212	12	8	8	NUM
alkej-16	212	13	-	-	PUNCT
alkej-16	212	14	a	a	NOUN
alkej-16	212	15	):	):	PUNCT
alkej-16	212	16	the	the	DET
alkej-16	212	17	response	response	NOUN
alkej-16	212	18	of	of	ADP
alkej-16	212	19	the	the	DET
alkej-16	212	20	plant	plant	NOUN
alkej-16	212	21	&	&	CCONJ
alkej-16	212	22	the	the	DET
alkej-16	212	23	serial	serial	ADJ
alkej-16	212	24	-	-	PUNCT
alkej-16	212	25	parallel	parallel	ADJ
alkej-16	212	26	narma	narma	NOUN
alkej-16	212	27	-	-	PUNCT
alkej-16	212	28	l2	l2	NOUN
alkej-16	212	29	identification	identification	NOUN
alkej-16	212	30	model	model	NOUN
alkej-16	212	31	for	for	ADP
alkej-16	212	32	learning	learn	VERB
alkej-16	212	33	patterns	pattern	NOUN
alkej-16	212	34	plant	plant	NOUN
alkej-16	212	35	response	response	NOUN
alkej-16	212	36	-----model	-----model	ADP
alkej-16	212	37	response	response	NOUN
alkej-16	212	38	-2	-2	INTJ
alkej-16	212	39	-1.5	-1.5	NUM
alkej-16	212	40	-1	-1	PROPN
alkej-16	213	1	-0.5	-0.5	X
alkej-16	213	2	0	0	NUM
alkej-16	213	3	0.5	0.5	NUM
alkej-16	213	4	1	1	NUM
alkej-16	213	5	1.5	1.5	NUM
alkej-16	213	6	2	2	NUM
alkej-16	213	7	0	0	NUM
alkej-16	213	8	10	10	NUM
alkej-16	213	9	20	20	NUM
alkej-16	213	10	30	30	NUM
alkej-16	213	11	40	40	NUM
alkej-16	213	12	50	50	NUM
alkej-16	213	13	60	60	NUM
alkej-16	213	14	70	70	NUM
alkej-16	213	15	80	80	NUM
alkej-16	213	16	90	90	NUM
alkej-16	213	17	100	100	NUM
alkej-16	213	18	k	k	NOUN
alkej-16	213	19	yp	yp	PROPN
alkej-16	214	1	[	[	X
alkej-16	214	2	k	k	X
alkej-16	214	3	]	]	X
alkej-16	214	4	&	&	CCONJ
alkej-16	214	5	ym	ym	X
alkej-16	215	1	[	[	X
alkej-16	215	2	k	k	X
alkej-16	215	3	]	]	X
alkej-16	215	4	fig	fig	NOUN
alkej-16	215	5	(	(	PUNCT
alkej-16	215	6	8	8	NUM
alkej-16	215	7	-	-	PUNCT
alkej-16	215	8	b	b	NOUN
alkej-16	215	9	):	):	PUNCT
alkej-16	215	10	the	the	DET
alkej-16	215	11	response	response	NOUN
alkej-16	215	12	of	of	ADP
alkej-16	215	13	the	the	DET
alkej-16	215	14	plant	plant	NOUN
alkej-16	215	15	&	&	CCONJ
alkej-16	215	16	the	the	DET
alkej-16	215	17	serial	serial	ADJ
alkej-16	215	18	-	-	PUNCT
alkej-16	215	19	parallel	parallel	ADJ
alkej-16	215	20	narma	narma	NOUN
alkej-16	215	21	-	-	PUNCT
alkej-16	215	22	l2	l2	NOUN
alkej-16	215	23	identification	identification	NOUN
alkej-16	215	24	model	model	NOUN
alkej-16	215	25	for	for	ADP
alkej-16	215	26	testing	testing	NOUN
alkej-16	215	27	patterns	pattern	NOUN
alkej-16	215	28	plant	plant	NOUN
alkej-16	215	29	response	response	NOUN
alkej-16	215	30	-----model	-----model	ADP
alkej-16	215	31	response	response	NOUN
alkej-16	215	32	-2	-2	INTJ
alkej-16	215	33	-1.5	-1.5	NUM
alkej-16	215	34	-1	-1	PROPN
alkej-16	216	1	-0.5	-0.5	X
alkej-16	216	2	0	0	NUM
alkej-16	216	3	0.5	0.5	NUM
alkej-16	216	4	1	1	NUM
alkej-16	216	5	1.5	1.5	NUM
alkej-16	216	6	2	2	NUM
alkej-16	216	7	0	0	NUM
alkej-16	216	8	10	10	NUM
alkej-16	216	9	20	20	NUM
alkej-16	216	10	30	30	NUM
alkej-16	216	11	40	40	NUM
alkej-16	216	12	50	50	NUM
alkej-16	216	13	60	60	NUM
alkej-16	216	14	70	70	NUM
alkej-16	216	15	80	80	NUM
alkej-16	216	16	90	90	NUM
alkej-16	216	17	100	100	NUM
alkej-16	217	1	k	k	NOUN
alkej-16	217	2	ym	ym	PROPN
alkej-16	218	1	[	[	X
alkej-16	218	2	k	k	X
alkej-16	218	3	]	]	X
alkej-16	218	4	&	&	CCONJ
alkej-16	218	5	y	y	PROPN
alkej-16	218	6	p	p	X
alkej-16	218	7	[	[	PUNCT
alkej-16	218	8	k	k	X
alkej-16	218	9	]	]	X
alkej-16	218	10	fig	fig	NOUN
alkej-16	218	11	(	(	PUNCT
alkej-16	218	12	9	9	NUM
alkej-16	218	13	-	-	PUNCT
alkej-16	218	14	a	a	NOUN
alkej-16	218	15	):	):	PUNCT
alkej-16	218	16	the	the	DET
alkej-16	218	17	response	response	NOUN
alkej-16	218	18	of	of	ADP
alkej-16	218	19	the	the	DET
alkej-16	218	20	plant	plant	NOUN
alkej-16	218	21	&	&	CCONJ
alkej-16	218	22	the	the	DET
alkej-16	218	23	parallel	parallel	ADJ
alkej-16	218	24	narma	narma	NOUN
alkej-16	218	25	-	-	PUNCT
alkej-16	218	26	l2	l2	NOUN
alkej-16	218	27	identification	identification	NOUN
alkej-16	218	28	model	model	NOUN
alkej-16	218	29	for	for	ADP
alkej-16	218	30	learning	learn	VERB
alkej-16	218	31	patterns	pattern	NOUN
alkej-16	218	32	plant	plant	NOUN
alkej-16	218	33	response	response	NOUN
alkej-16	218	34	-----model	-----model	ADP
alkej-16	218	35	response	response	PROPN
alkej-16	218	36	ahmed	ahmed	PROPN
alkej-16	218	37	sabah	sabah	PROPN
alkej-16	218	38	abdul	abdul	PROPN
alkej-16	218	39	ameer	ameer	PROPN
alkej-16	218	40	/al	/al	PROPN
alkej-16	218	41	khwarizmi	khwarizmi	PROPN
alkej-16	218	42	engineering	engineering	PROPN
alkej-16	218	43	journal	journal	PROPN
alkej-16	218	44	,	,	PUNCT
alkej-16	218	45	vol	vol	NOUN
alkej-16	218	46	.	.	PROPN
alkej-16	218	47	1	1	NUM
alkej-16	218	48	,	,	PUNCT
alkej-16	218	49	no	no	INTJ
alkej-16	218	50	.	.	NOUN
alkej-16	218	51	1	1	NUM
alkej-16	218	52	,	,	PUNCT
alkej-16	218	53	pp	pp	ADV
alkej-16	218	54	1	1	NUM
alkej-16	218	55	-	-	SYM
alkej-16	218	56	18	18	NUM
alkej-16	218	57	(	(	PUNCT
alkej-16	218	58	2005	2005	NUM
alkej-16	218	59	)	)	PUNCT
alkej-16	218	60	١٣	١٣	NUM
alkej-16	218	61	u(k	u(k	PROPN
alkej-16	218	62	)	)	PUNCT
alkej-16	218	63	.	.	PUNCT
alkej-16	219	1	the	the	DET
alkej-16	219	2	variation	variation	NOUN
alkej-16	219	3	of	of	ADP
alkej-16	219	4	]	]	PUNCT
alkej-16	219	5	[	[	X
alkej-16	219	6	g	g	X
alkej-16	219	7	−	−	PROPN
alkej-16	219	8	∧	∧	PROPN
alkej-16	219	9	is	be	AUX
alkej-16	219	10	approximately	approximately	ADV
alkej-16	219	11	around	around	ADP
alkej-16	219	12	1.2	1.2	NUM
alkej-16	219	13	as	as	SCONJ
alkej-16	219	14	it	it	PRON
alkej-16	219	15	is	be	AUX
alkej-16	219	16	expected	expect	VERB
alkej-16	219	17	.	.	PUNCT
alkej-16	220	1	this	this	PRON
alkej-16	220	2	can	can	AUX
alkej-16	220	3	be	be	AUX
alkej-16	220	4	explained	explain	VERB
alkej-16	220	5	easily	easily	ADV
alkej-16	220	6	by	by	ADP
alkej-16	220	7	noting	note	VERB
alkej-16	220	8	the	the	DET
alkej-16	220	9	fact	fact	NOUN
alkej-16	220	10	what	what	PRON
alkej-16	220	11	]	]	X
alkej-16	220	12	[	[	X
alkej-16	220	13	g	g	X
alkej-16	220	14	−	−	PROPN
alkej-16	220	15	∧	∧	PROPN
alkej-16	220	16	resembles	resemble	VERB
alkej-16	220	17	the	the	DET
alkej-16	220	18	plant	plant	NOUN
alkej-16	220	19	jacobain	jacobain	NOUN
alkej-16	220	20	is	be	AUX
alkej-16	220	21	equal	equal	ADJ
alkej-16	220	22	to	to	ADP
alkej-16	220	23	as	as	ADP
alkej-16	220	24	equation	equation	NOUN
alkej-16	220	25	(	(	PUNCT
alkej-16	220	26	7	7	NUM
alkej-16	220	27	)	)	PUNCT
alkej-16	220	28	and	and	CCONJ
alkej-16	220	29	for	for	ADP
alkej-16	220	30	this	this	DET
alkej-16	220	31	example	example	NOUN
alkej-16	220	32	2.1	2.1	NUM
alkej-16	220	33	)	)	PUNCT
alkej-16	220	34	k(u	k(u	NOUN
alkej-16	220	35	)	)	PUNCT
alkej-16	220	36	1k(yp	1k(yp	NUM
alkej-16	220	37	=	=	SYM
alkej-16	220	38	∂	∂	NUM
alkej-16	220	39	+	+	NOUN
alkej-16	220	40	∂	∂	NUM
alkej-16	220	41	.	.	PUNCT
alkej-16	221	1	to	to	PART
alkej-16	221	2	apply	apply	VERB
alkej-16	221	3	the	the	DET
alkej-16	221	4	proposed	propose	VERB
alkej-16	221	5	structure	structure	NOUN
alkej-16	221	6	of	of	ADP
alkej-16	221	7	controller	controller	NOUN
alkej-16	221	8	after	after	ADP
alkej-16	221	9	good	good	ADJ
alkej-16	221	10	learning	learning	NOUN
alkej-16	221	11	of	of	ADP
alkej-16	221	12	the	the	DET
alkej-16	221	13	identifier	identifier	NOUN
alkej-16	221	14	as	as	ADP
alkej-16	221	15	pm	pm	NOUN
alkej-16	221	16	yy	yy	PROPN
alkej-16	222	1	≈	≈	PROPN
alkej-16	222	2	.	.	PUNCT
alkej-16	223	1	it	it	PRON
alkej-16	223	2	used	use	VERB
alkej-16	223	3	the	the	DET
alkej-16	223	4	desired	desire	VERB
alkej-16	223	5	trajectory	trajectory	NOUN
alkej-16	223	6	and	and	CCONJ
alkej-16	223	7	the	the	DET
alkej-16	223	8	training	training	NOUN
