id	sid	tid	token	lemma	pos
ejpam-590	1	1	3_590_tomar.dvi	3_590_tomar.dvi	NUM
ejpam-590	1	2	european	european	ADJ
ejpam-590	1	3	journal	journal	NOUN
ejpam-590	1	4	of	of	ADP
ejpam-590	1	5	pure	pure	ADJ
ejpam-590	1	6	and	and	CCONJ
ejpam-590	1	7	applied	apply	VERB
ejpam-590	1	8	mathematics	mathematic	NOUN
ejpam-590	1	9	vol	vol	NOUN
ejpam-590	1	10	.	.	PROPN
ejpam-590	1	11	4	4	NUM
ejpam-590	1	12	,	,	PUNCT
ejpam-590	1	13	no	no	INTJ
ejpam-590	1	14	.	.	NOUN
ejpam-590	1	15	2	2	NUM
ejpam-590	1	16	,	,	PUNCT
ejpam-590	1	17	2011	2011	NUM
ejpam-590	1	18	,	,	PUNCT
ejpam-590	1	19	117	117	NUM
ejpam-590	1	20	-	-	SYM
ejpam-590	1	21	128	128	NUM
ejpam-590	1	22	issn	issn	PROPN
ejpam-590	1	23	1307	1307	NUM
ejpam-590	1	24	-	-	SYM
ejpam-590	1	25	5543	5543	NUM
ejpam-590	1	26	–	–	PUNCT
ejpam-590	1	27	www.ejpam.com	www.ejpam.com	X
ejpam-590	1	28	hybridization	hybridization	NOUN
ejpam-590	1	29	of	of	ADP
ejpam-590	1	30	neural	neural	ADJ
ejpam-590	1	31	nets	net	NOUN
ejpam-590	1	32	and	and	CCONJ
ejpam-590	1	33	genetic	genetic	ADJ
ejpam-590	1	34	algorithms	algorithm	NOUN
ejpam-590	1	35	to	to	PART
ejpam-590	1	36	compute	compute	VERB
ejpam-590	1	37	the	the	DET
ejpam-590	1	38	boundary	boundary	ADJ
ejpam-590	1	39	control	control	NOUN
ejpam-590	1	40	for	for	ADP
ejpam-590	1	41	controlled	control	VERB
ejpam-590	1	42	heat	heat	NOUN
ejpam-590	1	43	equation	equation	NOUN
ejpam-590	1	44	n.	n.	PROPN
ejpam-590	1	45	k.	k.	PROPN
ejpam-590	1	46	tomar1∗	tomar1∗	PROPN
ejpam-590	1	47	,	,	PUNCT
ejpam-590	1	48	n.	n.	PROPN
ejpam-590	1	49	sukavanam2	sukavanam2	PROPN
ejpam-590	1	50	,	,	PUNCT
ejpam-590	1	51	k.	k.	PROPN
ejpam-590	2	1	p.	p.	NOUN
ejpam-590	2	2	singh3	singh3	AUX
ejpam-590	2	3	1	1	NUM
ejpam-590	2	4	department	department	NOUN
ejpam-590	2	5	of	of	ADP
ejpam-590	2	6	mathematics	mathematics	PROPN
ejpam-590	2	7	,	,	PUNCT
ejpam-590	2	8	indian	indian	PROPN
ejpam-590	2	9	institute	institute	PROPN
ejpam-590	2	10	of	of	ADP
ejpam-590	2	11	technology	technology	PROPN
ejpam-590	2	12	patna-800013	patna-800013	ADJ
ejpam-590	2	13	,	,	PUNCT
ejpam-590	2	14	india	india	PROPN
ejpam-590	2	15	2	2	NUM
ejpam-590	2	16	department	department	NOUN
ejpam-590	2	17	of	of	ADP
ejpam-590	2	18	mathematics	mathematics	PROPN
ejpam-590	2	19	,	,	PUNCT
ejpam-590	2	20	indian	indian	PROPN
ejpam-590	2	21	institute	institute	PROPN
ejpam-590	2	22	of	of	ADP
ejpam-590	2	23	technology	technology	PROPN
ejpam-590	2	24	roorkee-247667	roorkee-247667	NOUN
ejpam-590	2	25	,	,	PUNCT
ejpam-590	2	26	india	india	PROPN
ejpam-590	2	27	3	3	NUM
ejpam-590	2	28	indian	indian	PROPN
ejpam-590	2	29	institute	institute	PROPN
ejpam-590	2	30	of	of	ADP
ejpam-590	2	31	information	information	NOUN
ejpam-590	2	32	technology	technology	NOUN
ejpam-590	2	33	allahabad-211012	allahabad-211012	NOUN
ejpam-590	2	34	,	,	PUNCT
ejpam-590	2	35	india	india	PROPN
ejpam-590	2	36	abstract	abstract	NOUN
ejpam-590	2	37	.	.	PUNCT
ejpam-590	3	1	this	this	DET
ejpam-590	3	2	paper	paper	NOUN
ejpam-590	3	3	presents	present	VERB
ejpam-590	3	4	a	a	DET
ejpam-590	3	5	computational	computational	ADJ
ejpam-590	3	6	method	method	NOUN
ejpam-590	3	7	for	for	ADP
ejpam-590	3	8	boundary	boundary	ADJ
ejpam-590	3	9	control	control	NOUN
ejpam-590	3	10	of	of	ADP
ejpam-590	3	11	controlled	control	VERB
ejpam-590	3	12	heat	heat	NOUN
ejpam-590	3	13	equation	equation	NOUN
ejpam-590	3	14	.	.	PUNCT
ejpam-590	4	1	the	the	DET
ejpam-590	4	2	proposed	propose	VERB
ejpam-590	4	3	method	method	NOUN
ejpam-590	4	4	relies	rely	VERB
ejpam-590	4	5	upon	upon	SCONJ
ejpam-590	4	6	the	the	DET
ejpam-590	4	7	function	function	NOUN
ejpam-590	4	8	approximation	approximation	NOUN
ejpam-590	4	9	capability	capability	NOUN
ejpam-590	4	10	of	of	ADP
ejpam-590	4	11	feedforward	feedforward	ADJ
ejpam-590	4	12	neural	neural	ADJ
ejpam-590	4	13	network	network	NOUN
ejpam-590	4	14	and	and	CCONJ
ejpam-590	4	15	global	global	ADJ
ejpam-590	4	16	optimization	optimization	NOUN
ejpam-590	4	17	power	power	NOUN
ejpam-590	4	18	of	of	ADP
ejpam-590	4	19	genetic	genetic	ADJ
ejpam-590	4	20	algorithm	algorithm	NOUN
ejpam-590	4	21	.	.	PUNCT
ejpam-590	5	1	2000	2000	NUM
ejpam-590	5	2	mathematics	mathematic	NOUN
ejpam-590	5	3	subject	subject	NOUN
ejpam-590	5	4	classifications	classification	NOUN
ejpam-590	5	5	:	:	PUNCT
ejpam-590	5	6	93c20	93c20	NUM
ejpam-590	5	7	,	,	PUNCT
ejpam-590	5	8	92b20	92b20	NUM
ejpam-590	5	9	,	,	PUNCT
ejpam-590	5	10	90c90	90c90	NUM
ejpam-590	5	11	key	key	ADJ
ejpam-590	5	12	words	word	NOUN
ejpam-590	5	13	and	and	CCONJ
ejpam-590	5	14	phrases	phrase	NOUN
ejpam-590	5	15	:	:	PUNCT
ejpam-590	5	16	control	control	NOUN
ejpam-590	5	17	system	system	NOUN
ejpam-590	5	18	governed	govern	VERB
ejpam-590	5	19	by	by	ADP
ejpam-590	5	20	heat	heat	NOUN
ejpam-590	5	21	equation	equation	NOUN
ejpam-590	5	22	,	,	PUNCT
ejpam-590	5	23	artificial	artificial	ADJ
ejpam-590	5	24	neural	neural	ADJ
ejpam-590	5	25	networks	network	NOUN
ejpam-590	5	26	,	,	PUNCT
ejpam-590	5	27	genetic	genetic	ADJ
ejpam-590	5	28	algorithms	algorithm	NOUN
ejpam-590	5	29	1	1	NUM
ejpam-590	5	30	.	.	PUNCT
ejpam-590	6	1	introduction	introduction	NOUN
ejpam-590	6	2	let	let	VERB
ejpam-590	6	3	ω	ω	NOUN
ejpam-590	6	4	be	be	AUX
ejpam-590	6	5	a	a	DET
ejpam-590	6	6	nonempty	nonempty	ADJ
ejpam-590	6	7	,	,	PUNCT
ejpam-590	6	8	bounded	bound	VERB
ejpam-590	6	9	,	,	PUNCT
ejpam-590	6	10	open	open	ADJ
ejpam-590	6	11	and	and	CCONJ
ejpam-590	6	12	connected	connected	ADJ
ejpam-590	6	13	domain	domain	NOUN
ejpam-590	6	14	in	in	ADP
ejpam-590	6	15	rn	rn	PROPN
ejpam-590	6	16	with	with	ADP
ejpam-590	6	17	a	a	DET
ejpam-590	6	18	smooth	smooth	ADJ
ejpam-590	6	19	boundary	boundary	ADJ
ejpam-590	6	20	γ	γ	PROPN
ejpam-590	6	21	.	.	PROPN
ejpam-590	6	22	consider	consider	VERB
ejpam-590	6	23	the	the	DET
ejpam-590	6	24	time	time	NOUN
ejpam-590	6	25	interval	interval	NOUN
ejpam-590	6	26	(	(	PUNCT
ejpam-590	6	27	0,τ	0,τ	NOUN
ejpam-590	6	28	)	)	PUNCT
ejpam-590	6	29	and	and	CCONJ
ejpam-590	6	30	the	the	DET
ejpam-590	6	31	sets	set	NOUN
ejpam-590	6	32	q	q	NOUN
ejpam-590	7	1	=	=	PUNCT
ejpam-590	7	2	ω×	ω×	X
ejpam-590	7	3	(	(	PUNCT
ejpam-590	7	4	0,τ	0,τ	NUM
ejpam-590	7	5	)	)	PUNCT
ejpam-590	7	6	and	and	CCONJ
ejpam-590	7	7	∑	∑	PUNCT
ejpam-590	7	8	=	=	SYM
ejpam-590	7	9	γ	γ	X
ejpam-590	7	10	×	×	NOUN
ejpam-590	7	11	(	(	PUNCT
ejpam-590	7	12	0,τ	0,τ	PROPN
ejpam-590	7	13	)	)	PUNCT
ejpam-590	7	14	.	.	PUNCT
ejpam-590	8	1	the	the	DET
ejpam-590	8	2	controlled	control	VERB
ejpam-590	8	3	semilinear	semilinear	PROPN
ejpam-590	8	4	heat	heat	NOUN
ejpam-590	8	5	equation	equation	NOUN
ejpam-590	8	6	,	,	PUNCT
ejpam-590	8	7	with	with	ADP
ejpam-590	8	8	boundary	boundary	ADJ
ejpam-590	8	9	control	control	NOUN
ejpam-590	8	10	,	,	PUNCT
ejpam-590	8	11	in	in	ADP
ejpam-590	8	12	q	q	PROPN
ejpam-590	8	13	is	be	AUX
ejpam-590	8	14	∂	∂	NUM
ejpam-590	8	15	ω(x	ω(x	NUM
ejpam-590	8	16	,	,	PUNCT
ejpam-590	8	17	t	t	PROPN
ejpam-590	8	18	)	)	PUNCT
ejpam-590	8	19	∂	∂	NOUN
ejpam-590	8	20	t	t	NOUN
ejpam-590	8	21	=	=	SYM
ejpam-590	8	22	c2∆ω(x	c2∆ω(x	PROPN
ejpam-590	8	23	,	,	PUNCT
ejpam-590	8	24	t	t	PROPN
ejpam-590	8	25	)	)	PUNCT
ejpam-590	8	26	+	+	PROPN
ejpam-590	8	27	φ(t	φ(t	PROPN
ejpam-590	8	28	,	,	PUNCT
ejpam-590	8	29	ω(x	ω(x	X
ejpam-590	8	30	,	,	PUNCT
ejpam-590	8	31	t	t	PROPN
ejpam-590	8	32	)	)	PUNCT
ejpam-590	8	33	)	)	PUNCT
ejpam-590	8	34	;	;	PUNCT
ejpam-590	8	35	in	in	ADP
ejpam-590	8	36	q	q	PROPN
ejpam-590	8	37	ω(x	ω(x	NUM
ejpam-590	8	38	,	,	PUNCT
ejpam-590	8	39	0	0	NUM
ejpam-590	8	40	)	)	PUNCT
ejpam-590	8	41	=	=	PUNCT
ejpam-590	8	42	ω0	ω0	NOUN
ejpam-590	8	43	;	;	PUNCT
ejpam-590	8	44	in	in	ADP
ejpam-590	8	45	ω	ω	PROPN
ejpam-590	8	46	ω	ω	PROPN
ejpam-590	8	47	=	=	SYM
ejpam-590	8	48	c(σ	c(σ	PROPN
ejpam-590	8	49	,	,	PUNCT
ejpam-590	8	50	t	t	PROPN
ejpam-590	8	51	)	)	PUNCT
ejpam-590	8	52	;	;	PUNCT
ejpam-590	8	53	on	on	ADP
ejpam-590	8	54	γ	γ	X
ejpam-590	8	55	(	(	PUNCT
ejpam-590	8	56	1	1	NUM
ejpam-590	8	57	)	)	PUNCT
ejpam-590	8	58	where	where	SCONJ
ejpam-590	8	59	,	,	PUNCT
ejpam-590	8	60	ω(x	ω(x	PROPN
ejpam-590	8	61	,	,	PUNCT
ejpam-590	8	62	t	t	PROPN
ejpam-590	8	63	)	)	PUNCT
ejpam-590	8	64	denotes	denote	VERB
ejpam-590	8	65	the	the	DET
ejpam-590	8	66	temperature	temperature	NOUN
ejpam-590	8	67	at	at	ADP
ejpam-590	8	68	x	x	PROPN
ejpam-590	8	69	∈	∈	PROPN
ejpam-590	8	70	ω	ω	PROPN
ejpam-590	8	71	and	and	CCONJ
ejpam-590	8	72	t	t	PROPN
ejpam-590	8	73	∈	∈	PROPN
ejpam-590	9	1	[	[	X
ejpam-590	9	2	0,τ	0,τ	NUM
ejpam-590	9	3	]	]	PUNCT
ejpam-590	9	4	,	,	PUNCT
ejpam-590	9	5	∆	∆	PROPN
ejpam-590	9	6	denotes	denote	VERB
ejpam-590	9	7	the	the	DET
ejpam-590	9	8	laplace	laplace	NOUN
ejpam-590	9	9	operator	operator	NOUN
ejpam-590	9	10	,	,	PUNCT
ejpam-590	9	11	φ	φ	PROPN
ejpam-590	9	12	is	be	AUX
ejpam-590	9	13	a	a	DET
ejpam-590	9	14	linear	linear	ADJ
ejpam-590	9	15	or	or	CCONJ
ejpam-590	9	16	nonlinear	nonlinear	ADJ
ejpam-590	9	17	operator	operator	NOUN
ejpam-590	9	18	and	and	CCONJ
ejpam-590	9	19	c	c	NOUN
ejpam-590	9	20	is	be	AUX
ejpam-590	9	21	a	a	DET
ejpam-590	9	22	real	real	ADV
ejpam-590	9	23	constant	constant	ADJ
ejpam-590	9	24	.	.	PUNCT
ejpam-590	10	1	c(σ	c(σ	PROPN
ejpam-590	10	2	,	,	PUNCT
ejpam-590	10	3	t	t	PROPN
ejpam-590	10	4	)	)	PUNCT
ejpam-590	10	5	represents	represent	VERB
ejpam-590	10	6	boundary	boundary	ADJ
ejpam-590	10	7	control	control	NOUN
ejpam-590	10	8	function	function	NOUN
ejpam-590	10	9	,	,	PUNCT
ejpam-590	10	10	σ	σ	NOUN
ejpam-590	10	11	being	be	AUX
ejpam-590	10	12	boundary	boundary	ADJ
ejpam-590	10	13	variable	variable	NOUN
ejpam-590	10	14	.	.	PUNCT
ejpam-590	11	1	now	now	ADV
ejpam-590	11	2	,	,	PUNCT
ejpam-590	11	3	the	the	DET
ejpam-590	11	4	problem	problem	NOUN
ejpam-590	11	5	is	be	AUX
ejpam-590	11	6	to	to	PART
ejpam-590	11	7	find	find	VERB
ejpam-590	11	8	a	a	DET
ejpam-590	11	9	boundary	boundary	ADJ
ejpam-590	11	10	control	control	NOUN
ejpam-590	11	11	function	function	NOUN
ejpam-590	11	12	c	c	NOUN
ejpam-590	11	13	on	on	ADP
ejpam-590	11	14	γ	γ	PRON
ejpam-590	11	15	such	such	ADJ
ejpam-590	11	16	that	that	SCONJ
ejpam-590	11	17	the	the	DET
ejpam-590	11	18	solution	solution	NOUN
ejpam-590	11	19	ω	ω	PROPN
ejpam-590	11	20	satisfies	satisfie	NOUN
ejpam-590	11	21	ω(x	ω(x	NUM
ejpam-590	11	22	,	,	PUNCT
ejpam-590	11	23	τ	τ	X
ejpam-590	11	24	)	)	PUNCT
ejpam-590	12	1	=	=	NOUN
ejpam-590	12	2	ωτ	ωτ	NOUN
ejpam-590	12	3	on	on	ADP
ejpam-590	12	4	ω	ω	PROPN
ejpam-590	12	5	,	,	PUNCT
ejpam-590	12	6	where	where	SCONJ
ejpam-590	12	7	ωτ	ωτ	PROPN
ejpam-590	12	8	is	be	AUX
ejpam-590	12	9	any	any	DET
ejpam-590	12	10	final	final	ADJ
ejpam-590	12	11	required	required	ADJ
ejpam-590	12	12	temperature	temperature	NOUN
ejpam-590	12	13	.	.	PUNCT
ejpam-590	13	1	∗corresponding	∗corresponde	VERB
ejpam-590	13	2	author	author	NOUN
ejpam-590	13	3	.	.	PUNCT
ejpam-590	14	1	email	email	NOUN
ejpam-590	14	2	addresses	address	NOUN
ejpam-590	14	3	:	:	PUNCT
ejpam-590	14	4	nktomar	nktomar	PROPN
ejpam-590	14	5	�	�	PROPN
ejpam-590	14	6	iitp.a	iitp.a	PROPN
ejpam-590	14	7	.in	.in	PUNCT
ejpam-590	14	8	(	(	PUNCT
ejpam-590	14	9	n.	n.	NOUN
ejpam-590	14	10	tomar	tomar	PROPN
ejpam-590	14	11	)	)	PUNCT
ejpam-590	14	12	,	,	PUNCT
ejpam-590	14	13	nsukvfma�iitr.ernet.in	nsukvfma�iitr.ernet.in	INTJ
ejpam-590	14	14	(	(	PUNCT
ejpam-590	14	15	n.	n.	NOUN
ejpam-590	14	16	sukavanam),kpsinghiitr	sukavanam),kpsinghiitr	PROPN
ejpam-590	14	17	�	�	NOUN
ejpam-590	14	18	gmail	gmail	NOUN
ejpam-590	14	19	.	.	PUNCT
ejpam-590	15	1	om	om	PROPN
ejpam-590	15	2	(	(	PUNCT
ejpam-590	15	3	k.	k.	PROPN
ejpam-590	15	4	singh	singh	PROPN
ejpam-590	15	5	)	)	PUNCT
ejpam-590	15	6	http://www.ejpam.com	http://www.ejpam.com	X
ejpam-590	16	1	117	117	NUM
ejpam-590	16	2	c	c	X
ejpam-590	16	3	©	©	PROPN
ejpam-590	16	4	2011	2011	NUM
ejpam-590	16	5	ejpam	ejpam	VERB
ejpam-590	16	6	all	all	DET
ejpam-590	16	7	rights	right	NOUN
ejpam-590	16	8	reserved	reserve	VERB
ejpam-590	16	9	.	.	PUNCT
ejpam-590	17	1	n.	n.	PROPN
ejpam-590	17	2	tomar	tomar	PROPN
ejpam-590	17	3	,	,	PUNCT
ejpam-590	17	4	n.	n.	NOUN
ejpam-590	17	5	sukavanam	sukavanam	NOUN
ejpam-590	17	6	,	,	PUNCT
ejpam-590	17	7	k.	k.	PROPN
ejpam-590	17	8	singh	singh	PROPN
ejpam-590	17	9	/	/	SYM
ejpam-590	17	10	eur	eur	PROPN
ejpam-590	17	11	.	.	PUNCT
ejpam-590	18	1	j.	j.	PROPN
ejpam-590	18	2	pure	pure	PROPN
ejpam-590	18	3	appl	appl	PROPN
ejpam-590	18	4	.	.	PROPN
ejpam-590	18	5	math	math	PROPN
ejpam-590	18	6	,	,	PUNCT
ejpam-590	18	7	4	4	NUM
ejpam-590	18	8	(	(	PUNCT
ejpam-590	18	9	2011	2011	NUM
ejpam-590	18	10	)	)	PUNCT
ejpam-590	18	11	,	,	PUNCT
ejpam-590	18	12	117	117	NUM
ejpam-590	18	13	-	-	SYM
ejpam-590	18	14	128	128	NUM
ejpam-590	18	15	118	118	NUM
ejpam-590	18	16	studies	study	NOUN
ejpam-590	18	17	on	on	ADP
ejpam-590	18	18	the	the	DET
ejpam-590	18	19	controlled	control	VERB
ejpam-590	18	20	heat	heat	NOUN
ejpam-590	18	21	equation	equation	NOUN
ejpam-590	18	22	have	have	AUX
ejpam-590	18	23	revealed	reveal	VERB
ejpam-590	18	24	many	many	ADJ
ejpam-590	18	25	theoretical	theoretical	ADJ
ejpam-590	18	26	concepts	concept	NOUN
ejpam-590	18	27	for	for	ADP
ejpam-590	18	28	different	different	ADJ
ejpam-590	18	29	types	type	NOUN
ejpam-590	18	30	of	of	ADP
ejpam-590	18	31	controllability	controllability	NOUN
ejpam-590	18	32	problems	problem	NOUN
ejpam-590	18	33	,	,	PUNCT
ejpam-590	18	34	see	see	VERB
ejpam-590	18	35	for	for	ADP
ejpam-590	18	36	instance	instance	NOUN
ejpam-590	18	37	[	[	X
ejpam-590	18	38	19	19	NUM
ejpam-590	18	39	,	,	PUNCT
ejpam-590	18	40	2	2	NUM
ejpam-590	18	41	,	,	PUNCT
ejpam-590	18	42	9	9	NUM
ejpam-590	18	43	,	,	PUNCT
ejpam-590	18	44	4	4	NUM
ejpam-590	18	45	,	,	PUNCT
ejpam-590	18	46	14	14	NUM
ejpam-590	18	47	,	,	PUNCT
ejpam-590	18	48	6	6	NUM
ejpam-590	18	49	,	,	PUNCT
ejpam-590	18	50	17	17	NUM
ejpam-590	18	51	,	,	PUNCT
ejpam-590	18	52	8	8	NUM
ejpam-590	18	53	,	,	PUNCT
ejpam-590	18	54	16	16	NUM
ejpam-590	18	55	]	]	PUNCT
ejpam-590	18	56	.	.	PUNCT
ejpam-590	19	1	but	but	CCONJ
ejpam-590	19	2	there	there	PRON
ejpam-590	19	3	is	be	VERB
ejpam-590	19	4	a	a	DET
ejpam-590	19	5	gap	gap	NOUN
ejpam-590	19	6	in	in	ADP
ejpam-590	19	7	the	the	DET
ejpam-590	19	8	literature	literature	NOUN
ejpam-590	19	9	for	for	ADP
ejpam-590	19	10	numerical	numerical	ADJ
ejpam-590	19	11	solution	solution	NOUN
ejpam-590	19	12	for	for	ADP
ejpam-590	19	13	boundary	boundary	ADJ
ejpam-590	19	14	control	control	NOUN
ejpam-590	19	15	,	,	PUNCT
ejpam-590	19	16	which	which	PRON
ejpam-590	19	17	is	be	AUX
ejpam-590	19	18	one	one	NUM
ejpam-590	19	19	of	of	ADP
ejpam-590	19	20	the	the	DET
ejpam-590	19	21	important	important	ADJ
ejpam-590	19	22	issues	issue	NOUN
ejpam-590	19	23	in	in	ADP
ejpam-590	19	24	the	the	DET
ejpam-590	19	25	context	context	NOUN
ejpam-590	19	26	of	of	ADP
ejpam-590	19	27	controlled	control	VERB
ejpam-590	19	28	heat	heat	NOUN
ejpam-590	19	29	equation	equation	NOUN
ejpam-590	19	30	model	model	NOUN
ejpam-590	19	31	.	.	PUNCT
ejpam-590	20	1	the	the	DET
ejpam-590	20	2	numerical	numerical	ADJ
ejpam-590	20	3	computation	computation	NOUN
ejpam-590	20	4	of	of	ADP
ejpam-590	20	5	boundary	boundary	ADJ
ejpam-590	20	6	control	control	NOUN
ejpam-590	20	7	of	of	ADP
ejpam-590	20	8	a	a	DET
ejpam-590	20	9	two	two	NUM
ejpam-590	20	10	dimensional	dimensional	ADJ
ejpam-590	20	11	linear	linear	ADJ
ejpam-590	20	12	heat	heat	NOUN
ejpam-590	20	13	equation	equation	NOUN
ejpam-590	20	14	has	have	AUX
ejpam-590	20	15	been	be	AUX
ejpam-590	20	16	shown	show	VERB
ejpam-590	20	17	in	in	ADP
ejpam-590	20	18	[	[	X
ejpam-590	20	19	2	2	NUM
ejpam-590	20	20	]	]	PUNCT
ejpam-590	20	21	using	use	VERB
ejpam-590	20	22	finite	finite	ADJ
ejpam-590	20	23	difference	difference	NOUN
ejpam-590	20	24	,	,	PUNCT
ejpam-590	20	25	finite	finite	NOUN
ejpam-590	20	26	element	element	NOUN
ejpam-590	20	27	and	and	CCONJ
ejpam-590	20	28	conjugate	conjugate	ADJ
ejpam-590	20	29	gradient	gradient	ADJ
ejpam-590	20	30	method	method	NOUN
ejpam-590	20	31	.	.	PUNCT
ejpam-590	21	1	in	in	ADP
ejpam-590	21	2	this	this	DET
ejpam-590	21	3	paper	paper	NOUN
ejpam-590	21	4	,	,	PUNCT
ejpam-590	21	5	a	a	DET
ejpam-590	21	6	method	method	NOUN
ejpam-590	21	7	for	for	ADP
ejpam-590	21	8	computation	computation	NOUN
ejpam-590	21	9	of	of	ADP
ejpam-590	21	10	boundary	boundary	ADJ
ejpam-590	21	11	control	control	NOUN
ejpam-590	21	12	for	for	ADP
ejpam-590	21	13	mathematical	mathematical	ADJ
ejpam-590	21	14	model	model	NOUN
ejpam-590	21	15	(	(	PUNCT
ejpam-590	21	16	1	1	NUM
ejpam-590	21	17	)	)	PUNCT
ejpam-590	21	18	,	,	PUNCT
ejpam-590	21	19	under	under	ADP
ejpam-590	21	20	the	the	DET
ejpam-590	21	21	given	give	VERB
ejpam-590	21	22	initial	initial	ADJ
ejpam-590	21	23	,	,	PUNCT
ejpam-590	21	24	final	final	ADJ
ejpam-590	21	25	and	and	CCONJ
ejpam-590	21	26	boundary	boundary	ADJ
ejpam-590	21	27	conditions	condition	NOUN
ejpam-590	21	28	,	,	PUNCT
ejpam-590	21	29	is	be	AUX
ejpam-590	21	30	proposed	propose	VERB
ejpam-590	21	31	using	use	VERB
ejpam-590	21	32	developing	develop	VERB
ejpam-590	21	33	less	less	ADJ
ejpam-590	21	34	conventional	conventional	ADJ
ejpam-590	21	35	artificial	artificial	ADJ
ejpam-590	21	36	neural	neural	ADJ
ejpam-590	21	37	network	network	NOUN
ejpam-590	21	38	(	(	PUNCT
ejpam-590	21	39	ann	ann	PROPN