alkej-16	223	9	done	do	VERB
alkej-16	223	10	by	by	ADP
alkej-16	223	11	repeating	repeat	VERB
alkej-16	223	12	the	the	DET
alkej-16	223	13	desired	desire	VERB
alkej-16	223	14	trajectory	trajectory	NOUN
alkej-16	223	15	cycles	cycle	NOUN
alkej-16	223	16	over	over	ADP
alkej-16	223	17	26000	26000	NUM
alkej-16	223	18	times	time	NOUN
alkej-16	223	19	.	.	PUNCT
alkej-16	224	1	the	the	DET
alkej-16	224	2	neural	neural	ADJ
alkej-16	224	3	networks	network	NOUN
alkej-16	224	4	are	be	AUX
alkej-16	224	5	used	use	VERB
alkej-16	224	6	to	to	PART
alkej-16	224	7	minimize	minimize	VERB
alkej-16	224	8	the	the	DET
alkej-16	224	9	performance	performance	NOUN
alkej-16	224	10	error	error	NOUN
alkej-16	224	11	between	between	ADP
alkej-16	224	12	the	the	DET
alkej-16	224	13	reference	reference	NOUN
alkej-16	224	14	and	and	CCONJ
alkej-16	224	15	the	the	DET
alkej-16	224	16	model	model	NOUN
alkej-16	224	17	output	output	NOUN
alkej-16	224	18	,	,	PUNCT
alkej-16	224	19	where	where	SCONJ
alkej-16	224	20	the	the	DET
alkej-16	224	21	model	model	NOUN
alkej-16	224	22	output	output	NOUN
alkej-16	224	23	is	be	AUX
alkej-16	224	24	similar	similar	ADJ
alkej-16	224	25	to	to	ADP
alkej-16	224	26	the	the	DET
alkej-16	224	27	actual	actual	ADJ
alkej-16	224	28	output	output	NOUN
alkej-16	224	29	.	.	PUNCT
alkej-16	225	1	convergence	convergence	NOUN
alkej-16	225	2	is	be	AUX
alkej-16	225	3	achieved	achieve	VERB
alkej-16	225	4	when	when	SCONJ
alkej-16	225	5	the	the	DET
alkej-16	225	6	performance	performance	NOUN
alkej-16	225	7	error	error	NOUN
alkej-16	225	8	falls	fall	VERB
alkej-16	225	9	below	below	ADP
alkej-16	225	10	a	a	DET
alkej-16	225	11	pre	pre	ADJ
alkej-16	225	12	-	-	ADJ
alkej-16	225	13	specified	specified	ADJ
alkej-16	225	14	value	value	NOUN
alkej-16	225	15	.	.	PUNCT
alkej-16	226	1	after	after	ADP
alkej-16	226	2	training	training	NOUN
alkej-16	226	3	,	,	PUNCT
alkej-16	226	4	it	it	PRON
alkej-16	226	5	can	can	AUX
alkej-16	226	6	be	be	AUX
alkej-16	226	7	observed	observe	VERB
alkej-16	226	8	that	that	SCONJ
alkej-16	226	9	the	the	DET
alkej-16	226	10	actual	actual	ADJ
alkej-16	226	11	output	output	NOUN
alkej-16	226	12	of	of	ADP
alkej-16	226	13	the	the	DET
alkej-16	226	14	plant	plant	NOUN
alkej-16	226	15	is	be	AUX
alkej-16	226	16	following	follow	VERB
alkej-16	226	17	the	the	DET
alkej-16	226	18	desired	desire	VERB
alkej-16	226	19	trajectory	trajectory	NOUN
alkej-16	226	20	and	and	CCONJ
alkej-16	226	21	the	the	DET
alkej-16	226	22	model	model	NOUN
alkej-16	226	23	output	output	NOUN
alkej-16	226	24	is	be	AUX
alkej-16	226	25	the	the	DET
alkej-16	226	26	same	same	ADJ
alkej-16	226	27	as	as	ADP
alkej-16	226	28	the	the	DET
alkej-16	226	29	actual	actual	ADJ
alkej-16	226	30	output	output	NOUN
alkej-16	226	31	in	in	ADP
alkej-16	226	32	figs.11	figs.11	PROPN
alkej-16	226	33	&	&	CCONJ
alkej-16	226	34	12	12	NUM
alkej-16	226	35	.	.	PUNCT
alkej-16	227	1	and	and	CCONJ
alkej-16	227	2	also	also	ADV
alkej-16	227	3	,	,	PUNCT
alkej-16	227	4	the	the	DET
alkej-16	227	5	gains	gain	NOUN
alkej-16	227	6	of	of	ADP
alkej-16	227	7	the	the	DET
alkej-16	227	8	pid	pid	NOUN
alkej-16	227	9	selftuning	selftune	VERB
alkej-16	227	10	neural	neural	ADJ
alkej-16	227	11	controller	controller	NOUN
alkej-16	227	12	as	as	SCONJ
alkej-16	227	13	shown	show	VERB
alkej-16	227	14	in	in	ADP
alkej-16	227	15	fig	fig	NOUN
alkej-16	227	16	.	.	PUNCT
alkej-16	228	1	13	13	NUM
alkej-16	228	2	-a	-a	NUM
alkej-16	228	3	,	,	PUNCT
alkej-16	228	4	b	b	NOUN
alkej-16	228	5	,	,	PUNCT
alkej-16	228	6	&	&	CCONJ
alkej-16	228	7	c	c	PROPN
alkej-16	228	8	kp	kp	PROPN
alkej-16	228	9	,	,	PUNCT
alkej-16	228	10	ki	ki	PROPN
alkej-16	228	11	,	,	PUNCT
alkej-16	228	12	&	&	CCONJ
alkej-16	228	13	kd	kd	PROPN
alkej-16	228	14	1.19	1.19	NUM
alkej-16	228	15	1.195	1.195	NUM
alkej-16	228	16	1.2	1.2	NUM
alkej-16	228	17	1.205	1.205	NUM
alkej-16	228	18	1.21	1.21	NUM
alkej-16	228	19	0	0	NUM
alkej-16	228	20	10	10	NUM
alkej-16	228	21	20	20	NUM
alkej-16	228	22	30	30	NUM
alkej-16	228	23	40	40	NUM
alkej-16	228	24	50	50	NUM
alkej-16	228	25	60	60	NUM
alkej-16	228	26	70	70	NUM
alkej-16	228	27	80	80	NUM
alkej-16	228	28	90	90	NUM
alkej-16	228	29	100	100	NUM
alkej-16	229	1	k	k	NOUN
alkej-16	229	2	ja	ja	PROPN
alkej-16	229	3	co	co	PROPN
alkej-16	229	4	ba	ba	PROPN
alkej-16	229	5	in	in	ADP
alkej-16	229	6	o	o	PROPN
alkej-16	230	1	f	f	PROPN
alkej-16	230	2	t	t	NOUN
alkej-16	231	1	he	he	PRON
alkej-16	231	2	p	p	PROPN
alkej-16	231	3	la	la	INTJ
alkej-16	231	4	nt	not	PART
alkej-16	231	5	fig	fig	NOUN
alkej-16	231	6	(	(	PUNCT
alkej-16	231	7	10	10	NUM
alkej-16	231	8	):	):	PUNCT
alkej-16	231	9	estimated	estimate	VERB
alkej-16	231	10	plant	plant	NOUN
alkej-16	231	11	jacobain	jacobain	NOUN
alkej-16	231	12	-2	-2	INTJ
alkej-16	232	1	-1.5	-1.5	NUM
alkej-16	232	2	-1	-1	PROPN
alkej-16	233	1	-0.5	-0.5	X
alkej-16	233	2	0	0	NUM
alkej-16	233	3	0.5	0.5	NUM
alkej-16	233	4	1	1	NUM
alkej-16	233	5	1.5	1.5	NUM
alkej-16	233	6	2	2	NUM
alkej-16	233	7	0	0	NUM
alkej-16	233	8	10	10	NUM
alkej-16	233	9	20	20	NUM
alkej-16	233	10	30	30	NUM
alkej-16	233	11	40	40	NUM
alkej-16	233	12	50	50	NUM
alkej-16	233	13	60	60	NUM
alkej-16	233	14	70	70	NUM
alkej-16	233	15	80	80	NUM
alkej-16	233	16	90	90	NUM
alkej-16	233	17	100	100	NUM
alkej-16	233	18	k	k	NOUN
alkej-16	233	19	yp	yp	PROPN
alkej-16	234	1	[	[	X
alkej-16	234	2	k	k	X
alkej-16	234	3	]	]	X
alkej-16	234	4	&	&	CCONJ
alkej-16	234	5	ym	ym	X
alkej-16	235	1	[	[	X
alkej-16	235	2	k	k	X
alkej-16	235	3	]	]	X
alkej-16	235	4	fig	fig	NOUN
alkej-16	235	5	(	(	PUNCT
alkej-16	235	6	9	9	NUM
alkej-16	235	7	-	-	PUNCT
alkej-16	235	8	b	b	NOUN
alkej-16	235	9	):	):	PUNCT
alkej-16	235	10	the	the	DET
alkej-16	235	11	response	response	NOUN
alkej-16	235	12	of	of	ADP
alkej-16	235	13	the	the	DET
alkej-16	235	14	plant	plant	NOUN
alkej-16	235	15	&	&	CCONJ
alkej-16	235	16	the	the	DET
alkej-16	235	17	parallel	parallel	ADJ
alkej-16	235	18	narma	narma	NOUN
alkej-16	235	19	-	-	PUNCT
alkej-16	235	20	l2	l2	NOUN
alkej-16	235	21	identification	identification	NOUN
alkej-16	235	22	model	model	NOUN
alkej-16	235	23	for	for	ADP
alkej-16	235	24	testing	testing	NOUN
alkej-16	235	25	patterns	pattern	NOUN
alkej-16	235	26	plant	plant	NOUN
alkej-16	235	27	response	response	NOUN
alkej-16	235	28	-----model	-----model	ADP
alkej-16	235	29	response	response	PROPN
alkej-16	235	30	ahmed	ahmed	PROPN
alkej-16	235	31	sabah	sabah	PROPN
alkej-16	235	32	abdul	abdul	PROPN
alkej-16	235	33	ameer	ameer	PROPN
alkej-16	235	34	/al	/al	PROPN
alkej-16	235	35	khwarizmi	khwarizmi	PROPN
alkej-16	235	36	engineering	engineering	PROPN
alkej-16	235	37	journal	journal	PROPN
alkej-16	235	38	,	,	PUNCT
alkej-16	235	39	vol	vol	NOUN
alkej-16	235	40	.	.	PROPN
alkej-16	235	41	1	1	NUM
alkej-16	235	42	,	,	PUNCT
alkej-16	235	43	no	no	INTJ
alkej-16	235	44	.	.	NOUN
alkej-16	235	45	1	1	NUM
alkej-16	235	46	,	,	PUNCT
alkej-16	235	47	pp	pp	ADV
alkej-16	235	48	1	1	NUM
alkej-16	235	49	-	-	SYM
alkej-16	235	50	18	18	NUM
alkej-16	235	51	(	(	PUNCT
alkej-16	235	52	2005	2005	NUM
alkej-16	235	53	)	)	PUNCT
alkej-16	235	54	١٤	١٤	NUM
alkej-16	235	55	-1	-1	SYM
alkej-16	235	56	-0.5	-0.5	X
alkej-16	235	57	0	0	NUM
alkej-16	235	58	0.5	0.5	NUM
alkej-16	235	59	1	1	NUM
alkej-16	235	60	0	0	NUM
alkej-16	235	61	10	10	NUM
alkej-16	235	62	20	20	NUM
alkej-16	235	63	30	30	NUM
alkej-16	235	64	40	40	NUM
alkej-16	235	65	50	50	NUM
alkej-16	235	66	60	60	NUM
alkej-16	235	67	70	70	NUM
alkej-16	235	68	80	80	NUM
alkej-16	235	69	90	90	NUM
alkej-16	235	70	100	100	NUM
alkej-16	235	71	110	110	NUM