ejpam-590	21	40	)	)	PUNCT
ejpam-590	21	41	and	and	CCONJ
ejpam-590	21	42	genetic	genetic	ADJ
ejpam-590	21	43	algorithm	algorithm	NOUN
ejpam-590	21	44	(	(	PUNCT
ejpam-590	21	45	ga	ga	NOUN
ejpam-590	21	46	)	)	PUNCT
ejpam-590	21	47	techniques	technique	NOUN
ejpam-590	21	48	.	.	PUNCT
ejpam-590	22	1	in	in	ADP
ejpam-590	22	2	[	[	X
ejpam-590	22	3	11	11	NUM
ejpam-590	22	4	,	,	PUNCT
ejpam-590	22	5	12	12	NUM
ejpam-590	22	6	]	]	PUNCT
ejpam-590	22	7	neural	neural	ADJ
ejpam-590	22	8	networks	network	NOUN
ejpam-590	22	9	have	have	AUX
ejpam-590	22	10	been	be	AUX
ejpam-590	22	11	used	use	VERB
ejpam-590	22	12	for	for	ADP
ejpam-590	22	13	solving	solve	VERB
ejpam-590	22	14	ordinary	ordinary	ADJ
ejpam-590	22	15	and	and	CCONJ
ejpam-590	22	16	partial	partial	ADJ
ejpam-590	22	17	differential	differential	ADJ
ejpam-590	22	18	equations	equation	NOUN
ejpam-590	22	19	with	with	ADP
ejpam-590	22	20	known	know	VERB
ejpam-590	22	21	initial	initial	ADJ
ejpam-590	22	22	and	and	CCONJ
ejpam-590	22	23	boundary	boundary	ADJ
ejpam-590	22	24	conditions	condition	NOUN
ejpam-590	22	25	.	.	PUNCT
ejpam-590	23	1	sukavanam	sukavanam	NOUN
ejpam-590	23	2	and	and	CCONJ
ejpam-590	23	3	panwar	panwar	VERB
ejpam-590	23	4	[	[	X
ejpam-590	23	5	15	15	NUM
ejpam-590	23	6	]	]	PUNCT
ejpam-590	23	7	presented	present	VERB
ejpam-590	23	8	a	a	DET
ejpam-590	23	9	numerical	numerical	ADJ
ejpam-590	23	10	solution	solution	NOUN
ejpam-590	23	11	of	of	ADP
ejpam-590	23	12	boundary	boundary	ADJ
ejpam-590	23	13	control	control	NOUN
ejpam-590	23	14	for	for	ADP
ejpam-590	23	15	controlled	control	VERB
ejpam-590	23	16	heat	heat	NOUN
ejpam-590	23	17	equation	equation	NOUN
ejpam-590	23	18	using	use	VERB
ejpam-590	23	19	ann	ann	PROPN
ejpam-590	23	20	.	.	PUNCT
ejpam-590	24	1	in	in	ADP
ejpam-590	24	2	all	all	DET
ejpam-590	24	3	these	these	DET
ejpam-590	24	4	thee	thee	NOUN
ejpam-590	24	5	papers	paper	NOUN
ejpam-590	24	6	[	[	X
ejpam-590	24	7	11	11	NUM
ejpam-590	24	8	,	,	PUNCT
ejpam-590	24	9	12	12	NUM
ejpam-590	24	10	,	,	PUNCT
ejpam-590	24	11	15	15	NUM
ejpam-590	24	12	]	]	PUNCT
ejpam-590	24	13	,	,	PUNCT
ejpam-590	24	14	the	the	DET
ejpam-590	24	15	back	back	ADJ
ejpam-590	24	16	propagation	propagation	NOUN
ejpam-590	24	17	algorithm	algorithm	NOUN
ejpam-590	24	18	is	be	AUX
ejpam-590	24	19	applied	apply	VERB
ejpam-590	24	20	to	to	PART
ejpam-590	24	21	train	train	VERB
ejpam-590	24	22	a	a	DET
ejpam-590	24	23	feed	feed	NOUN
ejpam-590	24	24	forward	forward	ADV
ejpam-590	24	25	neural	neural	ADJ
ejpam-590	24	26	network	network	NOUN
ejpam-590	24	27	,	,	PUNCT
ejpam-590	24	28	which	which	PRON
ejpam-590	24	29	is	be	AUX
ejpam-590	24	30	based	base	VERB
ejpam-590	24	31	on	on	ADP
ejpam-590	24	32	steepest	steep	ADJ
ejpam-590	24	33	descent	descent	NOUN
ejpam-590	24	34	method	method	NOUN
ejpam-590	24	35	.	.	PUNCT
ejpam-590	25	1	in	in	ADP
ejpam-590	25	2	this	this	DET
ejpam-590	25	3	paper	paper	NOUN
ejpam-590	25	4	a	a	DET
ejpam-590	25	5	similar	similar	ADJ
ejpam-590	25	6	technique	technique	NOUN
ejpam-590	25	7	as	as	ADP
ejpam-590	25	8	that	that	PRON
ejpam-590	25	9	of	of	ADP
ejpam-590	25	10	[	[	X
ejpam-590	25	11	11	11	NUM
ejpam-590	25	12	,	,	PUNCT
ejpam-590	25	13	12	12	NUM
ejpam-590	25	14	,	,	PUNCT
ejpam-590	25	15	15	15	NUM
ejpam-590	25	16	]	]	PUNCT
ejpam-590	25	17	is	be	AUX
ejpam-590	25	18	used	use	VERB
ejpam-590	25	19	to	to	PART
ejpam-590	25	20	approximate	approximate	VERB
ejpam-590	25	21	the	the	DET
ejpam-590	25	22	state	state	NOUN
ejpam-590	25	23	and	and	CCONJ
ejpam-590	25	24	control	control	NOUN
ejpam-590	25	25	terms	term	NOUN
ejpam-590	25	26	,	,	PUNCT
ejpam-590	25	27	that	that	PRON
ejpam-590	25	28	is	be	AUX
ejpam-590	25	29	possible	possible	ADJ
ejpam-590	25	30	due	due	ADP
ejpam-590	25	31	to	to	ADP
ejpam-590	25	32	the	the	DET
ejpam-590	25	33	capability	capability	NOUN
ejpam-590	25	34	of	of	ADP
ejpam-590	25	35	a	a	DET
ejpam-590	25	36	feed	feed	NOUN
ejpam-590	25	37	forward	forward	ADV
ejpam-590	25	38	neural	neural	ADJ
ejpam-590	25	39	network	network	NOUN
ejpam-590	25	40	.	.	PUNCT
ejpam-590	26	1	after	after	ADP
ejpam-590	26	2	the	the	DET
ejpam-590	26	3	approximation	approximation	NOUN
ejpam-590	26	4	,	,	PUNCT
ejpam-590	26	5	above	above	ADP
ejpam-590	26	6	problem	problem	NOUN
ejpam-590	26	7	is	be	AUX
ejpam-590	26	8	converted	convert	VERB
ejpam-590	26	9	into	into	ADP
ejpam-590	26	10	an	an	DET
ejpam-590	26	11	optimization	optimization	NOUN
ejpam-590	26	12	problem	problem	NOUN
ejpam-590	26	13	,	,	PUNCT
ejpam-590	26	14	and	and	CCONJ
ejpam-590	26	15	then	then	ADV
ejpam-590	26	16	for	for	ADP
ejpam-590	26	17	resulting	result	VERB
ejpam-590	26	18	problem	problem	NOUN
ejpam-590	26	19	,	,	PUNCT
ejpam-590	26	20	a	a	DET
ejpam-590	26	21	real	real	ADJ
ejpam-590	26	22	coded	code	VERB
ejpam-590	26	23	ga	ga	NOUN
ejpam-590	26	24	is	be	AUX
ejpam-590	26	25	applied	apply	VERB
ejpam-590	26	26	.	.	PUNCT
ejpam-590	27	1	use	use	NOUN
ejpam-590	27	2	of	of	ADP
ejpam-590	27	3	evolutionary	evolutionary	ADJ
ejpam-590	27	4	techniques	technique	NOUN
ejpam-590	27	5	in	in	ADP
ejpam-590	27	6	control	control	NOUN
ejpam-590	27	7	problems	problem	NOUN
ejpam-590	27	8	is	be	AUX
ejpam-590	27	9	not	not	PART
ejpam-590	27	10	an	an	DET
ejpam-590	27	11	new	new	ADJ
ejpam-590	27	12	idea	idea	NOUN
ejpam-590	27	13	.	.	PUNCT
ejpam-590	28	1	for	for	ADP
ejpam-590	28	2	example	example	NOUN
ejpam-590	28	3	,	,	PUNCT
ejpam-590	28	4	michalewicz	michalewicz	NOUN
ejpam-590	28	5	et	et	PROPN
ejpam-590	28	6	.	.	PUNCT
ejpam-590	29	1	at	at	ADP
ejpam-590	29	2	.	.	PUNCT
ejpam-590	30	1	[	[	X
ejpam-590	30	2	13	13	NUM
ejpam-590	30	3	]	]	PUNCT
ejpam-590	30	4	gave	give	VERB
ejpam-590	30	5	applications	application	NOUN
ejpam-590	30	6	of	of	ADP
ejpam-590	30	7	genetic	genetic	ADJ
ejpam-590	30	8	algorithm	algorithm	NOUN
ejpam-590	30	9	to	to	PART
ejpam-590	30	10	study	study	VERB
ejpam-590	30	11	some	some	DET
ejpam-590	30	12	discrete	discrete	ADJ
ejpam-590	30	13	-	-	PUNCT
ejpam-590	30	14	time	time	NOUN
ejpam-590	30	15	optimal	optimal	ADJ
ejpam-590	30	16	control	control	NOUN
ejpam-590	30	17	problems	problem	NOUN
ejpam-590	30	18	.	.	PUNCT
ejpam-590	31	1	in	in	ADP
ejpam-590	31	2	the	the	DET
ejpam-590	31	3	same	same	ADJ
ejpam-590	31	4	year	year	NOUN
ejpam-590	31	5	,	,	PUNCT
ejpam-590	31	6	krishnakumar	krishnakumar	PROPN
ejpam-590	31	7	and	and	CCONJ
ejpam-590	31	8	goldberg	goldberg	PROPN
ejpam-590	31	9	[	[	X
ejpam-590	31	10	10	10	NUM
ejpam-590	31	11	]	]	PUNCT
ejpam-590	31	12	explored	explore	VERB
ejpam-590	31	13	aerospace	aerospace	NOUN
ejpam-590	31	14	-	-	PUNCT
ejpam-590	31	15	related	relate	VERB
ejpam-590	31	16	control	control	NOUN
ejpam-590	31	17	system	system	NOUN
ejpam-590	31	18	optimization	optimization	NOUN
ejpam-590	31	19	problems	problem	NOUN
ejpam-590	31	20	using	use	VERB
ejpam-590	31	21	genetic	genetic	ADJ
ejpam-590	31	22	algorithms	algorithm	NOUN
ejpam-590	31	23	.	.	PUNCT
ejpam-590	32	1	chang	chang	PROPN
ejpam-590	33	1	[	[	X
ejpam-590	33	2	3	3	NUM
ejpam-590	33	3	]	]	PUNCT
ejpam-590	33	4	applied	apply	VERB
ejpam-590	33	5	a	a	DET
ejpam-590	33	6	real	real	ADV
ejpam-590	33	7	-	-	PUNCT
ejpam-590	33	8	coded	code	VERB
ejpam-590	33	9	genetic	genetic	ADJ
ejpam-590	33	10	algorithm	algorithm	NOUN
ejpam-590	33	11	to	to	ADP
ejpam-590	33	12	the	the	DET
ejpam-590	33	13	system	system	NOUN
ejpam-590	33	14	identification	identification	NOUN
ejpam-590	33	15	and	and	CCONJ
ejpam-590	33	16	control	control	NOUN
ejpam-590	33	17	for	for	ADP
ejpam-590	33	18	a	a	DET
ejpam-590	33	19	class	class	NOUN
ejpam-590	33	20	of	of	ADP
ejpam-590	33	21	nonlinear	nonlinear	ADJ
ejpam-590	33	22	systems	system	NOUN
ejpam-590	33	23	.	.	PUNCT
ejpam-590	34	1	some	some	DET
ejpam-590	34	2	more	more	ADJ
ejpam-590	34	3	applications	application	NOUN
ejpam-590	34	4	of	of	ADP
ejpam-590	34	5	evolutionary	evolutionary	ADJ
ejpam-590	34	6	algorithms	algorithm	NOUN
ejpam-590	34	7	in	in	ADP
ejpam-590	34	8	control	control	NOUN
ejpam-590	34	9	systems	system	NOUN
ejpam-590	34	10	can	can	AUX
ejpam-590	34	11	be	be	AUX
ejpam-590	34	12	seen	see	VERB
ejpam-590	34	13	in	in	ADP
ejpam-590	34	14	[	[	X
ejpam-590	34	15	18	18	NUM
ejpam-590	34	16	,	,	PUNCT
ejpam-590	34	17	1	1	NUM
ejpam-590	34	18	,	,	PUNCT
ejpam-590	34	19	7	7	NUM
ejpam-590	34	20	]	]	PUNCT
ejpam-590	34	21	.	.	PUNCT
ejpam-590	35	1	the	the	DET
ejpam-590	35	2	organization	organization	NOUN
ejpam-590	35	3	of	of	ADP
ejpam-590	35	4	this	this	DET
ejpam-590	35	5	paper	paper	NOUN
ejpam-590	35	6	is	be	AUX
ejpam-590	35	7	as	as	SCONJ
ejpam-590	35	8	follows	follow	VERB
ejpam-590	35	9	.	.	PUNCT