alkej-16	235	72	120	120	NUM
alkej-16	236	1	k	k	NOUN
alkej-16	236	2	yp	yp	PROPN
alkej-16	237	1	[	[	X
alkej-16	237	2	k	k	X
alkej-16	237	3	]	]	X
alkej-16	237	4	&	&	CCONJ
alkej-16	237	5	yd	yd	ADP
alkej-16	237	6	es	es	X
alkej-16	237	7	[	[	X
alkej-16	237	8	k	k	X
alkej-16	237	9	]	]	X
alkej-16	237	10	fig	fig	NOUN
alkej-16	237	11	(	(	PUNCT
alkej-16	237	12	11	11	NUM
alkej-16	237	13	):	):	PUNCT
alkej-16	237	14	the	the	DET
alkej-16	237	15	response	response	NOUN
alkej-16	237	16	of	of	ADP
alkej-16	237	17	the	the	DET
alkej-16	237	18	plant	plant	NOUN
alkej-16	237	19	with	with	ADP
alkej-16	237	20	the	the	DET
alkej-16	237	21	set	set	NOUN
alkej-16	237	22	point	point	NOUN
alkej-16	237	23	plant	plant	NOUN
alkej-16	237	24	response	response	NOUN
alkej-16	237	25	----set	----set	PROPN
alkej-16	237	26	point	point	NOUN
alkej-16	237	27	-1	-1	PUNCT
alkej-16	238	1	-0.5	-0.5	X
alkej-16	238	2	0	0	NUM
alkej-16	238	3	0.5	0.5	NUM
alkej-16	238	4	1	1	NUM
alkej-16	238	5	0	0	NUM
alkej-16	238	6	10	10	NUM
alkej-16	238	7	20	20	NUM
alkej-16	238	8	30	30	NUM
alkej-16	238	9	40	40	NUM
alkej-16	238	10	50	50	NUM
alkej-16	238	11	60	60	NUM
alkej-16	238	12	70	70	NUM
alkej-16	238	13	80	80	NUM
alkej-16	238	14	90	90	NUM
alkej-16	238	15	100	100	NUM
alkej-16	238	16	110	110	NUM
alkej-16	238	17	120	120	NUM
alkej-16	238	18	k	k	NOUN
alkej-16	238	19	yp	yp	PROPN
alkej-16	239	1	[	[	X
alkej-16	239	2	k	k	X
alkej-16	239	3	]	]	X
alkej-16	239	4	&	&	CCONJ
alkej-16	239	5	ym	ym	X
alkej-16	240	1	[	[	X
alkej-16	240	2	k	k	X
alkej-16	240	3	]	]	X
alkej-16	240	4	fig	fig	NOUN
alkej-16	240	5	(	(	PUNCT
alkej-16	240	6	12	12	NUM
alkej-16	240	7	):	):	PUNCT
alkej-16	240	8	the	the	DET
alkej-16	240	9	response	response	NOUN
alkej-16	240	10	of	of	ADP
alkej-16	240	11	the	the	DET
alkej-16	240	12	plant	plant	NOUN
alkej-16	240	13	&	&	CCONJ
alkej-16	240	14	the	the	DET
alkej-16	240	15	response	response	NOUN
alkej-16	240	16	of	of	ADP
alkej-16	240	17	the	the	DET
alkej-16	240	18	model	model	NOUN
alkej-16	240	19	plant	plant	NOUN
alkej-16	240	20	response	response	NOUN
alkej-16	240	21	-----model	-----model	ADP
alkej-16	240	22	response	response	NOUN
alkej-16	240	23	-2.5	-2.5	INTJ
alkej-16	240	24	-2	-2	INTJ
alkej-16	240	25	-1.5	-1.5	NUM
alkej-16	240	26	-1	-1	PROPN
alkej-16	241	1	-0.5	-0.5	X
alkej-16	241	2	0	0	NUM
alkej-16	241	3	0.5	0.5	NUM
alkej-16	241	4	1	1	NUM
alkej-16	241	5	1.5	1.5	NUM
alkej-16	241	6	2	2	NUM
alkej-16	241	7	2.5	2.5	NUM
alkej-16	241	8	0	0	NUM
alkej-16	241	9	10	10	NUM
alkej-16	241	10	20	20	NUM
alkej-16	241	11	30	30	NUM
alkej-16	241	12	40	40	NUM
alkej-16	241	13	50	50	NUM
alkej-16	241	14	60	60	NUM
alkej-16	241	15	70	70	NUM
alkej-16	241	16	80	80	NUM
alkej-16	241	17	90	90	NUM
alkej-16	241	18	100	100	NUM
alkej-16	241	19	110	110	NUM
alkej-16	241	20	120	120	NUM
alkej-16	242	1	k	k	NOUN
alkej-16	242	2	k	k	PROPN
alkej-16	242	3	p	p	X
alkej-16	242	4	fig	fig	NOUN
alkej-16	242	5	(	(	PUNCT
alkej-16	242	6	13	13	NUM
alkej-16	242	7	-	-	PUNCT
alkej-16	242	8	a	a	NOUN
alkej-16	242	9	):	):	PUNCT
alkej-16	242	10	kp	kp	PROPN
alkej-16	242	11	gain	gain	NOUN
alkej-16	242	12	of	of	ADP
alkej-16	242	13	pid	pid	NOUN
alkej-16	242	14	controller	controller	NOUN
alkej-16	242	15	ahmed	ahmed	PROPN
alkej-16	242	16	sabah	sabah	PROPN
alkej-16	242	17	abdul	abdul	PROPN
alkej-16	242	18	ameer	ameer	PROPN
alkej-16	242	19	/al	/al	PROPN
alkej-16	242	20	khwarizmi	khwarizmi	PROPN
alkej-16	242	21	engineering	engineering	PROPN
alkej-16	242	22	journal	journal	PROPN
alkej-16	242	23	,	,	PUNCT
alkej-16	242	24	vol	vol	NOUN
alkej-16	242	25	.	.	PROPN
alkej-16	242	26	1	1	NUM
alkej-16	242	27	,	,	PUNCT
alkej-16	242	28	no	no	INTJ
alkej-16	242	29	.	.	NOUN
alkej-16	242	30	1	1	NUM
alkej-16	242	31	,	,	PUNCT
alkej-16	242	32	pp	pp	ADV
alkej-16	242	33	1	1	NUM
alkej-16	242	34	-	-	SYM
alkej-16	242	35	18	18	NUM
alkej-16	242	36	(	(	PUNCT
alkej-16	242	37	2005	2005	NUM
alkej-16	242	38	)	)	PUNCT
alkej-16	242	39	١٥	١٥	NUM
alkej-16	242	40	fig	fig	NOUN
alkej-16	242	41	(	(	PUNCT
alkej-16	242	42	13	13	NUM
alkej-16	242	43	-	-	PUNCT
alkej-16	242	44	b	b	NOUN
alkej-16	242	45	):	):	PUNCT
alkej-16	242	46	ki	ki	PROPN
alkej-16	242	47	gain	gain	NOUN
alkej-16	242	48	of	of	ADP
alkej-16	242	49	pid	pid	NOUN
alkej-16	242	50	controller	controller	NOUN
alkej-16	242	51	-5.5	-5.5	PUNCT
alkej-16	242	52	-4.5	-4.5	PRON
alkej-16	242	53	-3.5	-3.5	INTJ
alkej-16	242	54	-2.5	-2.5	ADJ
alkej-16	242	55	-1.5	-1.5	PUNCT
alkej-16	242	56	-0.5	-0.5	PROPN
alkej-16	242	57	0.5	0.5	NUM
alkej-16	242	58	1.5	1.5	NUM
alkej-16	242	59	2.5	2.5	NUM
alkej-16	242	60	3.5	3.5	NUM
alkej-16	242	61	4.5	4.5	NUM
alkej-16	242	62	5.5	5.5	NUM
alkej-16	242	63	0	0	NUM
alkej-16	242	64	10	10	NUM
alkej-16	242	65	20	20	NUM
alkej-16	242	66	30	30	NUM
alkej-16	242	67	40	40	NUM
alkej-16	242	68	50	50	NUM
alkej-16	242	69	60	60	NUM
alkej-16	242	70	70	70	NUM
alkej-16	242	71	80	80	NUM
alkej-16	242	72	90	90	NUM
alkej-16	242	73	100	100	NUM
alkej-16	242	74	110	110	NUM
alkej-16	242	75	120	120	NUM
alkej-16	243	1	k	k	NOUN
alkej-16	243	2	k	k	PROPN
alkej-16	244	1	i	i	PRON
alkej-16	244	2	-2.5	-2.5	VERB
alkej-16	244	3	-2	-2	INTJ
alkej-16	244	4	-1.5	-1.5	NUM
alkej-16	244	5	-1	-1	PROPN
alkej-16	245	1	-0.5	-0.5	X
alkej-16	245	2	0	0	NUM
alkej-16	245	3	0.5	0.5	NUM
alkej-16	245	4	1	1	NUM
alkej-16	245	5	1.5	1.5	NUM
alkej-16	245	6	2	2	NUM
alkej-16	245	7	2.5	2.5	NUM
alkej-16	245	8	0	0	NUM
alkej-16	245	9	10	10	NUM
alkej-16	245	10	20	20	NUM
alkej-16	245	11	30	30	NUM
alkej-16	245	12	40	40	NUM
alkej-16	245	13	50	50	NUM
alkej-16	245	14	60	60	NUM
alkej-16	245	15	70	70	NUM
alkej-16	245	16	80	80	NUM
alkej-16	245	17	90	90	NUM
alkej-16	245	18	100	100	NUM
alkej-16	245	19	110	110	NUM
alkej-16	245	20	120	120	NUM
alkej-16	245	21	k	k	NOUN
alkej-16	245	22	k	k	PUNCT
alkej-16	245	23	d	d	X
alkej-16	245	24	fig	fig	NOUN
alkej-16	245	25	(	(	PUNCT
alkej-16	245	26	13	13	NUM
alkej-16	245	27	-	-	SYM
alkej-16	245	28	c	c	NOUN
alkej-16	245	29	):	):	PUNCT
alkej-16	245	30	kd	kd	PROPN
alkej-16	245	31	gain	gain	NOUN
alkej-16	245	32	of	of	ADP
alkej-16	245	33	pid	pid	NOUN
alkej-16	245	34	controller	controller	NOUN
alkej-16	245	35	-1	-1	PROPN
alkej-16	245	36	-0.8	-0.8	PROPN
alkej-16	245	37	-0.6	-0.6	PROPN
alkej-16	245	38	-0.4	-0.4	X
alkej-16	245	39	-0.2	-0.2	PROPN
alkej-16	245	40	0	0	NUM
alkej-16	245	41	0.2	0.2	NUM
alkej-16	245	42	0.4	0.4	NUM
alkej-16	245	43	0.6	0.6	NUM
alkej-16	245	44	0.8	0.8	NUM
alkej-16	245	45	1	1	NUM
alkej-16	245	46	0	0	NUM
alkej-16	245	47	10	10	NUM
alkej-16	245	48	20	20	NUM
alkej-16	245	49	30	30	NUM
alkej-16	245	50	40	40	NUM
alkej-16	245	51	50	50	NUM
alkej-16	245	52	60	60	NUM
alkej-16	245	53	70	70	NUM
alkej-16	245	54	80	80	NUM
alkej-16	245	55	90	90	NUM
alkej-16	245	56	100	100	NUM
alkej-16	245	57	110	110	NUM
alkej-16	245	58	120	120	NUM
alkej-16	245	59	k	k	NOUN
alkej-16	245	60	u	u	PROPN
alkej-16	246	1	[	[	X
alkej-16	246	2	k	k	X
alkej-16	246	3	]	]	X
alkej-16	246	4	fig	fig	NOUN
alkej-16	246	5	(	(	PUNCT
alkej-16	246	6	14	14	NUM
alkej-16	246	7	):	):	PUNCT
alkej-16	246	8	the	the	DET
alkej-16	246	9	control	control	NOUN
alkej-16	246	10	signal	signal	NOUN
alkej-16	246	11	of	of	ADP
alkej-16	246	12	the	the	DET
alkej-16	246	13	pid	pid	NOUN
alkej-16	246	14	controller	controller	NOUN
alkej-16	246	15	ahmed	ahmed	PROPN
alkej-16	246	16	sabah	sabah	PROPN
alkej-16	246	17	abdul	abdul	PROPN
alkej-16	246	18	ameer	ameer	PROPN
alkej-16	246	19	/al	/al	PROPN
alkej-16	246	20	khwarizmi	khwarizmi	PROPN
alkej-16	246	21	engineering	engineering	PROPN
alkej-16	246	22	journal	journal	PROPN