ejpam-590	36	1	next	next	ADJ
ejpam-590	36	2	section	section	NOUN
ejpam-590	36	3	is	be	AUX
ejpam-590	36	4	concerned	concern	VERB
ejpam-590	36	5	with	with	ADP
ejpam-590	36	6	some	some	DET
ejpam-590	36	7	preliminaries	preliminary	NOUN
ejpam-590	36	8	of	of	ADP
ejpam-590	36	9	a	a	DET
ejpam-590	36	10	feedforward	feedforward	ADJ
ejpam-590	36	11	neural	neural	ADJ
ejpam-590	36	12	network	network	NOUN
ejpam-590	36	13	and	and	CCONJ
ejpam-590	36	14	its	its	PRON
ejpam-590	36	15	derivatives	derivative	NOUN
ejpam-590	36	16	formulations	formulation	NOUN
ejpam-590	36	17	,	,	PUNCT
ejpam-590	36	18	which	which	PRON
ejpam-590	36	19	will	will	AUX
ejpam-590	36	20	be	be	AUX
ejpam-590	36	21	useful	useful	ADJ
ejpam-590	36	22	in	in	ADP
ejpam-590	36	23	section	section	NOUN
ejpam-590	36	24	3	3	NUM
ejpam-590	36	25	.	.	PUNCT
ejpam-590	36	26	using	use	VERB
ejpam-590	36	27	ann	ann	PROPN
ejpam-590	36	28	and	and	CCONJ
ejpam-590	36	29	ga	ga	PROPN
ejpam-590	36	30	,	,	PUNCT
ejpam-590	36	31	the	the	DET
ejpam-590	36	32	proposed	propose	VERB
ejpam-590	36	33	hybrid	hybrid	NOUN
ejpam-590	36	34	procedure	procedure	NOUN
ejpam-590	36	35	is	be	AUX
ejpam-590	36	36	described	describe	VERB
ejpam-590	36	37	in	in	ADP
ejpam-590	36	38	the	the	DET
ejpam-590	36	39	section	section	NOUN
ejpam-590	36	40	3	3	NUM
ejpam-590	36	41	.	.	PUNCT
ejpam-590	36	42	numerical	numerical	ADJ
ejpam-590	36	43	example	example	NOUN
ejpam-590	36	44	,	,	PUNCT
ejpam-590	36	45	for	for	ADP
ejpam-590	36	46	two	two	NUM
ejpam-590	36	47	dimensional	dimensional	ADJ
ejpam-590	36	48	linear	linear	ADJ
ejpam-590	36	49	heat	heat	NOUN
ejpam-590	36	50	equation	equation	NOUN
ejpam-590	36	51	,	,	PUNCT
ejpam-590	36	52	illustrates	illustrate	VERB
ejpam-590	36	53	the	the	DET
ejpam-590	36	54	proposed	propose	VERB
ejpam-590	36	55	method	method	NOUN
ejpam-590	36	56	in	in	ADP
ejpam-590	36	57	the	the	DET
ejpam-590	36	58	section	section	NOUN
ejpam-590	36	59	4	4	NUM
ejpam-590	36	60	.	.	PUNCT
ejpam-590	37	1	finally	finally	ADV
ejpam-590	37	2	,	,	PUNCT
ejpam-590	37	3	in	in	ADP
ejpam-590	37	4	the	the	DET
ejpam-590	37	5	last	last	ADJ
ejpam-590	37	6	,	,	PUNCT
ejpam-590	37	7	some	some	DET
ejpam-590	37	8	concluding	conclude	VERB
ejpam-590	37	9	remarks	remark	NOUN
ejpam-590	37	10	are	be	AUX
ejpam-590	37	11	given	give	VERB
ejpam-590	37	12	.	.	PUNCT
ejpam-590	38	1	2	2	X
ejpam-590	38	2	.	.	NUM
ejpam-590	38	3	preliminaries	preliminary	NOUN
ejpam-590	38	4	consider	consider	VERB
ejpam-590	38	5	a	a	DET
ejpam-590	38	6	multilayer	multilayer	ADJ
ejpam-590	38	7	feedforward	feedforward	NOUN
ejpam-590	38	8	neural	neural	ADJ
ejpam-590	38	9	network	network	NOUN
ejpam-590	38	10	,	,	PUNCT
ejpam-590	38	11	with	with	ADP
ejpam-590	38	12	n	n	ADP
ejpam-590	38	13	input	input	NOUN
ejpam-590	38	14	units	unit	NOUN
ejpam-590	38	15	,	,	PUNCT
ejpam-590	38	16	one	one	NUM
ejpam-590	38	17	hidden	hide	VERB
ejpam-590	38	18	layer	layer	NOUN
ejpam-590	38	19	with	with	ADP
ejpam-590	38	20	h	h	NOUN
ejpam-590	38	21	sigmoid	sigmoid	NOUN
ejpam-590	38	22	units	unit	NOUN
ejpam-590	38	23	and	and	CCONJ
ejpam-590	38	24	a	a	DET
ejpam-590	38	25	linear	linear	ADJ
ejpam-590	38	26	output	output	NOUN
ejpam-590	38	27	unit	unit	NOUN
ejpam-590	38	28	.	.	PUNCT
ejpam-590	39	1	for	for	ADP
ejpam-590	39	2	a	a	DET
ejpam-590	39	3	given	give	VERB
ejpam-590	39	4	input	input	NOUN
ejpam-590	39	5	vector	vector	NOUN
ejpam-590	39	6	x	x	X
ejpam-590	39	7	,	,	PUNCT
ejpam-590	39	8	where	where	SCONJ
ejpam-590	39	9	x	x	X
ejpam-590	39	10	=	=	PRON
ejpam-590	39	11	(	(	PUNCT
ejpam-590	39	12	x1	x1	PROPN
ejpam-590	39	13	,	,	PUNCT
ejpam-590	39	14	x2	x2	PROPN
ejpam-590	39	15	,	,	PUNCT
ejpam-590	39	16	.	.	PUNCT
ejpam-590	39	17	.	.	PUNCT
ejpam-590	39	18	.	.	PUNCT
ejpam-590	40	1	,	,	PUNCT
ejpam-590	40	2	xn	xn	PROPN
ejpam-590	40	3	)	)	PUNCT
ejpam-590	40	4	,	,	PUNCT
ejpam-590	40	5	the	the	DET
ejpam-590	40	6	output	output	NOUN
ejpam-590	40	7	of	of	ADP
ejpam-590	40	8	the	the	DET
ejpam-590	40	9	network	network	NOUN
ejpam-590	40	10	is	be	AUX
ejpam-590	40	11	n(x	n(x	PRON
ejpam-590	40	12	)	)	PUNCT
ejpam-590	41	1	=	=	SYM
ejpam-590	41	2	∑h	∑h	PROPN
ejpam-590	41	3	i=1	i=1	PROPN
ejpam-590	41	4	viσ(zi	viσ(zi	NOUN
ejpam-590	41	5	)	)	PUNCT
ejpam-590	41	6	,	,	PUNCT
ejpam-590	41	7	where	where	SCONJ
ejpam-590	41	8	zi	zi	NOUN
ejpam-590	41	9	=	=	PUNCT
ejpam-590	41	10	∑n	∑n	PROPN
ejpam-590	41	11	j=1(wi	j=1(wi	ADJ
ejpam-590	41	12	j	j	PROPN
ejpam-590	41	13	x	x	SYM
ejpam-590	41	14	j	j	PROPN
ejpam-590	41	15	+	+	CCONJ
ejpam-590	41	16	bi	bi	NOUN
ejpam-590	41	17	)	)	PUNCT
ejpam-590	41	18	.	.	PUNCT
ejpam-590	42	1	here	here	ADV
ejpam-590	42	2	,	,	PUNCT
ejpam-590	42	3	wi	wi	PROPN
ejpam-590	42	4	j	j	PROPN
ejpam-590	42	5	denotes	denote	VERB
ejpam-590	42	6	the	the	DET
ejpam-590	42	7	weight	weight	NOUN
ejpam-590	42	8	from	from	ADP
ejpam-590	42	9	the	the	DET
ejpam-590	42	10	input	input	NOUN
ejpam-590	42	11	unit	unit	NOUN
ejpam-590	42	12	j	j	PROPN
ejpam-590	42	13	to	to	ADP
ejpam-590	42	14	the	the	DET
ejpam-590	42	15	hidden	hide	VERB
ejpam-590	42	16	unit	unit	NOUN
ejpam-590	42	17	i	i	PRON
ejpam-590	42	18	,	,	PUNCT
ejpam-590	42	19	vi	vi	PROPN
ejpam-590	42	20	denotes	denote	VERB
ejpam-590	42	21	the	the	DET
ejpam-590	42	22	weight	weight	NOUN
ejpam-590	42	23	from	from	ADP
ejpam-590	42	24	the	the	DET
ejpam-590	42	25	hidden	hide	VERB
ejpam-590	42	26	unit	unit	NOUN
ejpam-590	42	27	i	i	PRON
ejpam-590	42	28	to	to	ADP
ejpam-590	42	29	the	the	DET
ejpam-590	42	30	output	output	NOUN
ejpam-590	42	31	,	,	PUNCT
ejpam-590	42	32	bi	bi	NOUN
ejpam-590	42	33	denotes	denote	VERB
ejpam-590	42	34	the	the	DET
ejpam-590	42	35	bias	bias	NOUN
ejpam-590	42	36	of	of	ADP
ejpam-590	42	37	hidden	hide	VERB
ejpam-590	42	38	unit	unit	NOUN
ejpam-590	42	39	i.	i.	PROPN
ejpam-590	42	40	σ(z	σ(z	PROPN
ejpam-590	42	41	)	)	PUNCT
ejpam-590	42	42	=	=	PUNCT
ejpam-590	43	1	1/(1	1/(1	NUM
ejpam-590	43	2	+	+	NUM
ejpam-590	43	3	e−z	e−z	NOUN
ejpam-590	43	4	)	)	PUNCT
ejpam-590	43	5	is	be	AUX
ejpam-590	43	6	the	the	DET
ejpam-590	43	7	sigmoid	sigmoid	NOUN
ejpam-590	43	8	transfer	transfer	NOUN
ejpam-590	43	9	function	function	NOUN
ejpam-590	43	10	.	.	PUNCT
ejpam-590	44	1	it	it	PRON
ejpam-590	44	2	is	be	AUX
ejpam-590	44	3	straightforward	straightforward	ADJ
ejpam-590	44	4	to	to	PART
ejpam-590	44	5	show	show	VERB
ejpam-590	44	6	that	that	PRON
ejpam-590	44	7	∂	∂	NUM
ejpam-590	44	8	kn	kn	PROPN
ejpam-590	44	9	∂	∂	NOUN
ejpam-590	44	10	x	x	X
ejpam-590	45	1	k	k	PROPN
ejpam-590	45	2	j	j	PROPN
ejpam-590	46	1	=	=	PUNCT
ejpam-590	46	2	h∑	h∑	ADP
ejpam-590	46	3	i=1	i=1	PROPN
ejpam-590	46	4	viw	viw	PROPN
ejpam-590	47	1	k	k	PROPN
ejpam-590	48	1	i	i	PRON
ejpam-590	48	2	jσ	jσ	INTJ
ejpam-590	49	1	k	k	PROPN
ejpam-590	49	2	i	i	PRON
ejpam-590	49	3	n.	n.	PROPN
ejpam-590	49	4	tomar	tomar	PROPN
ejpam-590	49	5	,	,	PUNCT
ejpam-590	49	6	n.	n.	NOUN
ejpam-590	49	7	sukavanam	sukavanam	NOUN
ejpam-590	49	8	,	,	PUNCT
ejpam-590	49	9	k.	k.	PROPN
ejpam-590	49	10	singh	singh	PROPN
ejpam-590	49	11	/	/	SYM
ejpam-590	49	12	eur	eur	PROPN
ejpam-590	49	13	.	.	PUNCT
ejpam-590	50	1	j.	j.	PROPN
ejpam-590	50	2	pure	pure	PROPN
ejpam-590	50	3	appl	appl	PROPN
ejpam-590	50	4	.	.	PROPN
ejpam-590	50	5	math	math	PROPN
ejpam-590	50	6	,	,	PUNCT
ejpam-590	50	7	4	4	NUM
ejpam-590	50	8	(	(	PUNCT
ejpam-590	50	9	2011	2011	NUM
ejpam-590	50	10	)	)	PUNCT
ejpam-590	50	11	,	,	PUNCT
ejpam-590	50	12	117	117	NUM
ejpam-590	50	13	-	-	SYM
ejpam-590	50	14	128	128	NUM
ejpam-590	50	15	119	119	NUM
ejpam-590	50	16	where	where	SCONJ
ejpam-590	50	17	σi	σi	NOUN
ejpam-590	50	18	=	=	PUNCT
ejpam-590	50	19	σ(zi	σ(zi	X
ejpam-590	50	20	)	)	PUNCT
ejpam-590	50	21	and	and	CCONJ
ejpam-590	50	22	σ(k	σ(k	NOUN
ejpam-590	50	23	)	)	PUNCT
ejpam-590	50	24	denote	denote	VERB
ejpam-590	50	25	the	the	DET
ejpam-590	50	26	kth	kth	NOUN
ejpam-590	50	27	-	-	PUNCT
ejpam-590	50	28	order	order	NOUN
ejpam-590	50	29	derivative	derivative	NOUN
ejpam-590	50	30	of	of	ADP
ejpam-590	50	31	the	the	DET
ejpam-590	50	32	sigmoid	sigmoid	NOUN
ejpam-590	50	33	function	function	NOUN
ejpam-590	50	34	.	.	PUNCT
ejpam-590	51	1	moreover	moreover	ADV
ejpam-590	51	2	,	,	PUNCT
ejpam-590	51	3	∂	∂	NOUN
ejpam-590	51	4	λ1	λ1	PROPN
ejpam-590	51	5	∂	∂	NOUN
ejpam-590	51	6	x	x	SYM
ejpam-590	51	7	λ1	λ1	PROPN
ejpam-590	51	8	1	1	NUM
ejpam-590	51	9	·	·	SYM
ejpam-590	51	10	∂	∂	NUM
ejpam-590	51	11	λ2	λ2	NOUN
ejpam-590	51	12	∂	∂	NOUN
ejpam-590	51	13	x	x	SYM
ejpam-590	51	14	λ2	λ2	NOUN
ejpam-590	51	15	2	2	NUM
ejpam-590	51	16	.	.	PUNCT
ejpam-590	51	17	.	.	PUNCT
ejpam-590	51	18	.	.	PUNCT
ejpam-590	52	1	∂	∂	NUM
ejpam-590	53	1	λn	λn	NOUN
ejpam-590	53	2	∂	∂	NOUN
ejpam-590	53	3	x	x	NOUN
ejpam-590	53	4	λn	λn	PROPN
ejpam-590	53	5	n	n	CCONJ
ejpam-590	53	6	n	n	NOUN
ejpam-590	53	7	=	=	NOUN
ejpam-590	53	8	h∑	h∑	ADP
ejpam-590	53	9	i=1	i=1	NOUN
ejpam-590	53	10	viρiσ	viρiσ	VERB
ejpam-590	53	11	α	α	INTJ
ejpam-590	53	12	i	i	PRON
ejpam-590	53	13	(	(	PUNCT
ejpam-590	53	14	2	2	NUM
ejpam-590	53	15	)	)	PUNCT
ejpam-590	53	16	where	where	SCONJ
ejpam-590	53	17	ρi	ρi	NOUN
ejpam-590	53	18	=	=	PRON
ejpam-590	53	19	∏n	∏n	PROPN
ejpam-590	53	20	k=1	k=1	X
ejpam-590	53	21	w	w	X
ejpam-590	53	22	λk	λk	PROPN
ejpam-590	53	23	ik	ik	PROPN
ejpam-590	53	24	and	and	CCONJ
ejpam-590	53	25	α	α	NOUN
ejpam-590	53	26	=	=	SYM
ejpam-590	53	27	∑n	∑n	PROPN
ejpam-590	53	28	i=1λi	i=1λi	X
ejpam-590	53	29	.	.	PUNCT
ejpam-590	54	1	equation	equation	NOUN
ejpam-590	54	2	(	(	PUNCT
ejpam-590	54	3	2	2	X
ejpam-590	54	4	)	)	PUNCT
ejpam-590	54	5	indicates	indicate	VERB
ejpam-590	54	6	that	that	SCONJ
ejpam-590	54	7	the	the	DET
ejpam-590	54	8	derivative	derivative	NOUN
ejpam-590	54	9	of	of	ADP
ejpam-590	54	10	the	the	DET
ejpam-590	54	11	network	network	NOUN
ejpam-590	54	12	n	n	X
ejpam-590	54	13	with	with	ADP
ejpam-590	54	14	respect	respect	NOUN
ejpam-590	54	15	to	to	ADP
ejpam-590	54	16	any	any	PRON
ejpam-590	54	17	of	of	ADP
ejpam-590	54	18	its	its	PRON
ejpam-590	54	19	inputs	input	NOUN
ejpam-590	54	20	is	be	AUX
ejpam-590	54	21	equivalent	equivalent	ADJ
ejpam-590	54	22	to	to	ADP
ejpam-590	54	23	a	a	DET
ejpam-590	54	24	feedforward	feedforward	ADJ
ejpam-590	54	25	neural	neural	ADJ
ejpam-590	54	26	network	network	NOUN
ejpam-590	54	27	with	with	ADP
ejpam-590	54	28	one	one	NUM
ejpam-590	54	29	hidden	hide	VERB
ejpam-590	54	30	layer	layer	NOUN
ejpam-590	54	31	,	,	PUNCT
ejpam-590	54	32	having	have	VERB
ejpam-590	54	33	the	the	DET
ejpam-590	54	34	same	same	ADJ
ejpam-590	54	35	values	value	NOUN
ejpam-590	54	36	for	for	ADP
ejpam-590	54	37	the	the	DET
ejpam-590	54	38	weights	weight	NOUN
ejpam-590	54	39	,	,	PUNCT
ejpam-590	54	40	as	as	ADP
ejpam-590	54	41	n	n	PROPN
ejpam-590	54	42	,	,	PUNCT
ejpam-590	54	43	wi	wi	PROPN
ejpam-590	54	44	j	j	PROPN
ejpam-590	54	45	and	and	CCONJ
ejpam-590	54	46	thresholds	threshold	VERB
ejpam-590	54	47	bi	bi	PROPN
ejpam-590	54	48	and	and	CCONJ
ejpam-590	54	49	each	each	DET
ejpam-590	54	50	vi	vi	NOUN
ejpam-590	54	51	being	be	AUX
ejpam-590	54	52	replaced	replace	VERB
ejpam-590	54	53	with	with	ADP
ejpam-590	54	54	viρi	viρi	NOUN
ejpam-590	54	55	.	.	PUNCT
ejpam-590	55	1	the	the	DET
ejpam-590	55	2	transfer	transfer	NOUN
ejpam-590	55	3	function	function	NOUN
ejpam-590	55	4	of	of	ADP
ejpam-590	55	5	each	each	DET
ejpam-590	55	6	hidden	hide	VERB
ejpam-590	55	7	unit	unit	NOUN
ejpam-590	55	8	is	be	AUX
ejpam-590	55	9	replaced	replace	VERB
ejpam-590	55	10	with	with	ADP
ejpam-590	55	11	the	the	DET
ejpam-590	55	12	αth	αth	NUM
ejpam-590	55	13	order	order	NOUN
ejpam-590	55	14	derivative	derivative	NOUN
ejpam-590	55	15	of	of	ADP
ejpam-590	55	16	the	the	DET
ejpam-590	55	17	sigmoid	sigmoid	NOUN
ejpam-590	55	18	.	.	PUNCT
ejpam-590	56	1	one	one	NUM
ejpam-590	56	2	of	of	ADP
ejpam-590	56	3	the	the	DET
ejpam-590	56	4	main	main	ADJ
ejpam-590	56	5	uses	use	NOUN
ejpam-590	56	6	of	of	ADP
ejpam-590	56	7	the	the	DET
ejpam-590	56	8	feed	feed	NOUN
ejpam-590	56	9	forward	forward	ADV
ejpam-590	56	10	neural	neural	ADJ
ejpam-590	56	11	network	network	NOUN
ejpam-590	56	12	is	be	AUX
ejpam-590	56	13	the	the	DET
ejpam-590	56	14	approximation	approximation	NOUN
ejpam-590	56	15	of	of	ADP
ejpam-590	56	16	any	any	DET
ejpam-590	56	17	function	function	NOUN
ejpam-590	56	18	.	.	PUNCT
ejpam-590	57	1	in	in	ADP
ejpam-590	57	2	the	the	DET
ejpam-590	57	3	current	current	ADJ
ejpam-590	57	4	effort	effort	NOUN
ejpam-590	57	5	,	,	PUNCT
ejpam-590	57	6	a	a	DET
ejpam-590	57	7	feed	feed	NOUN
ejpam-590	57	8	forward	forward	ADV
ejpam-590	57	9	neural	neural	ADJ
ejpam-590	57	10	network	network	NOUN
ejpam-590	57	11	with	with	ADP
ejpam-590	57	12	three	three	NUM
ejpam-590	57	13	input	input	NOUN
ejpam-590	57	14	units	unit	NOUN
ejpam-590	57	15	,	,	PUNCT
ejpam-590	57	16	one	one	NUM
ejpam-590	57	17	hidden	hide	VERB
ejpam-590	57	18	layer	layer	NOUN
ejpam-590	57	19	having	have	VERB
ejpam-590	57	20	six	six	NUM
ejpam-590	57	21	nodes	node	NOUN
ejpam-590	57	22	(	(	PUNCT
ejpam-590	57	23	with	with	ADP
ejpam-590	57	24	bias	bias	NOUN
ejpam-590	57	25	at	at	ADP
ejpam-590	57	26	each	each	DET
ejpam-590	57	27	node	node	NOUN
ejpam-590	57	28	)	)	PUNCT
ejpam-590	57	29	and	and	CCONJ
ejpam-590	57	30	one	one	NUM
ejpam-590	57	31	output	output	NOUN
ejpam-590	57	32	unit	unit	NOUN
ejpam-590	57	33	is	be	AUX
ejpam-590	57	34	used	use	VERB
ejpam-590	57	35	to	to	PART
ejpam-590	57	36	approximate	approximate	VERB
ejpam-590	57	37	both	both	CCONJ
ejpam-590	57	38	the	the	DET
ejpam-590	57	39	temperature	temperature	NOUN
ejpam-590	57	40	and	and	CCONJ
ejpam-590	57	41	the	the	DET
ejpam-590	57	42	control	control	NOUN
ejpam-590	57	43	functions	function	NOUN
ejpam-590	57	44	separately	separately	ADV
ejpam-590	57	45	.	.	PUNCT
ejpam-590	58	1	3	3	X
ejpam-590	58	2	.	.	X
ejpam-590	58	3	method	method	NOUN
ejpam-590	58	4	of	of	ADP
ejpam-590	58	5	computation	computation	NOUN
ejpam-590	58	6	of	of	ADP
ejpam-590	58	7	boundary	boundary	ADJ
ejpam-590	58	8	control	control	NOUN
ejpam-590	58	9	first	first	ADV
ejpam-590	58	10	,	,	PUNCT
ejpam-590	58	11	we	we	PRON
ejpam-590	58	12	assume	assume	VERB
ejpam-590	58	13	the	the	DET
ejpam-590	58	14	discretization	discretization	NOUN
ejpam-590	58	15	of	of	ADP
ejpam-590	58	16	domain	domain	NOUN
ejpam-590	58	17	q	q	NOUN
ejpam-590	59	1	=	=	SYM
ejpam-590	59	2	ω×	ω×	X
ejpam-590	59	3	(	(	PUNCT
ejpam-590	59	4	0,τ	0,τ	NUM
ejpam-590	59	5	)	)	PUNCT
ejpam-590	59	6	and	and	CCONJ
ejpam-590	59	7	its	its	PRON
ejpam-590	59	8	boundary∑	boundary∑	NOUN
ejpam-590	59	9	=	=	SYM
ejpam-590	59	10	γ×	γ×	PROPN
ejpam-590	59	11	(	(	PUNCT
ejpam-590	59	12	0,τ	0,τ	NOUN
ejpam-590	59	13	)	)	PUNCT
ejpam-590	59	14	into	into	ADP
ejpam-590	59	15	a	a	DET
ejpam-590	59	16	set	set	NOUN
ejpam-590	59	17	of	of	ADP
ejpam-590	59	18	points	point	NOUN
ejpam-590	59	19	q̂	q̂	NUM
ejpam-590	59	20	=	=	X
ejpam-590	59	21	ω×	ω×	X
ejpam-590	59	22	(	(	PUNCT
ejpam-590	59	23	t0	t0	X
ejpam-590	59	24	=	=	SYM
ejpam-590	59	25	0	0	NUM
ejpam-590	59	26	,	,	PUNCT
ejpam-590	59	27	t1	t1	NOUN
ejpam-590	59	28	,	,	PUNCT
ejpam-590	59	29	t2	t2	NOUN
ejpam-590	59	30	,	,	PUNCT
ejpam-590	59	31	.	.	PUNCT
ejpam-590	59	32	.	.	PUNCT
ejpam-590	59	33	.	.	PUNCT
ejpam-590	60	1	,	,	PUNCT
ejpam-590	60	2	tk	tk	PROPN
ejpam-590	60	3	=	=	SYM
ejpam-590	60	4	τ	τ	PROPN
ejpam-590	60	5	)	)	PUNCT
ejpam-590	60	6	and∑̂	and∑̂	PROPN
ejpam-590	60	7	=	=	SYM
ejpam-590	61	1	γ×	γ×	PROPN
ejpam-590	61	2	(	(	PUNCT
ejpam-590	61	3	t0	t0	X
ejpam-590	61	4	=	=	SYM
ejpam-590	61	5	0	0	NUM
ejpam-590	61	6	,	,	PUNCT
ejpam-590	61	7	t1	t1	NOUN
ejpam-590	61	8	,	,	PUNCT
ejpam-590	61	9	t2	t2	NOUN
ejpam-590	61	10	,	,	PUNCT
ejpam-590	61	11	.	.	PUNCT
ejpam-590	61	12	.	.	PUNCT
ejpam-590	62	1	.	.	PUNCT
ejpam-590	63	1	,	,	PUNCT
ejpam-590	63	2	tk	tk	PROPN
ejpam-590	63	3	=	=	SYM
ejpam-590	63	4	τ	τ	PROPN
ejpam-590	63	5	)	)	PUNCT
ejpam-590	63	6	where	where	SCONJ
ejpam-590	63	7	ω	ω	NUM
ejpam-590	63	8	and	and	CCONJ
ejpam-590	63	9	γ	γ	PROPN
ejpam-590	63	10	denote	denote	VERB
ejpam-590	63	11	the	the	DET
ejpam-590	63	12	set	set	NOUN
ejpam-590	63	13	of	of	ADP
ejpam-590	63	14	grid	grid	NOUN
ejpam-590	63	15	points	point	NOUN
ejpam-590	63	16	in	in	ADP
ejpam-590	63	17	ω	ω	PROPN
ejpam-590	63	18	and	and	CCONJ
ejpam-590	63	19	γ	γ	NOUN
ejpam-590	63	20	respectively	respectively	ADV
ejpam-590	63	21	and	and	CCONJ
ejpam-590	63	22	t0	t0	PROPN
ejpam-590	63	23	,	,	PUNCT
ejpam-590	63	24	t1	t1	NOUN
ejpam-590	63	25	,	,	PUNCT
ejpam-590	63	26	t2	t2	NOUN
ejpam-590	63	27	,	,	PUNCT
ejpam-590	63	28	.	.	PUNCT
ejpam-590	63	29	.	.	PUNCT
ejpam-590	63	30	.	.	PUNCT
ejpam-590	64	1	,	,	PUNCT
ejpam-590	64	2	tk	tk	PROPN
ejpam-590	64	3	are	be	AUX
ejpam-590	64	4	discrete	discrete	ADJ
ejpam-590	64	5	points	point	NOUN
ejpam-590	64	6	of	of	ADP
ejpam-590	64	7	the	the	DET
ejpam-590	64	8	interval	interval	NOUN
ejpam-590	64	9	[	[	X
ejpam-590	64	10	0	0	NUM
ejpam-590	64	11	,	,	PUNCT
ejpam-590	64	12	τ	τ	PROPN
ejpam-590	64	13	]	]	X
ejpam-590	64	14	.	.	PUNCT
ejpam-590	65	1	now	now	ADV
ejpam-590	65	2	the	the	DET
ejpam-590	65	3	problem	problem	NOUN
ejpam-590	65	4	(	(	PUNCT
ejpam-590	65	5	1	1	X
ejpam-590	65	6	)	)	PUNCT
ejpam-590	65	7	is	be	AUX
ejpam-590	65	8	transformed	transform	VERB
ejpam-590	65	9	into	into	ADP
ejpam-590	65	10	the	the	DET