alkej-16	246	23	,	,	PUNCT
alkej-16	246	24	vol	vol	NOUN
alkej-16	246	25	.	.	PROPN
alkej-16	246	26	1	1	NUM
alkej-16	246	27	,	,	PUNCT
alkej-16	246	28	no	no	INTJ
alkej-16	246	29	.	.	NOUN
alkej-16	246	30	1	1	NUM
alkej-16	246	31	,	,	PUNCT
alkej-16	246	32	pp	pp	ADV
alkej-16	246	33	1	1	NUM
alkej-16	246	34	-	-	SYM
alkej-16	246	35	18	18	NUM
alkej-16	246	36	(	(	PUNCT
alkej-16	246	37	2005	2005	NUM
alkej-16	246	38	)	)	PUNCT
alkej-16	246	39	١٦	١٦	NUM
alkej-16	246	40	respectively	respectively	ADV
alkej-16	246	41	.	.	PUNCT
alkej-16	247	1	and	and	CCONJ
alkej-16	247	2	the	the	DET
alkej-16	247	3	feedback	feedback	NOUN
alkej-16	247	4	control	control	NOUN
alkej-16	247	5	action	action	NOUN
alkej-16	247	6	as	as	SCONJ
alkej-16	247	7	shown	show	VERB
alkej-16	247	8	in	in	ADP
alkej-16	247	9	fig14	fig14	NOUN
alkej-16	247	10	.	.	PUNCT
alkej-16	248	1	5conclusion	5conclusion	NUM
alkej-16	248	2	:	:	PUNCT
alkej-16	248	3	the	the	DET
alkej-16	248	4	structure	structure	NOUN
alkej-16	248	5	of	of	ADP
alkej-16	248	6	the	the	DET
alkej-16	248	7	neural	neural	ADJ
alkej-16	248	8	controller	controller	NOUN
alkej-16	248	9	with	with	ADP
alkej-16	248	10	an	an	DET
alkej-16	248	11	identifier	identifier	NOUN
alkej-16	248	12	based	base	VERB
alkej-16	248	13	on	on	ADP
alkej-16	248	14	neural	neural	ADJ
alkej-16	248	15	narma	narma	NOUN
alkej-16	248	16	-	-	PUNCT
alkej-16	248	17	l2	l2	NOUN
alkej-16	248	18	model	model	NOUN
alkej-16	248	19	that	that	PRON
alkej-16	248	20	is	be	AUX
alkej-16	248	21	learned	learn	VERB
alkej-16	248	22	offline	offline	ADJ
alkej-16	248	23	with	with	ADP
alkej-16	248	24	two	two	NUM
alkej-16	248	25	configuration	configuration	NOUN
alkej-16	248	26	serialparallel	serialparallel	NOUN
alkej-16	248	27	&	&	CCONJ
alkej-16	248	28	parallel	parallel	ADJ
alkej-16	248	29	and	and	CCONJ
alkej-16	248	30	applied	apply	VERB
alkej-16	248	31	the	the	DET
alkej-16	248	32	algorithm	algorithm	NOUN
alkej-16	248	33	of	of	ADP
alkej-16	248	34	the	the	DET
alkej-16	248	35	self	self	NOUN
alkej-16	248	36	-	-	PUNCT
alkej-16	248	37	tuning	tune	VERB
alkej-16	248	38	pid	pid	NOUN
alkej-16	248	39	neural	neural	ADJ
alkej-16	248	40	controller	controller	NOUN
alkej-16	248	41	as	as	ADP
alkej-16	248	42	the	the	DET
alkej-16	248	43	proposed	propose	VERB
alkej-16	248	44	structure	structure	NOUN
alkej-16	248	45	of	of	ADP
alkej-16	248	46	controller	controller	NOUN
alkej-16	248	47	and	and	CCONJ
alkej-16	248	48	successfully	successfully	ADV
alkej-16	248	49	simulated	simulate	VERB
alkej-16	248	50	to	to	ADP
alkej-16	248	51	nonlinear	nonlinear	ADJ
alkej-16	248	52	system	system	NOUN
alkej-16	248	53	as	as	ADP
alkej-16	248	54	the	the	DET
alkej-16	248	55	example	example	NOUN
alkej-16	248	56	.	.	PUNCT
alkej-16	249	1	using	use	VERB
alkej-16	249	2	neural	neural	ADJ
alkej-16	249	3	narma	narma	NOUN
alkej-16	249	4	-	-	PUNCT
alkej-16	249	5	l2	l2	NOUN
alkej-16	249	6	model	model	NOUN
alkej-16	249	7	as	as	ADP
alkej-16	249	8	a	a	DET
alkej-16	249	9	nonlinear	nonlinear	ADJ
alkej-16	249	10	model	model	NOUN
alkej-16	249	11	of	of	ADP
alkej-16	249	12	the	the	DET
alkej-16	249	13	plant	plant	NOUN
alkej-16	249	14	provides	provide	VERB
alkej-16	249	15	a	a	DET
alkej-16	249	16	simple	simple	ADJ
alkej-16	249	17	check	check	NOUN
alkej-16	249	18	on	on	ADP
alkej-16	249	19	the	the	DET
alkej-16	249	20	model	model	NOUN
alkej-16	249	21	jacobain	jacobain	NOUN
alkej-16	249	22	,	,	PUNCT
alkej-16	249	23	which	which	PRON
alkej-16	249	24	appears	appear	VERB
alkej-16	249	25	to	to	PART
alkej-16	249	26	be	be	AUX
alkej-16	249	27	of	of	ADP
alkej-16	249	28	critical	critical	ADJ
alkej-16	249	29	importance	importance	NOUN
alkej-16	249	30	as	as	SCONJ
alkej-16	249	31	it	it	PRON
alkej-16	249	32	is	be	AUX
alkej-16	249	33	used	use	VERB
alkej-16	249	34	for	for	ADP
alkej-16	249	35	the	the	DET
alkej-16	249	36	feedback	feedback	NOUN
alkej-16	249	37	controller	controller	NOUN
alkej-16	249	38	.	.	PUNCT
alkej-16	250	1	the	the	DET
alkej-16	250	2	on	on	ADP
alkej-16	250	3	-	-	PUNCT
alkej-16	250	4	line	line	NOUN
alkej-16	250	5	identifier	identifier	NOUN
alkej-16	250	6	narma	narma	NOUN
alkej-16	250	7	-	-	PUNCT
alkej-16	250	8	l2	l2	NOUN
alkej-16	250	9	model	model	NOUN
alkej-16	250	10	of	of	ADP
alkej-16	250	11	the	the	DET
alkej-16	250	12	plant	plant	NOUN
alkej-16	250	13	is	be	AUX
alkej-16	250	14	used	use	VERB
alkej-16	250	15	to	to	PART
alkej-16	250	16	updated	update	VERB
alkej-16	250	17	of	of	ADP
alkej-16	250	18	the	the	DET
alkej-16	250	19	weights	weight	NOUN
alkej-16	250	20	of	of	ADP
alkej-16	250	21	the	the	DET
alkej-16	250	22	identifier	identifier	NOUN
alkej-16	250	23	by	by	ADP
alkej-16	250	24	using	use	VERB
alkej-16	250	25	(	(	PUNCT
alkej-16	250	26	bpa	bpa	NOUN
alkej-16	250	27	)	)	PUNCT
alkej-16	250	28	in	in	ADP
alkej-16	250	29	order	order	NOUN
alkej-16	250	30	to	to	PART
alkej-16	250	31	guarantee	guarantee	VERB
alkej-16	250	32	that	that	PRON
alkej-16	250	33	model	model	NOUN
alkej-16	250	34	output	output	NOUN
alkej-16	250	35	approaches	approach	VERB
alkej-16	250	36	the	the	DET
alkej-16	250	37	actual	actual	ADJ
alkej-16	250	38	output	output	NOUN
alkej-16	250	39	.	.	PUNCT
alkej-16	251	1	using	use	VERB
alkej-16	251	2	pid	pid	NUM
alkej-16	251	3	feedback	feedback	NOUN
alkej-16	251	4	controller	controller	NOUN
alkej-16	251	5	with	with	ADP
alkej-16	251	6	selftuning	selftune	VERB
alkej-16	251	7	neural	neural	NOUN
alkej-16	251	8	to	to	PART
alkej-16	251	9	adjust	adjust	VERB
alkej-16	251	10	the	the	DET
alkej-16	251	11	parameters	parameter	NOUN
alkej-16	251	12	of	of	ADP
alkej-16	251	13	the	the	DET
alkej-16	251	14	controller	controller	NOUN
alkej-16	251	15	.	.	PUNCT
alkej-16	252	1	so	so	ADV
alkej-16	252	2	that	that	SCONJ
alkej-16	252	3	,	,	PUNCT
alkej-16	252	4	the	the	DET
alkej-16	252	5	output	output	NOUN
alkej-16	252	6	of	of	ADP
alkej-16	252	7	the	the	DET
alkej-16	252	8	plant	plant	NOUN
alkej-16	252	9	follows	follow	VERB
alkej-16	252	10	the	the	DET
alkej-16	252	11	output	output	NOUN
alkej-16	252	12	of	of	ADP
alkej-16	252	13	the	the	DET
alkej-16	252	14	predefined	predefine	VERB
alkej-16	252	15	desired	desire	VERB
alkej-16	252	16	input	input	NOUN
alkej-16	252	17	and	and	CCONJ
alkej-16	252	18	(	(	PUNCT
alkej-16	252	19	bp	bp	PROPN
alkej-16	252	20	)	)	PUNCT
alkej-16	252	21	algorithm	algorithm	NOUN
alkej-16	252	22	is	be	AUX
alkej-16	252	23	used	use	VERB
alkej-16	252	24	to	to	PART
alkej-16	252	25	learn	learn	VERB
alkej-16	252	26	the	the	DET
alkej-16	252	27	model	model	NOUN
alkej-16	252	28	.	.	PUNCT
alkej-16	253	1	the	the	DET
alkej-16	253	2	proposed	propose	VERB
alkej-16	253	3	control	control	NOUN
alkej-16	253	4	structure	structure	NOUN
alkej-16	253	5	has	have	AUX
alkej-16	253	6	shown	show	VERB
alkej-16	253	7	the	the	DET
alkej-16	253	8	ability	ability	NOUN
alkej-16	253	9	to	to	PART
alkej-16	253	10	minimize	minimize	VERB
alkej-16	253	11	the	the	DET
alkej-16	253	12	error	error	NOUN
alkej-16	253	13	between	between	ADP
alkej-16	253	14	the	the	DET
alkej-16	253	15	desired	desire	VERB
alkej-16	253	16	output	output	NOUN
alkej-16	253	17	and	and	CCONJ
alkej-16	253	18	the	the	DET
alkej-16	253	19	actual	actual	ADJ
alkej-16	253	20	output	output	NOUN
alkej-16	253	21	of	of	ADP
alkej-16	253	22	the	the	DET
alkej-16	253	23	plant	plant	NOUN
alkej-16	253	24	as	as	ADV
alkej-16	253	25	well	well	ADV
alkej-16	253	26	as	as	ADP
alkej-16	253	27	the	the	DET
alkej-16	253	28	control	control	NOUN
alkej-16	253	29	action	action	NOUN
alkej-16	253	30	,	,	PUNCT
alkej-16	253	31	excellent	excellent	ADJ