ejpam-590	65	11	solution	solution	NOUN
ejpam-590	65	12	of	of	ADP
ejpam-590	65	13	following	follow	VERB
ejpam-590	65	14	system	system	NOUN
ejpam-590	65	15	of	of	ADP
ejpam-590	65	16	equations	equation	NOUN
ejpam-590	65	17	∂ω(x	∂ω(x	PROPN
ejpam-590	65	18	,	,	PUNCT
ejpam-590	65	19	t	t	PROPN
ejpam-590	65	20	)	)	PUNCT
ejpam-590	65	21	∂	∂	NUM
ejpam-590	66	1	t	t	NOUN
ejpam-590	66	2	−	−	PROPN
ejpam-590	66	3	c2∆ω(x	c2∆ω(x	ADJ
ejpam-590	66	4	,	,	PUNCT
ejpam-590	66	5	t)−φ	t)−φ	PROPN
ejpam-590	66	6	(	(	PUNCT
ejpam-590	66	7	t	t	PROPN
ejpam-590	66	8	,	,	PUNCT
ejpam-590	66	9	ω(x	ω(x	X
ejpam-590	66	10	,	,	PUNCT
ejpam-590	66	11	t	t	PROPN
ejpam-590	66	12	)	)	PUNCT
ejpam-590	66	13	)	)	PUNCT
ejpam-590	67	1	=	=	PUNCT
ejpam-590	67	2	0	0	NUM
ejpam-590	67	3	;	;	PUNCT
ejpam-590	67	4	∀(x	∀(x	NUM
ejpam-590	67	5	,	,	PUNCT
ejpam-590	67	6	t	t	X
ejpam-590	67	7	)	)	PUNCT
ejpam-590	67	8	∈	∈	NOUN
ejpam-590	67	9	q̂	q̂	X
ejpam-590	67	10	(	(	PUNCT
ejpam-590	67	11	3	3	X
ejpam-590	67	12	)	)	PUNCT
ejpam-590	67	13	subject	subject	NOUN
ejpam-590	67	14	to	to	ADP
ejpam-590	67	15	the	the	DET
ejpam-590	67	16	given	give	VERB
ejpam-590	67	17	initial	initial	ADJ
ejpam-590	67	18	and	and	CCONJ
ejpam-590	67	19	final	final	ADJ
ejpam-590	67	20	conditions	condition	NOUN
ejpam-590	67	21	.	.	PUNCT
ejpam-590	68	1	in	in	ADP
ejpam-590	68	2	the	the	DET
ejpam-590	68	3	proposed	propose	VERB
ejpam-590	68	4	approach	approach	NOUN
ejpam-590	68	5	,	,	PUNCT
ejpam-590	68	6	we	we	PRON
ejpam-590	68	7	construct	construct	VERB
ejpam-590	68	8	a	a	DET
ejpam-590	68	9	trial	trial	NOUN
ejpam-590	68	10	solution	solution	NOUN
ejpam-590	68	11	with	with	ADP
ejpam-590	68	12	adjustable	adjustable	ADJ
ejpam-590	68	13	parameters	parameter	NOUN
ejpam-590	68	14	.	.	PUNCT
ejpam-590	69	1	this	this	DET
ejpam-590	69	2	trial	trial	NOUN
ejpam-590	69	3	solution	solution	NOUN
ejpam-590	69	4	is	be	AUX
ejpam-590	69	5	written	write	VERB
ejpam-590	69	6	as	as	ADP
ejpam-590	69	7	a	a	DET
ejpam-590	69	8	sum	sum	NOUN
ejpam-590	69	9	of	of	ADP
ejpam-590	69	10	two	two	NUM
ejpam-590	69	11	parts	part	NOUN
ejpam-590	69	12	.	.	PUNCT
ejpam-590	70	1	the	the	DET
ejpam-590	70	2	first	first	ADJ
ejpam-590	70	3	part	part	NOUN
ejpam-590	70	4	is	be	AUX
ejpam-590	70	5	constructed	construct	VERB
ejpam-590	70	6	to	to	PART
ejpam-590	70	7	satisfy	satisfy	VERB
ejpam-590	70	8	,	,	PUNCT
ejpam-590	70	9	the	the	DET
ejpam-590	70	10	known	know	VERB
ejpam-590	70	11	initial	initial	ADJ
ejpam-590	70	12	and	and	CCONJ
ejpam-590	70	13	final	final	ADJ
ejpam-590	70	14	conditions	condition	NOUN
ejpam-590	70	15	,	,	PUNCT
ejpam-590	70	16	and	and	CCONJ
ejpam-590	70	17	the	the	DET
ejpam-590	70	18	unknown	unknown	ADJ
ejpam-590	70	19	boundary	boundary	ADJ
ejpam-590	70	20	conditions	condition	NOUN
ejpam-590	70	21	in	in	ADP
ejpam-590	70	22	the	the	DET
ejpam-590	70	23	form	form	NOUN
ejpam-590	70	24	of	of	ADP
ejpam-590	70	25	a	a	DET
ejpam-590	70	26	feedforward	feedforward	ADJ
ejpam-590	70	27	neural	neural	ADJ
ejpam-590	70	28	network	network	NOUN
ejpam-590	70	29	.	.	PUNCT
ejpam-590	71	1	the	the	DET
ejpam-590	71	2	second	second	ADJ
ejpam-590	71	3	part	part	NOUN
ejpam-590	71	4	is	be	AUX
ejpam-590	71	5	also	also	ADV
ejpam-590	71	6	a	a	DET
ejpam-590	71	7	feedforward	feedforward	ADJ
ejpam-590	71	8	neural	neural	ADJ
ejpam-590	71	9	network	network	NOUN
ejpam-590	71	10	with	with	ADP
ejpam-590	71	11	adjustable	adjustable	ADJ
ejpam-590	71	12	weights	weight	NOUN
ejpam-590	71	13	.	.	PUNCT
ejpam-590	72	1	it	it	PRON
ejpam-590	72	2	is	be	AUX
ejpam-590	72	3	constructed	construct	VERB
ejpam-590	72	4	in	in	ADP
ejpam-590	72	5	a	a	DET
ejpam-590	72	6	way	way	NOUN
ejpam-590	72	7	so	so	SCONJ
ejpam-590	72	8	as	as	SCONJ
ejpam-590	72	9	not	not	PART
ejpam-590	72	10	to	to	PART
ejpam-590	72	11	affect	affect	VERB
ejpam-590	72	12	the	the	DET
ejpam-590	72	13	given	give	VERB
ejpam-590	72	14	conditions	condition	NOUN
ejpam-590	72	15	.	.	PUNCT
ejpam-590	73	1	if	if	SCONJ
ejpam-590	73	2	ωtr(x	ωtr(x	PROPN
ejpam-590	73	3	,	,	PUNCT
ejpam-590	73	4	t	t	PROPN
ejpam-590	73	5	)	)	PUNCT
ejpam-590	73	6	denotes	denote	VERB
ejpam-590	73	7	the	the	DET
ejpam-590	73	8	trial	trial	NOUN
ejpam-590	73	9	solution	solution	NOUN
ejpam-590	73	10	with	with	ADP
ejpam-590	73	11	adjustable	adjustable	ADJ
ejpam-590	73	12	weight	weight	NOUN
ejpam-590	73	13	vector	vector	NOUN
ejpam-590	73	14	p	p	NOUN
ejpam-590	73	15	then	then	ADV
ejpam-590	73	16	it	it	PRON
ejpam-590	73	17	is	be	AUX
ejpam-590	73	18	written	write	VERB
ejpam-590	73	19	as	as	ADP
ejpam-590	73	20	ωtr(x	ωtr(x	PROPN
ejpam-590	73	21	,	,	PUNCT
ejpam-590	73	22	t	t	PROPN
ejpam-590	73	23	,	,	PUNCT
ejpam-590	73	24	p	p	NOUN
ejpam-590	73	25	)	)	PUNCT
ejpam-590	73	26	=	=	SYM
ejpam-590	73	27	a(x	a(x	PROPN
ejpam-590	73	28	,	,	PUNCT
ejpam-590	73	29	t	t	PROPN
ejpam-590	73	30	,	,	PUNCT
ejpam-590	73	31	n1(x	n1(x	PROPN
ejpam-590	73	32	,	,	PUNCT
ejpam-590	73	33	t	t	PROPN
ejpam-590	73	34	,	,	PUNCT
ejpam-590	73	35	p1	p1	PROPN
ejpam-590	73	36	)	)	PUNCT
ejpam-590	73	37	)	)	PUNCT
ejpam-590	74	1	+	+	CCONJ
ejpam-590	74	2	b(x	b(x	PROPN
ejpam-590	74	3	,	,	PUNCT
ejpam-590	74	4	t	t	PROPN
ejpam-590	74	5	,	,	PUNCT
ejpam-590	74	6	n2(x	n2(x	PROPN
ejpam-590	74	7	,	,	PUNCT
ejpam-590	74	8	t	t	PROPN
ejpam-590	74	9	,	,	PUNCT
ejpam-590	74	10	p2	p2	PROPN
ejpam-590	74	11	)	)	PUNCT
ejpam-590	74	12	)	)	PUNCT
ejpam-590	74	13	(	(	PUNCT
ejpam-590	74	14	4	4	X
ejpam-590	74	15	)	)	PUNCT
ejpam-590	74	16	where	where	SCONJ
ejpam-590	74	17	(	(	PUNCT
ejpam-590	74	18	x	x	X
ejpam-590	74	19	,	,	PUNCT
ejpam-590	74	20	t	t	PROPN
ejpam-590	74	21	)	)	PUNCT
ejpam-590	74	22	∈	∈	NOUN
ejpam-590	74	23	q̂	q̂	X
ejpam-590	74	24	and	and	CCONJ
ejpam-590	74	25	p	p	NOUN
ejpam-590	74	26	=	=	PUNCT
ejpam-590	75	1	[	[	X
ejpam-590	75	2	p1	p1	NOUN
ejpam-590	75	3	,	,	PUNCT
ejpam-590	75	4	p2	p2	PROPN
ejpam-590	75	5	]	]	PUNCT
ejpam-590	75	6	.	.	PUNCT
ejpam-590	76	1	the	the	DET
ejpam-590	76	2	control	control	NOUN
ejpam-590	76	3	term	term	NOUN
ejpam-590	76	4	is	be	AUX
ejpam-590	76	5	approximated	approximate	VERB
ejpam-590	76	6	by	by	ADP
ejpam-590	76	7	an	an	DET
ejpam-590	76	8	another	another	DET
ejpam-590	76	9	feedforward	feedforward	ADJ
ejpam-590	76	10	neural	neural	ADJ
ejpam-590	76	11	network	network	NOUN
ejpam-590	76	12	.	.	PUNCT
ejpam-590	77	1	a	a	DET
ejpam-590	77	2	general	general	ADJ
ejpam-590	77	3	description	description	NOUN
ejpam-590	77	4	of	of	ADP
ejpam-590	77	5	the	the	DET
ejpam-590	77	6	network	network	NOUN
ejpam-590	77	7	approximating	approximate	VERB
ejpam-590	77	8	the	the	DET
ejpam-590	77	9	boundary	boundary	ADJ
ejpam-590	77	10	control	control	NOUN
ejpam-590	77	11	function	function	NOUN
ejpam-590	77	12	is	be	AUX
ejpam-590	77	13	not	not	PART
ejpam-590	77	14	easy	easy	ADJ
ejpam-590	77	15	.	.	PUNCT
ejpam-590	78	1	it	it	PRON
ejpam-590	78	2	is	be	AUX
ejpam-590	78	3	clear	clear	ADJ
ejpam-590	78	4	from	from	ADP
ejpam-590	78	5	the	the	DET
ejpam-590	78	6	example	example	NOUN
ejpam-590	78	7	given	give	VERB
ejpam-590	78	8	below	below	ADP
ejpam-590	78	9	that	that	PRON
ejpam-590	78	10	the	the	DET
ejpam-590	78	11	form	form	NOUN
ejpam-590	78	12	of	of	ADP
ejpam-590	78	13	network	network	NOUN
ejpam-590	78	14	depends	depend	VERB
ejpam-590	78	15	on	on	ADP
ejpam-590	78	16	the	the	DET
ejpam-590	78	17	shape	shape	NOUN
ejpam-590	78	18	of	of	ADP
ejpam-590	78	19	boundary	boundary	NOUN
ejpam-590	78	20	.	.	PUNCT
ejpam-590	79	1	now	now	ADV
ejpam-590	79	2	the	the	DET
ejpam-590	79	3	problem	problem	NOUN
ejpam-590	79	4	of	of	ADP
ejpam-590	79	5	solving	solve	VERB
ejpam-590	79	6	the	the	DET
ejpam-590	79	7	system	system	NOUN
ejpam-590	79	8	of	of	ADP
ejpam-590	79	9	equation	equation	NOUN
ejpam-590	79	10	(	(	PUNCT
ejpam-590	79	11	3	3	X
ejpam-590	79	12	)	)	PUNCT
ejpam-590	79	13	is	be	AUX
ejpam-590	79	14	transformed	transform	VERB
ejpam-590	79	15	to	to	ADP
ejpam-590	79	16	the	the	DET
ejpam-590	79	17	following	follow	VERB
ejpam-590	79	18	minimization	minimization	NOUN
ejpam-590	79	19	problem	problem	NOUN
ejpam-590	79	20	e	e	PROPN
ejpam-590	80	1	=	=	NOUN
ejpam-590	80	2	min	min	NOUN
ejpam-590	80	3	p	p	NOUN
ejpam-590	80	4	∑	∑	PROPN
ejpam-590	80	5	(	(	PUNCT
ejpam-590	80	6	x	x	INTJ
ejpam-590	80	7	,	,	PUNCT
ejpam-590	80	8	t)∈q̂	t)∈q̂	NOUN
ejpam-590	80	9	{	{	PUNCT
ejpam-590	80	10	∂ωtr(x	∂ωtr(x	X
ejpam-590	80	11	,	,	PUNCT
ejpam-590	80	12	t	t	PROPN
ejpam-590	80	13	,	,	PUNCT
ejpam-590	80	14	p	p	NOUN
ejpam-590	80	15	)	)	PUNCT
ejpam-590	80	16	∂	∂	NUM
ejpam-590	80	17	t	t	NOUN
ejpam-590	80	18	−	−	PROPN
ejpam-590	80	19	c2∆ωtr(x	c2∆ωtr(x	PROPN
ejpam-590	80	20	,	,	PUNCT
ejpam-590	80	21	t	t	PROPN
ejpam-590	80	22	,	,	PUNCT
ejpam-590	80	23	p)−φ(t	p)−φ(t	PROPN
ejpam-590	80	24	,	,	PUNCT
ejpam-590	80	25	ωtr(x	ωtr(x	PROPN
ejpam-590	80	26	,	,	PUNCT
ejpam-590	80	27	t	t	PROPN
ejpam-590	80	28	,	,	PUNCT
ejpam-590	80	29	p))}2	p))}2	X
ejpam-590	80	30	(	(	PUNCT
ejpam-590	80	31	5	5	X
ejpam-590	80	32	)	)	PUNCT
ejpam-590	80	33	n.	n.	NOUN
ejpam-590	80	34	tomar	tomar	NOUN
ejpam-590	80	35	,	,	PUNCT
ejpam-590	80	36	n.	n.	NOUN
ejpam-590	80	37	sukavanam	sukavanam	NOUN
ejpam-590	80	38	,	,	PUNCT
ejpam-590	80	39	k.	k.	PROPN
ejpam-590	80	40	singh	singh	PROPN
ejpam-590	80	41	/	/	SYM
ejpam-590	80	42	eur	eur	PROPN
ejpam-590	80	43	.	.	PUNCT
ejpam-590	81	1	j.	j.	PROPN
ejpam-590	81	2	pure	pure	PROPN
ejpam-590	81	3	appl	appl	PROPN
ejpam-590	81	4	.	.	PROPN
ejpam-590	81	5	math	math	PROPN
ejpam-590	81	6	,	,	PUNCT
ejpam-590	81	7	4	4	NUM
ejpam-590	81	8	(	(	PUNCT
ejpam-590	81	9	2011	2011	NUM
ejpam-590	81	10	)	)	PUNCT
ejpam-590	81	11	,	,	PUNCT
ejpam-590	81	12	117	117	NUM
ejpam-590	81	13	-	-	SYM
ejpam-590	81	14	128	128	NUM
ejpam-590	81	15	120	120	NUM
ejpam-590	81	16	the	the	DET
ejpam-590	81	17	weight	weight	NOUN
ejpam-590	81	18	parameters	parameter	NOUN
ejpam-590	81	19	are	be	AUX
ejpam-590	81	20	found	find	VERB
ejpam-590	81	21	by	by	ADP
ejpam-590	81	22	minimizing	minimize	VERB
ejpam-590	81	23	e[(p1	e[(p1	NUM
ejpam-590	81	24	,	,	PUNCT
ejpam-590	81	25	p2	p2	PROPN
ejpam-590	81	26	)	)	PUNCT
ejpam-590	81	27	]	]	PUNCT
ejpam-590	81	28	using	use	VERB
ejpam-590	81	29	ga	ga	PROPN
ejpam-590	81	30	.	.	PUNCT
ejpam-590	82	1	in	in	ADP
ejpam-590	82	2	this	this	DET
ejpam-590	82	3	study	study	NOUN
ejpam-590	82	4	,	,	PUNCT
ejpam-590	82	5	the	the	DET
ejpam-590	82	6	real	real	ADV
ejpam-590	82	7	coded	code	VERB
ejpam-590	82	8	genetic	genetic	ADJ
ejpam-590	82	9	algorithm	algorithm	NOUN
ejpam-590	82	10	,	,	PUNCT
ejpam-590	82	11	mi	mi	NOUN
ejpam-590	82	12	-	-	NOUN
ejpam-590	82	13	lxpm	lxpm	PROPN
ejpam-590	82	14	,	,	PUNCT
ejpam-590	82	15	for	for	ADP
ejpam-590	82	16	details	detail	NOUN
ejpam-590	82	17	see	see	VERB
ejpam-590	82	18	[	[	X
ejpam-590	82	19	5	5	NUM
ejpam-590	82	20	]	]	PUNCT
ejpam-590	82	21	,	,	PUNCT
ejpam-590	82	22	has	have	AUX
ejpam-590	82	23	been	be	AUX
ejpam-590	82	24	used	use	VERB
ejpam-590	82	25	to	to	PART
ejpam-590	82	26	solve	solve	VERB
ejpam-590	82	27	above	above	ADP
ejpam-590	82	28	single	single	ADJ
ejpam-590	82	29	objective	objective	ADJ
ejpam-590	82	30	optimization	optimization	NOUN
ejpam-590	82	31	problems	problem	NOUN
ejpam-590	82	32	.	.	PUNCT
ejpam-590	83	1	computational	computational	ADJ
ejpam-590	83	2	steps	step	NOUN
ejpam-590	83	3	of	of	ADP
ejpam-590	83	4	mi	mi	NOUN
ejpam-590	83	5	-	-	PUNCT
ejpam-590	83	6	lxpm	lxpm	NOUN
ejpam-590	83	7	algorithm	algorithm	NOUN
ejpam-590	83	8	are	be	AUX
ejpam-590	83	9	as	as	SCONJ
ejpam-590	83	10	follows	follow	VERB
ejpam-590	83	11	:	:	PUNCT
ejpam-590	83	12	step-1	step-1	NUM
ejpam-590	83	13	:	:	PUNCT
ejpam-590	83	14	generate	generate	VERB
ejpam-590	83	15	a	a	DET
ejpam-590	83	16	suitably	suitably	ADV
ejpam-590	83	17	large	large	ADJ
ejpam-590	83	18	initial	initial	ADJ
ejpam-590	83	19	set	set	NOUN
ejpam-590	83	20	of	of	ADP
ejpam-590	83	21	random	random	ADJ
ejpam-590	83	22	points	point	NOUN
ejpam-590	83	23	within	within	ADP
ejpam-590	83	24	the	the	DET
ejpam-590	83	25	domain	domain	NOUN
ejpam-590	83	26	,	,	PUNCT
ejpam-590	83	27	it	it	PRON
ejpam-590	83	28	may	may	AUX
ejpam-590	83	29	be	be	AUX
ejpam-590	83	30	5	5	NUM
ejpam-590	83	31	to	to	PART
ejpam-590	83	32	10	10	NUM
ejpam-590	83	33	times	time	NOUN
ejpam-590	83	34	of	of	ADP
ejpam-590	83	35	number	number	NOUN
ejpam-590	83	36	of	of	ADP
ejpam-590	83	37	variables	variable	NOUN
ejpam-590	83	38	.	.	PUNCT
ejpam-590	84	1	evaluate	evaluate	VERB
ejpam-590	84	2	their	their	PRON
ejpam-590	84	3	fitness	fitness	NOUN
ejpam-590	84	4	values	value	NOUN
ejpam-590	84	5	.	.	PUNCT
ejpam-590	85	1	step-2	step-2	NUM
ejpam-590	85	2	:	:	PUNCT
ejpam-590	85	3	check	check	VERB
ejpam-590	85	4	the	the	DET
ejpam-590	85	5	stopping	stopping	NOUN
ejpam-590	85	6	criteria	criterion	NOUN
ejpam-590	85	7	?	?	PUNCT
ejpam-590	86	1	if	if	SCONJ
ejpam-590	86	2	satisfied	satisfied	ADJ
ejpam-590	86	3	stop	stop	VERB
ejpam-590	86	4	else	else	ADV
ejpam-590	86	5	goto	goto	ADJ
ejpam-590	86	6	step	step	NOUN
ejpam-590	86	7	3	3	NUM
ejpam-590	86	8	.	.	PUNCT
ejpam-590	87	1	step-3	step-3	NOUN
ejpam-590	87	2	:	:	PUNCT
ejpam-590	87	3	apply	apply	VERB
ejpam-590	87	4	tournament	tournament	NOUN
ejpam-590	87	5	selection	selection	NOUN
ejpam-590	87	6	operator	operator	NOUN
ejpam-590	87	7	to	to	PART
ejpam-590	87	8	decide	decide	VERB
ejpam-590	87	9	which	which	PRON
ejpam-590	87	10	of	of	ADP
ejpam-590	87	11	these	these	DET
ejpam-590	87	12	individuals	individual	NOUN
ejpam-590	87	13	are	be	AUX
ejpam-590	87	14	to	to	PART
ejpam-590	87	15	be	be	AUX
ejpam-590	87	16	in	in	ADP
ejpam-590	87	17	mating	mate	VERB
ejpam-590	87	18	pool	pool	NOUN
ejpam-590	87	19	.	.	PUNCT
ejpam-590	88	1	step-4	step-4	NUM
ejpam-590	88	2	:	:	PUNCT
ejpam-590	88	3	apply	apply	VERB
ejpam-590	88	4	laplace	laplace	NOUN
ejpam-590	88	5	crossover	crossover	NOUN
ejpam-590	88	6	operator	operator	NOUN
ejpam-590	88	7	to	to	ADP
ejpam-590	88	8	all	all	DET
ejpam-590	88	9	individuals	individual	NOUN
ejpam-590	88	10	in	in	ADP
ejpam-590	88	11	mating	mate	VERB
ejpam-590	88	12	pool	pool	NOUN
ejpam-590	88	13	with	with	ADP
ejpam-590	88	14	probability	probability	NOUN
ejpam-590	88	15	of	of	ADP
ejpam-590	88	16	crossover	crossover	ADP
ejpam-590	88	17	pc	pc	NOUN
ejpam-590	88	18	.	.	PUNCT
ejpam-590	89	1	crossover	crossover	NOUN
ejpam-590	89	2	operator	operator	NOUN
ejpam-590	89	3	produces	produce	VERB
ejpam-590	89	4	new	new	ADJ
ejpam-590	89	5	solution	solution	NOUN
ejpam-590	89	6	points	point	NOUN
ejpam-590	89	7	in	in	ADP
ejpam-590	89	8	the	the	DET
ejpam-590	89	9	search	search	NOUN
ejpam-590	89	10	space	space	NOUN
ejpam-590	89	11	.	.	PUNCT
ejpam-590	90	1	step-5	step-5	NUM
ejpam-590	90	2	:	:	PUNCT
ejpam-590	90	3	apply	apply	VERB
ejpam-590	90	4	power	power	NOUN
ejpam-590	90	5	mutation	mutation	NOUN
ejpam-590	90	6	to	to	ADP
ejpam-590	90	7	all	all	DET
ejpam-590	90	8	individuals	individual	NOUN
ejpam-590	90	9	in	in	ADP
ejpam-590	90	10	mating	mate	VERB
ejpam-590	90	11	pool	pool	NOUN
ejpam-590	90	12	with	with	ADP
ejpam-590	90	13	probability	probability	NOUN
ejpam-590	90	14	of	of	ADP
ejpam-590	90	15	mutation	mutation	NOUN
ejpam-590	90	16	pm	pm	NOUN
ejpam-590	90	17	.	.	PUNCT
ejpam-590	91	1	mutation	mutation	NOUN
ejpam-590	91	2	operator	operator	NOUN
ejpam-590	91	3	maintains	maintain	VERB
ejpam-590	91	4	diversity	diversity	NOUN
ejpam-590	91	5	in	in	ADP
ejpam-590	91	6	the	the	DET
ejpam-590	91	7	population	population	NOUN
ejpam-590	91	8	,	,	PUNCT
ejpam-590	91	9	so	so	CCONJ
ejpam-590	91	10	it	it	PRON
ejpam-590	91	11	prevents	prevent	VERB
ejpam-590	91	12	the	the	DET
ejpam-590	91	13	algorithm	algorithm	NOUN
ejpam-590	91	14	to	to	PART
ejpam-590	91	15	converge	converge	VERB
ejpam-590	91	16	to	to	ADP
ejpam-590	91	17	local	local	ADJ
ejpam-590	91	18	optima	optima	NOUN
ejpam-590	91	19	.	.	PUNCT
ejpam-590	92	1	step-6	step-6	NUM
ejpam-590	92	2	:	:	PUNCT
ejpam-590	92	3	increase	increase	NOUN
ejpam-590	92	4	generation	generation	NOUN
ejpam-590	92	5	;	;	PUNCT
ejpam-590	92	6	goto	goto	ADJ
ejpam-590	92	7	step	step	NOUN
ejpam-590	92	8	2	2	NUM
ejpam-590	92	9	.	.	PUNCT
ejpam-590	93	1	parameter	parameter	NOUN
ejpam-590	93	2	setting	set	VERB
ejpam-590	93	3	is	be	AUX
ejpam-590	93	4	one	one	NUM
ejpam-590	93	5	of	of	ADP
ejpam-590	93	6	the	the	DET
ejpam-590	93	7	important	important	ADJ
ejpam-590	93	8	aspect	aspect	NOUN
ejpam-590	93	9	of	of	ADP
ejpam-590	93	10	genetic	genetic	ADJ
ejpam-590	93	11	algorithms	algorithm	NOUN
ejpam-590	93	12	.	.	PUNCT
ejpam-590	94	1	in	in	ADP
ejpam-590	94	2	this	this	DET
ejpam-590	94	3	study	study	NOUN
ejpam-590	94	4	parameters	parameter	NOUN
ejpam-590	94	5	value	value	NOUN
ejpam-590	94	6	have	have	AUX
ejpam-590	94	7	been	be	AUX
ejpam-590	94	8	taken	take	VERB
ejpam-590	94	9	as	as	ADP
ejpam-590	94	10	a	a	DET
ejpam-590	94	11	=	=	SYM
ejpam-590	94	12	0	0	NUM
ejpam-590	94	13	,	,	PUNCT
ejpam-590	94	14	b	b	X
ejpam-590	94	15	=	=	SYM
ejpam-590	94	16	0.35	0.35	NUM
ejpam-590	94	17	,	,	PUNCT
ejpam-590	94	18	p	p	X
ejpam-590	94	19	=	=	NOUN
ejpam-590	94	20	4	4	NUM
ejpam-590	94	21	,	,	PUNCT
ejpam-590	94	22	pc	pc	NOUN
ejpam-590	94	23	=	=	NUM
ejpam-590	94	24	0.8	0.8	NUM
ejpam-590	94	25	,	,	PUNCT
ejpam-590	94	26	pm	pm	NOUN
ejpam-590	94	27	=	=	NOUN
ejpam-590	94	28	0.005	0.005	NUM
ejpam-590	94	29	with	with	ADP