alkej-16	253	32	set	set	NOUN
alkej-16	253	33	point	point	NOUN
alkej-16	253	34	tracking	tracking	NOUN
alkej-16	253	35	,	,	PUNCT
alkej-16	253	36	as	as	SCONJ
alkej-16	253	37	it	it	PRON
alkej-16	253	38	was	be	AUX
alkej-16	253	39	clear	clear	ADJ
alkej-16	253	40	when	when	SCONJ
alkej-16	253	41	applied	apply	VERB
alkej-16	253	42	to	to	ADP
alkej-16	253	43	the	the	DET
alkej-16	253	44	example	example	NOUN
alkej-16	253	45	.	.	PUNCT
alkej-16	254	1	the	the	DET
alkej-16	254	2	simulation	simulation	NOUN
alkej-16	254	3	example	example	NOUN
alkej-16	254	4	in	in	ADP
alkej-16	254	5	this	this	DET
alkej-16	254	6	paper	paper	NOUN
alkej-16	254	7	is	be	AUX
alkej-16	254	8	implemented	implement	VERB
alkej-16	254	9	using	use	VERB
alkej-16	254	10	turbo	turbo	NOUN
alkej-16	254	11	c++	c++	NOUN
alkej-16	254	12	programming	programming	NOUN
alkej-16	254	13	language	language	NOUN
alkej-16	254	14	together	together	ADV
alkej-16	254	15	with	with	ADP
alkej-16	254	16	microsoft	microsoft	PROPN
alkej-16	254	17	excel	excel	PROPN
alkej-16	254	18	.	.	PUNCT
alkej-16	255	1	references	reference	NOUN
alkej-16	255	2	1	1	NUM
alkej-16	255	3	.	.	PUNCT
alkej-16	255	4	porter	porter	PROPN
alkej-16	255	5	b.	b.	PROPN
alkej-16	255	6	&	&	CCONJ
alkej-16	255	7	jones	jones	PROPN
alkej-16	256	1	a.h	a.h	PROPN
alkej-16	256	2	.	.	PROPN
alkej-16	256	3	,	,	PUNCT
alkej-16	256	4	“	"	PUNCT
alkej-16	256	5	design	design	NOUN
alkej-16	256	6	of	of	ADP
alkej-16	256	7	tunable	tunable	ADJ
alkej-16	256	8	digital	digital	ADJ
alkej-16	256	9	set	set	NOUN
alkej-16	256	10	-	-	PUNCT
alkej-16	256	11	point	point	NOUN
alkej-16	256	12	tracking	tracking	NOUN
alkej-16	256	13	pi	pi	NOUN
alkej-16	256	14	controller	controller	NOUN
alkej-16	256	15	using	use	VERB
alkej-16	256	16	step	step	NOUN
alkej-16	256	17	response	response	NOUN
alkej-16	256	18	matrices	matrix	NOUN
alkej-16	256	19	for	for	ADP
alkej-16	256	20	gas	gas	NOUN
alkej-16	256	21	turbain	turbain	NOUN
alkej-16	256	22	”	"	PUNCT
alkej-16	256	23	alaa	alaa	PROPN
alkej-16	256	24	guidance	guidance	PROPN
alkej-16	256	25	,	,	PUNCT
alkej-16	256	26	naving	naving	NOUN
alkej-16	256	27	–	–	PUNCT
alkej-16	256	28	1986	1986	NUM
alkej-16	256	29	.	.	PUNCT
alkej-16	257	1	nomenclature	nomenclature	ADJ
alkej-16	257	2	abbreviations	abbreviation	NOUN
alkej-16	257	3	2	2	NUM
alkej-16	257	4	.	.	X
alkej-16	257	5	porter	porter	PROPN
alkej-16	257	6	b.	b.	PROPN
alkej-16	257	7	&	&	CCONJ
alkej-16	257	8	jones	jones	PROPN
alkej-16	258	1	a.h	a.h	PROPN
alkej-16	258	2	.	.	PROPN
alkej-16	258	3	,	,	PUNCT
alkej-16	258	4	“	"	PUNCT
alkej-16	258	5	genetic	genetic	ADJ
alkej-16	258	6	tuning	tuning	NOUN
alkej-16	258	7	of	of	ADP
alkej-16	258	8	digital	digital	ADJ
alkej-16	258	9	pid	pid	NOUN
alkej-16	258	10	controllers	controller	NOUN
alkej-16	258	11	”	"	PUNCT
alkej-16	258	12	electronics	electronic	NOUN
alkej-16	258	13	letters	letter	NOUN
alkej-16	258	14	:	:	PUNCT
alkej-16	258	15	vol	vol	NOUN
alkej-16	258	16	.	.	PROPN
alkej-16	258	17	28	28	NUM
alkej-16	258	18	,	,	PUNCT
alkej-16	258	19	pp	pp	ADV
alkej-16	258	20	843	843	NUM
alkej-16	258	21	-	-	PUNCT
alkej-16	258	22	844	844	NUM
alkej-16	258	23	,	,	PUNCT
alkej-16	258	24	1992	1992	NUM
alkej-16	258	25	.	.	PUNCT
alkej-16	259	1	ase	ase	NOUN
alkej-16	259	2	average	average	ADJ
alkej-16	259	3	system	system	NOUN
alkej-16	259	4	error	error	NOUN
alkej-16	259	5	bpa	bpa	NOUN
alkej-16	259	6	back	back	ADJ
alkej-16	259	7	propagation	propagation	NOUN
alkej-16	259	8	algorithm	algorithm	NOUN
alkej-16	259	9	fbnc	fbnc	NOUN
alkej-16	259	10	feedback	feedback	NOUN
alkej-16	259	11	neural	neural	ADJ
alkej-16	259	12	controller	controller	NOUN
alkej-16	259	13	ffnc	ffnc	PROPN
alkej-16	259	14	feedforward	feedforward	PROPN
alkej-16	259	15	neural	neural	ADJ
alkej-16	259	16	controller	controller	NOUN
alkej-16	259	17	narma	narma	PROPN
alkej-16	259	18	nonlinear	nonlinear	ADJ
alkej-16	259	19	auto	auto	NOUN
alkej-16	259	20	regressive	regressive	ADJ
alkej-16	259	21	moving	move	VERB
alkej-16	259	22	average	average	ADJ
alkej-16	259	23	pid	pid	NOUN
alkej-16	259	24	proportional	proportional	ADJ
alkej-16	259	25	integral	integral	ADJ
alkej-16	259	26	derivative	derivative	ADJ
alkej-16	259	27	siso	siso	NOUN
alkej-16	259	28	single	single	ADJ
alkej-16	259	29	-	-	PUNCT
alkej-16	259	30	input	input	NOUN
alkej-16	259	31	single	single	ADJ
alkej-16	259	32	-	-	PUNCT
alkej-16	259	33	output	output	NOUN
alkej-16	259	34	stc	stc	NOUN
alkej-16	259	35	self	self	NOUN
alkej-16	259	36	-	-	PUNCT
alkej-16	259	37	tuning	tune	VERB
alkej-16	259	38	control	control	NOUN
alkej-16	259	39	symbol	symbol	NOUN
alkej-16	259	40	description	description	NOUN
alkej-16	259	41	e	e	NOUN
alkej-16	259	42	summation	summation	NOUN
alkej-16	259	43	of	of	ADP
alkej-16	259	44	error	error	NOUN
alkej-16	259	45	e	e	NOUN
alkej-16	259	46	the	the	DET
alkej-16	259	47	error	error	NOUN
alkej-16	259	48	between	between	ADP
alkej-16	259	49	reference	reference	NOUN
alkej-16	259	50	input	input	NOUN
alkej-16	259	51	and	and	CCONJ
alkej-16	259	52	the	the	DET
alkej-16	259	53	model	model	NOUN
alkej-16	259	54	output	output	NOUN
alkej-16	259	55	]	]	X
alkej-16	260	1	[	[	X
alkej-16	260	2	2],[1	2],[1	NUM
alkej-16	260	3	]	]	PUNCT
alkej-16	260	4	,	,	PUNCT
alkej-16	261	1	[	[	X
alkej-16	261	2	]	]	X
alkej-16	261	3	,	,	PUNCT
alkej-16	261	4	[	[	PUNCT
alkej-16	261	5	−−	−−	NOUN
alkej-16	261	6	−−	−−	PROPN
alkej-16	261	7	∧∧	∧∧	PROPN
alkej-16	261	8	nn	nn	PROPN
alkej-16	261	9	gf	gf	PROPN
alkej-16	261	10	neural	neural	ADJ
alkej-16	261	11	input	input	NOUN
alkej-16	261	12	-	-	PUNCT
alkej-16	261	13	output	output	NOUN
alkej-16	261	14	mapping	mapping	NOUN
alkej-16	261	15	functions	function	NOUN
alkej-16	261	16	h	h	NOUN
alkej-16	261	17	sigmoidal	sigmoidal	NOUN
alkej-16	261	18	activation	activation	NOUN
alkej-16	261	19	function	function	NOUN
alkej-16	261	20	of	of	ADP
alkej-16	261	21	the	the	DET
alkej-16	261	22	hidden	hide	VERB
alkej-16	261	23	nodes	node	NOUN
alkej-16	261	24	k	k	X
alkej-16	261	25	discrete	discrete	ADJ
alkej-16	261	26	time	time	NOUN
alkej-16	261	27	instant	instant	ADJ
alkej-16	261	28	l	l	PROPN
alkej-16	261	29	linear	linear	ADJ
alkej-16	261	30	activation	activation	NOUN
alkej-16	261	31	function	function	NOUN
alkej-16	261	32	of	of	ADP
alkej-16	261	33	the	the	DET
alkej-16	261	34	output	output	NOUN
alkej-16	261	35	node	node	NOUN
alkej-16	261	36	n	n	CCONJ
alkej-16	261	37	plant	plant	NOUN
alkej-16	261	38	order	order	NOUN
alkej-16	261	39	jnet	jnet	NOUN
alkej-16	261	40	the	the	DET
alkej-16	261	41	weighted	weighted	ADJ
alkej-16	261	42	sum	sum	NOUN
alkej-16	261	43	of	of	ADP
alkej-16	261	44	the	the	DET
alkej-16	261	45	inputs	input	NOUN
alkej-16	261	46	of	of	ADP
alkej-16	261	47	the	the	DET
alkej-16	261	48	node	node	PROPN
alkej-16	261	49	j	j	PROPN
alkej-16	261	50	in	in	ADP
alkej-16	261	51	the	the	DET
alkej-16	261	52	hidden	hide	VERB
alkej-16	261	53	layer	layer	NOUN
alkej-16	261	54	neto	neto	VERB
alkej-16	261	55	the	the	DET
alkej-16	261	56	weighted	weighted	ADJ
alkej-16	261	57	sum	sum	NOUN
alkej-16	261	58	of	of	ADP
alkej-16	261	59	the	the	DET
alkej-16	261	60	inputs	input	NOUN
alkej-16	261	61	of	of	ADP
alkej-16	261	62	the	the	DET
alkej-16	261	63	output	output	NOUN
alkej-16	261	64	node	node	PROPN
alkej-16	261	65	nh	nh	PROPN
alkej-16	261	66	number	number	NOUN
alkej-16	261	67	of	of	ADP
alkej-16	261	68	nodes	node	NOUN
alkej-16	261	69	in	in	ADP
alkej-16	261	70	hidden	hidden	ADJ
alkej-16	261	71	layer	layer	NOUN
alkej-16	261	72	ni	ni	NOUN
alkej-16	261	73	number	number	NOUN
alkej-16	261	74	of	of	ADP
alkej-16	261	75	nodes	node	NOUN
alkej-16	261	76	in	in	ADP
alkej-16	261	77	input	input	NOUN
alkej-16	261	78	layer	layer	NOUN
alkej-16	261	79	u	u	NOUN
alkej-16	261	80	manipulated	manipulate	VERB
alkej-16	261	81	input	input	NOUN
alkej-16	261	82	v	v	ADP
alkej-16	261	83	weight	weight	NOUN
alkej-16	261	84	matrix	matrix	NOUN
alkej-16	261	85	between	between	ADP
alkej-16	261	86	the	the	DET
alkej-16	261	87	input	input	NOUN
alkej-16	261	88	and	and	CCONJ
alkej-16	261	89	the	the	DET
alkej-16	261	90	hidden	hide	VERB
alkej-16	261	91	layer	layer	NOUN
alkej-16	261	92	w	w	ADP
alkej-16	261	93	weight	weight	NOUN
alkej-16	261	94	matrix	matrix	NOUN
alkej-16	261	95	between	between	ADP
alkej-16	261	96	the	the	DET
alkej-16	261	97	hidden	hidden	ADJ
alkej-16	261	98	and	and	CCONJ
alkej-16	261	99	the	the	DET
alkej-16	261	100	output	output	NOUN
alkej-16	261	101	layer	layer	NOUN
alkej-16	261	102	x	x	PUNCT
alkej-16	261	103	the	the	DET
alkej-16	261	104	input	input	NOUN
alkej-16	261	105	vector	vector	NOUN
alkej-16	261	106	for	for	ADP
alkej-16	261	107	the	the	DET
alkej-16	261	108	input	input	NOUN
alkej-16	261	109	layer	layer	NOUN
alkej-16	261	110	desy	desy	PROPN
alkej-16	261	111	the	the	DET
alkej-16	261	112	desired	desire	VERB
alkej-16	261	113	output	output	NOUN
alkej-16	261	114	py	py	PROPN
alkej-16	261	115	plant	plant	NOUN
alkej-16	261	116	output	output	NOUN
alkej-16	261	117	my	my	PRON
alkej-16	261	118	model	model	NOUN
alkej-16	261	119	output	output	NOUN
alkej-16	261	120	p	p	NOUN
alkej-16	261	121	number	number	NOUN
alkej-16	261	122	of	of	ADP
alkej-16	261	123	patterns	pattern	NOUN
alkej-16	261	124	in	in	ADP
alkej-16	261	125	the	the	DET
alkej-16	261	126	training	training	NOUN
alkej-16	261	127	set	set	VERB
alkej-16	261	128	η	η	PROPN
alkej-16	261	129	learning	learning	NOUN
alkej-16	261	130	rate	rate	NOUN
alkej-16	261	131	of	of	ADP
alkej-16	261	132	the	the	DET
alkej-16	261	133	neural	neural	ADJ
alkej-16	261	134	network	network	NOUN
alkej-16	262	1	ahmed	ahmed	PROPN
alkej-16	262	2	sabah	sabah	PROPN
alkej-16	262	3	abdul	abdul	PROPN
alkej-16	262	4	ameer	ameer	PROPN
alkej-16	262	5	/al	/al	PROPN
alkej-16	262	6	khwarizmi	khwarizmi	PROPN
alkej-16	262	7	engineering	engineering	PROPN
alkej-16	262	8	journal	journal	PROPN
alkej-16	262	9	,	,	PUNCT
alkej-16	262	10	vol	vol	NOUN
alkej-16	262	11	.	.	PROPN
alkej-16	262	12	1	1	NUM
alkej-16	262	13	,	,	PUNCT
alkej-16	262	14	no	no	INTJ
alkej-16	262	15	.	.	NOUN
alkej-16	262	16	1	1	NUM
alkej-16	262	17	,	,	PUNCT
alkej-16	262	18	pp	pp	ADV
alkej-16	262	19	1	1	NUM
alkej-16	262	20	-	-	SYM
alkej-16	262	21	18	18	NUM
alkej-16	262	22	(	(	PUNCT
alkej-16	262	23	2005	2005	NUM
alkej-16	262	24	)	)	PUNCT
alkej-16	262	25	١٧	١٧	NUM
alkej-16	262	26	3	3	NUM
alkej-16	262	27	.	.	PUNCT
alkej-16	263	1	patterson	patterson	PROPN
alkej-16	263	2	d.w	d.w	PROPN
alkej-16	263	3	.	.	PUNCT
alkej-16	264	1	“	"	PUNCT
alkej-16	264	2	artificial	artificial	ADJ
alkej-16	264	3	neural	neural	ADJ
alkej-16	264	4	networks	network	NOUN
alkej-16	264	5	,	,	PUNCT
alkej-16	264	6	theory	theory	NOUN
alkej-16	264	7	&	&	CCONJ
alkej-16	264	8	applications	application	NOUN
alkej-16	264	9	”	"	PUNCT
alkej-16	264	10	prentice	prentice	NOUN
alkej-16	264	11	hall	hall	NOUN
alkej-16	264	12	1996	1996	NUM
alkej-16	264	13	.	.	PUNCT
alkej-16	265	1	4	4	X
alkej-16	265	2	.	.	X
alkej-16	265	3	lightbody	lightbody	PROPN
alkej-16	265	4	g.	g.	PROPN
alkej-16	265	5	and	and	CCONJ
alkej-16	265	6	irwin	irwin	PROPN
alkej-16	265	7	g.w	g.w	PROPN
alkej-16	265	8	.	.	PUNCT
alkej-16	265	9	”	"	PUNCT
alkej-16	266	1	direct	direct	ADJ
alkej-16	266	2	neural	neural	ADJ
alkej-16	266	3	model	model	NOUN
alkej-16	266	4	reference	reference	PROPN
alkej-16	266	5	adaptive	adaptive	PROPN
alkej-16	266	6	control	control	NOUN
alkej-16	266	7	”	"	PUNCT
alkej-16	266	8	ieee	ieee	NOUN
alkej-16	266	9	proce	proce	PROPN
alkej-16	266	10	.	.	PUNCT
alkej-16	267	1	on	on	ADP
alkej-16	267	2	control	control	NOUN
alkej-16	267	3	theory	theory	NOUN
alkej-16	267	4	and	and	CCONJ
alkej-16	267	5	applications	application	NOUN
alkej-16	267	6	,	,	PUNCT
alkej-16	267	7	vol	vol	NOUN
alkej-16	267	8	.	.	PROPN
alkej-16	267	9	142	142	NUM
alkej-16	267	10	;	;	PUNCT
alkej-16	267	11	no	no	INTJ
alkej-16	267	12	.	.	NOUN
alkej-16	267	13	1	1	NUM
alkej-16	267	14	,	,	PUNCT
alkej-16	267	15	pp	pp	ADJ
alkej-16	267	16	.	.	PUNCT
alkej-16	268	1	31	31	NUM
alkej-16	268	2	-	-	SYM
alkej-16	268	3	42	42	NUM
alkej-16	268	4	;	;	PUNCT
alkej-16	268	5	jun	jun	PROPN
alkej-16	268	6	1995	1995	NUM
alkej-16	268	7	.	.	PUNCT
alkej-16	269	1	5	5	NUM
alkej-16	269	2	.	.	PUNCT
alkej-16	269	3	k.	k.	PROPN
alkej-16	269	4	s.	s.	PROPN
alkej-16	269	5	narendra	narendra	PROPN
alkej-16	269	6	and	and	CCONJ
alkej-16	269	7	k.	k.	PROPN
alkej-16	269	8	parthasarathy	parthasarathy	PROPN
alkej-16	269	9	,	,	PUNCT
alkej-16	269	10	“	"	PUNCT
alkej-16	269	11	identification	identification	NOUN
alkej-16	269	12	and	and	CCONJ
alkej-16	269	13	control	control	NOUN
alkej-16	269	14	of	of	ADP
alkej-16	269	15	dynamical	dynamical	ADJ
alkej-16	269	16	systems	system	NOUN
alkej-16	269	17	using	use	VERB
alkej-16	269	18	neural	neural	ADJ
alkej-16	269	19	networks	network	NOUN
alkej-16	269	20	,	,	PUNCT
alkej-16	269	21	”	"	PUNCT
alkej-16	269	22	ieee	ieee	NOUN
alkej-16	269	23	trans	tran	NOUN
alkej-16	269	24	.	.	PUNCT
alkej-16	270	1	neural	neural	ADJ
alkej-16	270	2	networks	network	NOUN
alkej-16	270	3	,	,	PUNCT
alkej-16	270	4	vol	vol	NOUN
alkej-16	270	5	.	.	PUNCT
alkej-16	271	1	1,pp	1,pp	NUM
alkej-16	271	2	.	.	PUNCT
alkej-16	272	1	4	4	NUM
alkej-16	272	2	-	-	SYM
alkej-16	272	3	27	27	NUM
alkej-16	272	4	,	,	PUNCT
alkej-16	272	5	1990	1990	NUM
alkej-16	272	6	.	.	PUNCT
alkej-16	273	1	6	6	NUM
alkej-16	273	2	.	.	PUNCT
alkej-16	273	3	k.	k.	PROPN
alkej-16	273	4	s.	s.	PROPN
alkej-16	273	5	narendra	narendra	PROPN
alkej-16	273	6	and	and	CCONJ
alkej-16	273	7	k.	k.	PROPN
alkej-16	273	8	parthasarathy	parthasarathy	PROPN
alkej-16	273	9	,	,	PUNCT
alkej-16	273	10	“	"	PUNCT
alkej-16	273	11	gradient	gradient	ADJ
alkej-16	273	12	methods	method	NOUN
alkej-16	273	13	for	for	ADP
alkej-16	273	14	the	the	DET
alkej-16	273	15	optimization	optimization	NOUN
alkej-16	273	16	of	of	ADP
alkej-16	273	17	dynamical	dynamical	ADJ
alkej-16	273	18	systems	system	NOUN
alkej-16	273	19	containing	contain	VERB
alkej-16	273	20	neural	neural	ADJ
alkej-16	273	21	networks	network	NOUN
alkej-16	273	22	,	,	PUNCT
alkej-16	273	23	”	"	PUNCT
alkej-16	273	24	ieee	ieee	NOUN
alkej-16	273	25	trans	tran	NOUN
alkej-16	273	26	.	.	PUNCT
alkej-16	274	1	neural	neural	ADJ
alkej-16	274	2	networks	network	NOUN
alkej-16	274	3	,	,	PUNCT
alkej-16	274	4	vol	vol	NOUN
alkej-16	274	5	.	.	PROPN
alkej-16	274	6	2	2	NUM
alkej-16	274	7	no	no	NOUN
alkej-16	274	8	.	.	NOUN
alkej-16	275	1	2	2	NUM
alkej-16	275	2	,	,	PUNCT
alkej-16	275	3	pp	pp	ADJ
alkej-16	275	4	.	.	PUNCT
alkej-16	276	1	252	252	NUM
alkej-16	276	2	-	-	SYM
alkej-16	276	3	262	262	NUM
alkej-16	276	4	,	,	PUNCT
alkej-16	276	5	1991	1991	NUM
alkej-16	276	6	.	.	PUNCT
alkej-16	277	1	7	7	X
alkej-16	277	2	.	.	X
alkej-16	277	3	l.	l.	PROPN
alkej-16	277	4	behera	behera	PROPN
alkej-16	277	5	,	,	PUNCT
alkej-16	277	6	s.	s.	PROPN
alkej-16	277	7	chaudhury	chaudhury	PROPN
alkej-16	277	8	,	,	PUNCT
alkej-16	277	9	and	and	CCONJ
alkej-16	277	10	m.	m.	NOUN
alkej-16	277	11	gopal	gopal	NOUN
alkej-16	277	12	,	,	PUNCT
alkej-16	277	13	“	"	PUNCT
alkej-16	277	14	neuro	neuro	ADJ
alkej-16	277	15	-	-	PUNCT
alkej-16	277	16	adaptive	adaptive	ADJ
alkej-16	277	17	hybrid	hybrid	ADJ
alkej-16	277	18	controller	controller	NOUN
alkej-16	277	19	for	for	ADP
alkej-16	277	20	robot	robot	NOUN
alkej-16	277	21	-	-	PUNCT
alkej-16	277	22	manipulator	manipulator	NOUN
alkej-16	277	23	tracking	tracking	NOUN
alkej-16	277	24	control	control	NOUN
alkej-16	277	25	”	"	PUNCT
alkej-16	277	26	iee	iee	PROPN
alkej-16	277	27	proc	proc	PROPN
alkej-16	277	28	.	.	PUNCT
alkej-16	278	1	control	control	PROPN
alkej-16	278	2	theory	theory	PROPN
alkej-16	278	3	appl	appl	PROPN
alkej-16	279	1	.	.	PROPN
alkej-16	279	2	vol.143	vol.143	PROPN
alkej-16	279	3	,	,	PUNCT
alkej-16	279	4	no	no	INTJ
alkej-16	279	5	.	.	NOUN
alkej-16	279	6	3	3	NUM
alkej-16	279	7	,	,	PUNCT
alkej-16	279	8	pp.270275	pp.270275	PROPN
alkej-16	279	9	,	,	PUNCT
alkej-16	279	10	1996	1996	NUM
alkej-16	279	11	.	.	PUNCT
alkej-16	280	1	8	8	NUM
alkej-16	280	2	.	.	PUNCT
alkej-16	280	3	f.	f.	PROPN
alkej-16	280	4	c.	c.	PROPN
alkej-16	280	5	chen	chen	PROPN
alkej-16	280	6	,	,	PUNCT
alkej-16	280	7	“	"	PUNCT
alkej-16	280	8	back	back	ADJ
alkej-16	280	9	-	-	PUNCT
alkej-16	280	10	propagation	propagation	NOUN
alkej-16	280	11	neural	neural	ADJ
alkej-16	280	12	networks	network	NOUN
alkej-16	280	13	for	for	ADP
alkej-16	280	14	nonlinear	nonlinear	ADJ
alkej-16	280	15	selftuning	selftune	VERB
alkej-16	280	16	adaptive	adaptive	ADJ
alkej-16	280	17	control	control	NOUN
alkej-16	280	18	,	,	PUNCT
alkej-16	280	19	”	"	PUNCT
alkej-16	280	20	ieee	ieee	NOUN
alkej-16	280	21	control	control	PROPN
alkej-16	280	22	systems	systems	PROPN
alkej-16	280	23	magazine	magazine	NOUN
alkej-16	280	24	,	,	PUNCT
alkej-16	280	25	vol	vol	NOUN
alkej-16	280	26	.	.	PROPN
alkej-16	280	27	10	10	NUM
alkej-16	280	28	,	,	PUNCT
alkej-16	280	29	no	no	INTJ
alkej-16	280	30	.	.	NOUN
alkej-16	280	31	3	3	NUM
alkej-16	280	32	,	,	PUNCT
alkej-16	280	33	pp	pp	ADJ
alkej-16	280	34	.	.	PUNCT
alkej-16	281	1	44	44	NUM
alkej-16	281	2	-	-	SYM
alkej-16	281	3	48	48	NUM
alkej-16	281	4	,	,	PUNCT
alkej-16	281	5	1990	1990	NUM
alkej-16	281	6	.	.	PUNCT
alkej-16	282	1	9	9	NUM
alkej-16	282	2	.	.	X
alkej-16	282	3	s.	s.	PROPN
alkej-16	282	4	omatu	omatu	PROPN
alkej-16	282	5	,	,	PUNCT
alkej-16	282	6	m.	m.	PROPN
alkej-16	282	7	khalid	khalid	PROPN
alkej-16	282	8	,	,	PUNCT
alkej-16	282	9	and	and	CCONJ
alkej-16	282	10	r.	r.	PROPN
alkej-16	282	11	yusof	yusof	PROPN
alkej-16	282	12	,	,	PUNCT
alkej-16	282	13	neuro	neuro	NOUN
alkej-16	282	14	-	-	PUNCT
alkej-16	282	15	control	control	NOUN
alkej-16	282	16	and	and	CCONJ
alkej-16	282	17	its	its	PRON
alkej-16	282	18	applications	application	NOUN
alkej-16	282	19	.	.	PUNCT
alkej-16	283	1	london	london	PROPN
alkej-16	283	2	:	:	PUNCT
alkej-16	283	3	springervelag	springervelag	PROPN
alkej-16	283	4	,	,	PUNCT
alkej-16	283	5	1995	1995	NUM
alkej-16	283	6	.	.	PUNCT
alkej-16	284	1	10	10	NUM
alkej-16	284	2	.	.	PUNCT
alkej-16	284	3	s.	s.	PROPN
alkej-16	284	4	a.	a.	NOUN
alkej-16	284	5	billings	billing	NOUN
alkej-16	284	6	,	,	PUNCT
alkej-16	284	7	“	"	PUNCT
alkej-16	284	8	identification	identification	NOUN
alkej-16	284	9	of	of	ADP
alkej-16	284	10	nonlinear	nonlinear	ADJ
alkej-16	284	11	systems	system	NOUN
alkej-16	284	12	a	a	DET
alkej-16	284	13	survey	survey	NOUN
alkej-16	284	14	,	,	PUNCT
alkej-16	284	15	”	"	PUNCT
alkej-16	284	16	iee	iee	PROPN
alkej-16	284	17	proc	proc	PROPN
alkej-16	284	18	.	.	PROPN
alkej-16	284	19	,	,	PUNCT
alkej-16	284	20	vol	vol	NOUN
alkej-16	284	21	.	.	PUNCT
alkej-16	285	1	3,pp	3,pp	NUM
alkej-16	285	2	.	.	PUNCT
alkej-16	286	1	272	272	NUM
alkej-16	286	2	-	-	NUM
alkej-16	286	3	285,1980	285,1980	NUM
alkej-16	286	4	.	.	PUNCT
alkej-16	287	1	11	11	NUM
alkej-16	287	2	.	.	PUNCT
alkej-16	288	1	n.	n.	PROPN
alkej-16	288	2	b.	b.	PROPN
alkej-16	288	3	karayiannis	karayiannis	PROPN
alkej-16	288	4	and	and	CCONJ
alkej-16	288	5	a.n	a.n	PROPN
alkej-16	288	6	.	.	PROPN
alkej-16	288	7	venetsanopoulos	venetsanopoulos	PROPN
alkej-16	288	8	,	,	PUNCT
alkej-16	288	9	artificial	artificial	ADJ
alkej-16	288	10	neural	neural	ADJ
alkej-16	288	11	networks	network	NOUN
alkej-16	288	12	learning	learn	VERB
alkej-16	288	13	algorithms	algorithm	NOUN
alkej-16	288	14	,	,	PUNCT
alkej-16	288	15	performance	performance	NOUN
alkej-16	288	16	evaluation	evaluation	NOUN
alkej-16	288	17	,	,	PUNCT
alkej-16	288	18	and	and	CCONJ
alkej-16	288	19	applications	application	NOUN
alkej-16	288	20	.	.	PUNCT
alkej-16	289	1	london	london	PROPN
alkej-16	289	2	:	:	PUNCT
alkej-16	289	3	kluwer	kluwer	NOUN
alkej-16	289	4	academic	academic	ADJ
alkej-16	289	5	publishers	publisher	NOUN
alkej-16	289	6	.	.	PUNCT
alkej-16	290	1	1993	1993	NUM
alkej-16	290	2	.	.	PUNCT
alkej-16	291	1	12	12	NUM
alkej-16	291	2	.	.	PUNCT
alkej-16	292	1	k.	k.	PROPN
alkej-16	292	2	j.	j.	PROPN
alkej-16	292	3	hunt	hunt	PROPN
alkej-16	292	4	,	,	PUNCT
alkej-16	292	5	d.	d.	PROPN
alkej-16	292	6	sbarbaro	sbarbaro	PROPN
alkej-16	292	7	,	,	PUNCT
alkej-16	292	8	r.	r.	PROPN
alkej-16	292	9	zbikowski	zbikowski	PROPN
alkej-16	292	10	and	and	CCONJ
alkej-16	292	11	p.	p.	PROPN
alkej-16	292	12	j.	j.	PROPN
alkej-16	292	13	gawthrop	gawthrop	PROPN
alkej-16	292	14	,	,	PUNCT
alkej-16	292	15	”	"	PUNCT
alkej-16	292	16	neural	neural	ADJ
alkej-16	292	17	networks	network	NOUN
alkej-16	292	18	for	for	ADP
alkej-16	292	19	control	control	NOUN
alkej-16	292	20	systems	system	NOUN
alkej-16	292	21	—	—	PUNCT
alkej-16	292	22	a	a	DET
alkej-16	292	23	survey	survey	NOUN
alkej-16	292	24	,	,	PUNCT
alkej-16	292	25	”	"	PUNCT
alkej-16	292	26	automatica	automatica	PROPN
alkej-16	292	27	,	,	PUNCT
alkej-16	292	28	vol	vol	NOUN
alkej-16	292	29	.	.	PROPN
alkej-16	292	30	28	28	NUM
alkej-16	292	31	,	,	PUNCT
alkej-16	292	32	no	no	INTJ
alkej-16	292	33	.	.	NOUN
alkej-16	292	34	6	6	NUM
alkej-16	292	35	,	,	PUNCT
alkej-16	292	36	pp	pp	ADJ
alkej-16	292	37	.	.	PUNCT
alkej-16	292	38	1083	1083	NUM
alkej-16	292	39	-	-	SYM
alkej-16	292	40	1112	1112	NUM
alkej-16	292	41	,	,	PUNCT
alkej-16	292	42	1992	1992	NUM
alkej-16	292	43	.	.	PUNCT
alkej-16	293	1	13	13	NUM
alkej-16	293	2	.	.	PUNCT
alkej-16	294	1	k.	k.	PROPN
alkej-16	294	2	s.	s.	PROPN
alkej-16	294	3	narendra	narendra	PROPN
alkej-16	294	4	and	and	CCONJ
alkej-16	294	5	s.	s.	PROPN
alkej-16	294	6	mukhopadhyay	mukhopadhyay	PROPN
alkej-16	294	7	,	,	PUNCT
alkej-16	294	8	“	"	PUNCT
alkej-16	294	9	adaptive	adaptive	ADJ
alkej-16	294	10	control	control	NOUN
alkej-16	294	11	using	use	VERB
alkej-16	294	12	neural	neural	ADJ
alkej-16	294	13	networks	network	NOUN
alkej-16	294	14	and	and	CCONJ
alkej-16	294	15	approximate	approximate	ADJ
alkej-16	294	16	models	model	NOUN
alkej-16	294	17	,	,	PUNCT
alkej-16	294	18	”	"	PUNCT
alkej-16	294	19	ieee	ieee	NOUN
alkej-16	294	20	trans	tran	NOUN
alkej-16	294	21	.	.	PUNCT
alkej-16	295	1	neural	neural	ADJ
alkej-16	295	2	networks	network	NOUN
alkej-16	295	3	,	,	PUNCT
alkej-16	295	4	vol	vol	NOUN
alkej-16	295	5	.	.	PROPN
alkej-16	295	6	8	8	NUM
alkej-16	295	7	,	,	PUNCT
alkej-16	295	8	no	no	INTJ
alkej-16	295	9	.	.	NOUN
alkej-16	295	10	3	3	NUM
alkej-16	295	11	,	,	PUNCT
alkej-16	295	12	pp	pp	ADJ
alkej-16	295	13	.	.	PUNCT
alkej-16	296	1	475	475	NUM
alkej-16	296	2	-	-	SYM
alkej-16	296	3	485	485	NUM
alkej-16	296	4	,	,	PUNCT
alkej-16	296	5	1997	1997	NUM
alkej-16	296	6	.	.	PUNCT
alkej-16	297	1	14	14	NUM
alkej-16	297	2	.	.	PUNCT
alkej-16	298	1	ahmed	ahmed	PROPN
alkej-16	298	2	s.	s.	PROPN
alkej-16	298	3	al	al	PROPN
alkej-16	298	4	-	-	PUNCT
alkej-16	298	5	araji	araji	NOUN
alkej-16	298	6	“	"	PUNCT
alkej-16	298	7	a	a	DET
alkej-16	298	8	neural	neural	ADJ
alkej-16	298	9	controller	controller	NOUN
alkej-16	298	10	with	with	ADP
alkej-16	298	11	a	a	DET
alkej-16	298	12	pre	pre	ADJ
alkej-16	298	13	-	-	ADJ
alkej-16	298	14	assigned	assign	VERB
alkej-16	298	15	performance	performance	NOUN
alkej-16	298	16	index	index	NOUN
alkej-16	298	17	”	"	PUNCT
alkej-16	298	18	m.sc	m.sc	PROPN
alkej-16	298	19	.	.	PUNCT
alkej-16	298	20	thesis	thesis	NOUN
alkej-16	298	21	,	,	PUNCT
alkej-16	298	22	university	university	NOUN
alkej-16	298	23	of	of	ADP
alkej-16	298	24	technology	technology	NOUN
alkej-16	298	25	,	,	PUNCT
alkej-16	298	26	november	november	PROPN
alkej-16	298	27	2000	2000	NUM
alkej-16	298	28	.	.	PUNCT
alkej-16	299	1	ahmed	ahmed	PROPN
alkej-16	299	2	sabah	sabah	PROPN
alkej-16	299	3	abdul	abdul	PROPN
alkej-16	299	4	ameer	ameer	PROPN
alkej-16	299	5	/al	/al	PROPN
alkej-16	299	6	khwarizmi	khwarizmi	PROPN
alkej-16	299	7	engineering	engineering	PROPN
alkej-16	299	8	journal	journal	PROPN
alkej-16	299	9	,	,	PUNCT
alkej-16	299	10	vol	vol	NOUN
alkej-16	299	11	.	.	PROPN
alkej-16	299	12	1	1	NUM
alkej-16	299	13	,	,	PUNCT
alkej-16	299	14	no	no	INTJ
alkej-16	299	15	.	.	NOUN
alkej-16	299	16	1	1	NUM
alkej-16	299	17	,	,	PUNCT
alkej-16	299	18	pp	pp	ADV
alkej-16	299	19	1	1	NUM
alkej-16	299	20	-	-	SYM
alkej-16	299	21	18	18	NUM
alkej-16	299	22	(	(	PUNCT
alkej-16	299	23	2005	2005	NUM
alkej-16	299	24	)	)	PUNCT
alkej-16	299	25	١٨	١٨	NUM
alkej-16	299	26	المسيطر	المسيطر	PROPN
alkej-16	299	27	المتكيف	المتكيف	PROPN
alkej-16	299	28	ذو	ذو	PROPN
alkej-16	299	29	التنغيم	التنغيم	PROPN
alkej-16	299	30	التلقائي	التلقائي	PROPN
alkej-16	299	31	العصبي	العصبي	PROPN
alkej-16	299	32	لالنظمة	لالنظمة	VERB
alkej-16	299	33	الديناميكية	الديناميكية	PROPN
alkej-16	299	34	الالخطية	الالخطية	PROPN
alkej-16	299	35	احمد	احمد	VERB
alkej-16	299	36	صباح	صباح	PROPN
alkej-16	299	37	عبد	عبد	PROPN
alkej-16	299	38	االمير	االمير	PROPN
alkej-16	299	39	االعرجي	االعرجي	PROPN
alkej-16	299	40	لوجيةوالجامعة	لوجيةوالجامعة	PROPN
alkej-16	299	41	التكن	التكن	PROPN
alkej-16	299	42	:	:	PUNCT
alkej-16	299	43	الخالصة	الخالصة	VERB
alkej-16	299	44	يتم	يتم	PROPN
alkej-16	299	45	تعليمه	تعليمه	PROPN
alkej-16	299	46	بطريقة	بطريقة	NOUN
alkej-16	299	47	(	(	PUNCT
alkej-16	299	48	narma	narma	NOUN
alkej-16	299	49	-	-	PUNCT
alkej-16	299	50	l2	l2	NOUN
alkej-16	299	51	)	)	PUNCT
alkej-16	299	52	الذي	الذي	PROPN
alkej-16	299	53	أساسه	أساسه	PROPN
alkej-16	299	54	النموذج	النموذج	PROPN
alkej-16	299	55	العصبي	العصبي	PROPN
alkej-16	299	56	(	(	PUNCT
alkej-16	299	57	identifier	identifier	NOUN
alkej-16	299	58	)	)	PUNCT
alkej-16	299	59	أن	أن	ADP
alkej-16	299	60	هيكلية	هيكلية	NOUN
alkej-16	299	61	المسيطر	المسيطر	PROPN
alkej-16	299	62	العصبي	العصبي	PROPN
alkej-16	299	63	مع	مع	ADP
alkej-16	299	64	المعرف	المعرف	PROPN
alkej-16	299	65	(	(	PUNCT
alkej-16	299	66	off	off	ADP
alkej-16	299	67	-	-	PUNCT
alkej-16	299	68	line	line	NOUN
alkej-16	299	69	)	)	PUNCT
alkej-16	299	70	مع	مع	ADP
alkej-16	299	71	صيغتين	صيغتين	NOUN
alkej-16	299	72	التوالي	التوالي	NOUN
alkej-16	299	73	المتوازي	المتوازي	NOUN
alkej-16	299	74	و	و	PRON
alkej-16	299	75	المتوازي	المتوازي	PROPN
alkej-16	299	76	وتطبيق	وتطبيق	PROPN
alkej-16	299	77	خوارزمية	خوارزمية	PROPN
alkej-16	299	78	التنغيم	التنغيم	PROPN
alkej-16	299	79	التلقائي	التلقائي	PROPN
alkej-16	299	80	العصبي	العصبي	PROPN
alkej-16	299	81	للمسـيطر	للمسـيطر	PROPN
alkej-16	299	82	(	(	PUNCT
alkej-16	299	83	pid	pid	NOUN
alkej-16	299	84	)	)	PUNCT
alkej-16	299	85	كمقتـرح	كمقتـرح	NOUN
alkej-16	299	86	.لبناء	.لبناء	VERB
alkej-16	299	87	هيكلية	هيكلية	PROPN
alkej-16	299	88	المسيطر	المسيطر	PROPN
alkej-16	299	89	(	(	PUNCT
alkej-16	299	90	jacobain)هو	jacobain)هو	NOUN
alkej-16	299	91	نموذج	نموذج	PROPN
alkej-16	299	92	ألخطي	ألخطي	PROPN
alkej-16	299	93	يصف	يصف	PROPN
alkej-16	299	94	المنظومة	المنظومة	ADP
alkej-16	299	95	ألالخطية	ألالخطية	NOUN
alkej-16	299	96	ويسـتخدم	ويسـتخدم	PROPN
alkej-16	300	1	لتحقـق	لتحقـق	PROPN
alkej-16	300	2	مـن	مـن	NOUN
alkej-16	300	3	(	(	PUNCT
alkej-16	300	4	narma	narma	NOUN
alkej-16	300	5	-	-	PUNCT
alkej-16	300	6	l2)أن	l2)أن	PROPN
alkej-16	300	7	النموذج	النموذج	NOUN
alkej-16	300	8	العصبي	العصبي	ADJ
alkej-16	300	9	.منظومة	.منظومة	NUM
alkej-16	300	10	و	و	PRON
alkej-16	300	11	التي	التي	PROPN
alkej-16	300	12	تعتبر	تعتبر	PROPN
alkej-16	301	1	من	من	PRON
alkej-16	301	2	العناصر	العناصر	VERB
alkej-16	301	3	المهمة	المهمة	NOUN
alkej-16	301	4	و	و	PRON
alkej-16	301	5	الحرجة	الحرجة	VERB
alkej-16	301	6	في	في	ADP
alkej-16	301	7	إيجاد	إيجاد	PROPN
alkej-16	301	8	إشارة	إشارة	PROPN
alkej-16	301	9	التغذية	التغذية	PROPN
alkej-16	301	10	العكسيةلل	العكسيةلل	PROPN
alkej-16	301	11	للنموذج	للنموذج	PROPN
alkej-16	301	12	بطريقة	بطريقة	PROPN
alkej-16	301	13	خوارزمية	خوارزمية	PROPN
alkej-16	301	14	االنتشار	االنتشار	NOUN
alkej-16	301	15	(	(	PUNCT
alkej-16	301	16	weights)لتحديث	weights)لتحديث	X
alkej-16	301	17	األوزان	األوزان	NOUN
alkej-16	301	18	(	(	PUNCT
alkej-16	301	19	on	on	ADP
alkej-16	301	20	-	-	PUNCT
alkej-16	301	21	line)يتم	line)يتم	NOUN
alkej-16	302	1	أيضا	أيضا	ADJ
alkej-16	302	2	تعليمه	تعليمه	NOUN
alkej-16	302	3	(	(	PUNCT
alkej-16	302	4	narma	narma	NOUN
alkej-16	302	5	-	-	PUNCT
alkej-16	302	6	l2)أن	l2)أن	NOUN
alkej-16	302	7	المعرف	المعرف	NOUN
alkej-16	302	8	.العكسي	.العكسي	PUNCT
alkej-16	302	9	العامة	العامة	PROPN
alkej-16	302	10	لكي	لكي	PROPN
alkej-16	302	11	يصبح	يصبح	PROPN
alkej-16	302	12	النموذج	النموذج	PROPN
alkej-16	302	13	مطابق	مطابق	PROPN
alkej-16	302	14	الى	الى	PROPN
alkej-16	302	15	المنظومة	المنظومة	PROPN
alkej-16	302	16	ألالخطية	ألالخطية	PROPN
alkej-16	302	17	لكي	لكي	VERB
alkej-16	302	18	يتبع	يتبع	ADJ
alkej-16	302	19	إخراج	إخراج	NOUN
alkej-16	302	20	المنظومة	المنظومة	ADP
alkej-16	302	21	الحقيقية	الحقيقية	PROPN
alkej-16	302	22	(	(	PUNCT
alkej-16	302	23	pid	pid	NOUN
alkej-16	302	24	)	)	PUNCT
alkej-16	303	1	يطر	يطر	PRON
alkej-16	303	2	الراجع	الراجع	PROPN
alkej-16	303	3	العصبي	العصبي	ADJ
alkej-16	303	4	ذات	ذات	NOUN
alkej-16	303	5	التنغيم	التنغيم	PROPN
alkej-16	303	6	التلقائي	التلقائي	PROPN
alkej-16	303	7	لتعبير	لتعبير	PROPN
alkej-16	303	8	عناصر	عناصر	PROPN
alkej-16	303	9	المسيطر	المسيطر	PROPN
alkej-16	303	10	يستخدم	يستخدم	PROPN
alkej-16	303	11	المس	المس	PROPN
alkej-16	303	12	.خوارزمية	.خوارزمية	INTJ
alkej-16	303	13	االنتشار	االنتشار	PROPN
alkej-16	303	14	العكسي	العكسي	PROPN
alkej-16	303	15	العامة	العامة	PROPN
alkej-16	303	16	"	"	PUNCT
alkej-16	303	17	اإلدخال	اإلدخال	PROPN
alkej-16	303	18	المطلوب	المطلوب	PROPN
alkej-16	303	19	وباستخدام	وباستخدام	PROPN
alkej-16	303	20	أيضا	أيضا	PROPN
alkej-16	303	21	.للمنظومةأن	.للمنظومةأن	DET
alkej-16	303	22	هيكلية	هيكلية	PROPN
alkej-16	303	23	المسيطر	المسيطر	PROPN
alkej-16	303	24	المقترح	المقترح	VERB
alkej-16	303	25	يستخدم	يستخدم	PROPN
alkej-16	303	26	لتقليل	لتقليل	PROPN
alkej-16	303	27	الخطاء	الخطاء	PROPN
alkej-16	304	1	بين	بين	AUX
alkej-16	304	2	اإلخراج	اإلخراج	VERB
alkej-16	304	3	المرغوب	المرغوب	VERB
alkej-16	304	4	و	و	PRON
alkej-16	304	5	اإلخراج	اإلخراج	NOUN
alkej-16	304	6	الحقيقي	الحقيقي	VERB
alkej-16	304	7	.لقد	.لقد	PROPN
alkej-16	304	8	تم	تم	PROPN
alkej-16	304	9	الحصول	الحصول	PROPN
alkej-16	304	10	على	على	PROPN
alkej-16	304	11	نتائج	نتائج	PROPN
alkej-16	304	12	ممتازة	ممتازة	PROPN
alkej-16	304	13	باستخدام	باستخدام	PROPN
alkej-16	304	14	المسيطر	المسيطر	PROPN
alkej-16	304	15	المقترح	المقترح	PROPN
alkej-16	304	16	عندما	عندما	ADJ
alkej-16	304	17	طبق	طبق	NOUN
alkej-16	304	18	هذا	هذا	PROPN
alkej-16	304	19	المسيطر	المسيطر	PROPN
alkej-16	304	20	على	على	PROPN
alkej-16	304	21	المنظومة	المنظومة	ADP
alkej-16	304	22	ألالخطية	ألالخطية	NOUN