ejpam-590	94	30	tournament	tournament	NOUN
ejpam-590	94	31	size	size	NOUN
ejpam-590	94	32	three	three	NUM
ejpam-590	94	33	(	(	PUNCT
ejpam-590	94	34	details	detail	NOUN
ejpam-590	94	35	of	of	ADP
ejpam-590	94	36	the	the	DET
ejpam-590	94	37	parameters	parameter	NOUN
ejpam-590	94	38	a	a	DET
ejpam-590	94	39	,	,	PUNCT
ejpam-590	94	40	b	b	NOUN
ejpam-590	94	41	,	,	PUNCT
ejpam-590	94	42	and	and	CCONJ
ejpam-590	94	43	p	p	NOUN
ejpam-590	94	44	can	can	AUX
ejpam-590	94	45	be	be	AUX
ejpam-590	94	46	seen	see	VERB
ejpam-590	94	47	in	in	ADP
ejpam-590	94	48	[	[	X
ejpam-590	94	49	5	5	NUM
ejpam-590	94	50	]	]	NUM
ejpam-590	94	51	)	)	PUNCT
ejpam-590	94	52	.	.	PUNCT
ejpam-590	95	1	moreover	moreover	ADV
ejpam-590	95	2	,	,	PUNCT
ejpam-590	95	3	40,000	40,000	NUM
ejpam-590	95	4	generation	generation	NOUN
ejpam-590	95	5	has	have	AUX
ejpam-590	95	6	been	be	AUX
ejpam-590	95	7	used	use	VERB
ejpam-590	95	8	as	as	ADP
ejpam-590	95	9	stopping	stop	VERB
ejpam-590	95	10	criteria	criterion	NOUN
ejpam-590	95	11	for	for	ADP
ejpam-590	95	12	a	a	DET
ejpam-590	95	13	run	run	NOUN
ejpam-590	95	14	of	of	ADP
ejpam-590	95	15	ga	ga	PROPN
ejpam-590	95	16	.	.	PROPN
ejpam-590	95	17	4	4	NUM
ejpam-590	95	18	.	.	X
ejpam-590	95	19	numerical	numerical	PROPN
ejpam-590	95	20	result	result	PROPN
ejpam-590	95	21	consider	consider	VERB
ejpam-590	95	22	the	the	DET
ejpam-590	95	23	controlled	control	VERB
ejpam-590	95	24	linear	linear	ADJ
ejpam-590	95	25	two	two	NUM
ejpam-590	95	26	-	-	PUNCT
ejpam-590	95	27	dimensional	dimensional	ADJ
ejpam-590	95	28	heat	heat	NOUN
ejpam-590	95	29	equation	equation	NOUN
ejpam-590	95	30	∂ω(x	∂ω(x	PROPN
ejpam-590	95	31	,	,	PUNCT
ejpam-590	95	32	t	t	PROPN
ejpam-590	95	33	)	)	PUNCT
ejpam-590	95	34	∂	∂	NOUN
ejpam-590	95	35	t	t	NOUN
ejpam-590	95	36	=	=	SYM
ejpam-590	95	37	ν	ν	PROPN
ejpam-590	95	38	∂	∂	NUM
ejpam-590	95	39	2ω(x	2ω(x	NUM
ejpam-590	95	40	,	,	PUNCT
ejpam-590	95	41	t	t	PROPN
ejpam-590	95	42	)	)	PUNCT
ejpam-590	95	43	∂	∂	NOUN
ejpam-590	96	1	x2	x2	NOUN
ejpam-590	96	2	+	+	CCONJ
ejpam-590	96	3	∂	∂	NUM
ejpam-590	96	4	2ω(x	2ω(x	NUM
ejpam-590	96	5	,	,	PUNCT
ejpam-590	96	6	t	t	PROPN
ejpam-590	96	7	)	)	PUNCT
ejpam-590	96	8	∂	∂	NUM
ejpam-590	97	1	y2	y2	NOUN
ejpam-590	98	1	+	+	CCONJ
ejpam-590	98	2	3π3ν	3π3ν	ADV
ejpam-590	98	3	exp(2π2ν	exp(2π2ν	PROPN
ejpam-590	98	4	t)(sin(πx)+	t)(sin(πx)+	NOUN
ejpam-590	98	5	sin(πy	sin(πy	NOUN
ejpam-590	98	6	)	)	PUNCT
ejpam-590	98	7	)	)	PUNCT
ejpam-590	99	1	(	(	PUNCT
ejpam-590	99	2	6	6	NUM
ejpam-590	99	3	)	)	PUNCT
ejpam-590	99	4	with	with	ADP
ejpam-590	99	5	initial	initial	ADJ
ejpam-590	99	6	condition	condition	NOUN
ejpam-590	99	7	ω(x	ω(x	X
ejpam-590	99	8	,	,	PUNCT
ejpam-590	99	9	y	y	PROPN
ejpam-590	99	10	,	,	PUNCT
ejpam-590	99	11	0	0	NUM
ejpam-590	99	12	)	)	PUNCT
ejpam-590	99	13	=	=	PRON
ejpam-590	99	14	π(sin(πx)+	π(sin(πx)+	VERB
ejpam-590	99	15	sin(πy	sin(πy	NOUN
ejpam-590	99	16	)	)	PUNCT
ejpam-590	99	17	)	)	PUNCT
ejpam-590	99	18	(	(	PUNCT
ejpam-590	99	19	7	7	X
ejpam-590	99	20	)	)	PUNCT
ejpam-590	100	1	where	where	SCONJ
ejpam-590	100	2	t	t	PROPN
ejpam-590	100	3	∈	∈	PROPN
ejpam-590	100	4	(	(	PUNCT
ejpam-590	100	5	0,1	0,1	NUM
ejpam-590	100	6	)	)	PUNCT
ejpam-590	100	7	,	,	PUNCT
ejpam-590	100	8	ν	ν	X
ejpam-590	100	9	=	=	SYM
ejpam-590	100	10	1	1	NUM
ejpam-590	100	11	2π2	2π2	NUM
ejpam-590	100	12	and	and	CCONJ
ejpam-590	100	13	(	(	PUNCT
ejpam-590	100	14	x	x	X
ejpam-590	100	15	,	,	PUNCT
ejpam-590	100	16	y	y	PROPN
ejpam-590	100	17	)	)	PUNCT
ejpam-590	100	18	∈	∈	PROPN
ejpam-590	100	19	ω	ω	NUM
ejpam-590	100	20	=	=	SYM
ejpam-590	100	21	(	(	PUNCT
ejpam-590	100	22	0,1)×	0,1)×	PROPN
ejpam-590	100	23	(	(	PUNCT
ejpam-590	100	24	0,1	0,1	NUM
ejpam-590	100	25	)	)	PUNCT
ejpam-590	100	26	.	.	PUNCT
ejpam-590	101	1	on	on	ADP
ejpam-590	101	2	unit	unit	NOUN
ejpam-590	101	3	square	square	PROPN
ejpam-590	101	4	boundary	boundary	ADJ
ejpam-590	101	5	γ	γ	X
ejpam-590	101	6	=	=	SYM
ejpam-590	101	7	{	{	PUNCT
ejpam-590	101	8	y	y	NOUN
ejpam-590	101	9	=	=	PUNCT
ejpam-590	101	10	0,0≤	0,0≤	NOUN
ejpam-590	101	11	x	x	SYM
ejpam-590	101	12	≤	≤	NUM
ejpam-590	101	13	1	1	NUM
ejpam-590	101	14	;	;	PUNCT
ejpam-590	101	15	x	x	SYM
ejpam-590	101	16	=	=	SYM
ejpam-590	101	17	1,0≤	1,0≤	NUM
ejpam-590	101	18	y	y	PROPN
ejpam-590	101	19	≤	≤	PROPN
ejpam-590	101	20	1	1	NUM
ejpam-590	101	21	;	;	PUNCT
ejpam-590	101	22	y	y	PROPN
ejpam-590	101	23	=	=	PUNCT
ejpam-590	101	24	1,0≤	1,0≤	NUM
ejpam-590	101	25	x	x	SYM
ejpam-590	101	26	≤	≤	NUM
ejpam-590	101	27	1	1	NUM
ejpam-590	101	28	;	;	PUNCT
ejpam-590	101	29	x	x	SYM
ejpam-590	101	30	=	=	SYM
ejpam-590	101	31	0,0≤	0,0≤	NUM
ejpam-590	101	32	y	y	PROPN
ejpam-590	101	33	≤	≤	NUM
ejpam-590	101	34	1	1	NUM
ejpam-590	101	35	}	}	PUNCT
ejpam-590	101	36	.	.	PUNCT
ejpam-590	102	1	now	now	ADV
ejpam-590	102	2	the	the	DET
ejpam-590	102	3	problem	problem	NOUN
ejpam-590	102	4	is	be	AUX
ejpam-590	102	5	to	to	PART
ejpam-590	102	6	find	find	VERB
ejpam-590	102	7	the	the	DET
ejpam-590	102	8	unknown	unknown	ADJ
ejpam-590	102	9	control	control	NOUN
ejpam-590	102	10	functions	function	NOUN
ejpam-590	102	11	,	,	PUNCT
ejpam-590	102	12	g	g	NOUN
ejpam-590	102	13	,	,	PUNCT
ejpam-590	102	14	h	h	NOUN
ejpam-590	102	15	,	,	PUNCT
ejpam-590	102	16	m	m	PROPN
ejpam-590	102	17	,	,	PUNCT
ejpam-590	102	18	and	and	CCONJ
ejpam-590	102	19	n	n	CCONJ
ejpam-590	102	20	,	,	PUNCT
ejpam-590	102	21	defined	define	VERB
ejpam-590	102	22	on	on	ADP
ejpam-590	102	23	the	the	DET
ejpam-590	102	24	given	give	VERB
ejpam-590	102	25	boundary	boundary	NOUN
ejpam-590	102	26	as	as	ADP
ejpam-590	102	27	ω(0	ω(0	PROPN
ejpam-590	102	28	,	,	PUNCT
ejpam-590	102	29	y	y	PROPN
ejpam-590	102	30	,	,	PUNCT
ejpam-590	102	31	t	t	PROPN
ejpam-590	102	32	)	)	PUNCT
ejpam-590	102	33	=	=	SYM
ejpam-590	103	1	g(y	g(y	PROPN
ejpam-590	103	2	,	,	PUNCT
ejpam-590	103	3	t	t	PROPN
ejpam-590	103	4	)	)	PUNCT
ejpam-590	103	5	ω(x	ω(x	X
ejpam-590	103	6	,	,	PUNCT
ejpam-590	103	7	0	0	NUM
ejpam-590	103	8	,	,	PUNCT
ejpam-590	103	9	t	t	PROPN
ejpam-590	103	10	)	)	PUNCT
ejpam-590	103	11	=	=	PROPN
ejpam-590	103	12	h(x	h(x	PROPN
ejpam-590	103	13	,	,	PUNCT
ejpam-590	103	14	t	t	PROPN
ejpam-590	103	15	)	)	PUNCT
ejpam-590	103	16	n.	n.	PROPN
ejpam-590	103	17	tomar	tomar	PROPN
ejpam-590	103	18	,	,	PUNCT
ejpam-590	103	19	n.	n.	NOUN
ejpam-590	103	20	sukavanam	sukavanam	NOUN
ejpam-590	103	21	,	,	PUNCT
ejpam-590	103	22	k.	k.	PROPN
ejpam-590	103	23	singh	singh	PROPN
ejpam-590	103	24	/	/	SYM
ejpam-590	103	25	eur	eur	PROPN
ejpam-590	103	26	.	.	PUNCT
ejpam-590	104	1	j.	j.	PROPN
ejpam-590	104	2	pure	pure	PROPN
ejpam-590	104	3	appl	appl	PROPN
ejpam-590	104	4	.	.	PROPN
ejpam-590	104	5	math	math	PROPN
ejpam-590	104	6	,	,	PUNCT
ejpam-590	104	7	4	4	NUM
ejpam-590	104	8	(	(	PUNCT
ejpam-590	104	9	2011	2011	NUM
ejpam-590	104	10	)	)	PUNCT
ejpam-590	104	11	,	,	PUNCT
ejpam-590	104	12	117	117	NUM
ejpam-590	104	13	-	-	SYM
ejpam-590	104	14	128	128	NUM
ejpam-590	104	15	121	121	NUM
ejpam-590	104	16	ω(1	ω(1	PROPN
ejpam-590	104	17	,	,	PUNCT
ejpam-590	104	18	y	y	PROPN
ejpam-590	104	19	,	,	PUNCT
ejpam-590	104	20	t	t	PROPN
ejpam-590	104	21	)	)	PUNCT
ejpam-590	104	22	=	=	SYM
ejpam-590	104	23	m(y	m(y	PROPN
ejpam-590	104	24	,	,	PUNCT
ejpam-590	104	25	t	t	PROPN
ejpam-590	104	26	)	)	PUNCT
ejpam-590	104	27	ω(x	ω(x	X
ejpam-590	104	28	,	,	PUNCT
ejpam-590	104	29	1	1	NUM
ejpam-590	104	30	,	,	PUNCT
ejpam-590	104	31	t	t	PROPN
ejpam-590	104	32	)	)	PUNCT
ejpam-590	104	33	=	=	SYM
ejpam-590	105	1	n(x	n(x	PROPN
ejpam-590	105	2	,	,	PUNCT
ejpam-590	105	3	t	t	PROPN
ejpam-590	105	4	)	)	PUNCT
ejpam-590	105	5	(	(	PUNCT
ejpam-590	105	6	8)	8)	NUM
ejpam-590	105	7	such	such	ADJ
ejpam-590	105	8	that	that	PRON
ejpam-590	105	9	at	at	ADP
ejpam-590	105	10	the	the	DET
ejpam-590	105	11	final	final	ADJ
ejpam-590	105	12	time	time	NOUN
ejpam-590	105	13	t	t	NOUN
ejpam-590	105	14	=	=	SYM
ejpam-590	105	15	1	1	NUM
ejpam-590	105	16	the	the	DET
ejpam-590	105	17	solution	solution	NOUN
ejpam-590	105	18	ω(x	ω(x	NUM
ejpam-590	105	19	,	,	PUNCT
ejpam-590	105	20	y	y	PROPN
ejpam-590	105	21	,	,	PUNCT
ejpam-590	105	22	t	t	PROPN
ejpam-590	105	23	)	)	PUNCT
ejpam-590	105	24	satisfies	satisfie	NOUN
ejpam-590	105	25	ω(x	ω(x	NUM
ejpam-590	105	26	,	,	PUNCT
ejpam-590	105	27	y	y	PROPN
ejpam-590	105	28	,	,	PUNCT
ejpam-590	105	29	1	1	NUM
ejpam-590	105	30	)	)	PUNCT
ejpam-590	105	31	=	=	PUNCT
ejpam-590	105	32	πexp(2π2ν)(sin(πx)+	πexp(2π2ν)(sin(πx)+	NOUN
ejpam-590	105	33	sin(πy	sin(πy	NOUN
ejpam-590	105	34	)	)	PUNCT
ejpam-590	105	35	)	)	PUNCT
ejpam-590	105	36	(	(	PUNCT
ejpam-590	105	37	9	9	X
ejpam-590	105	38	)	)	PUNCT
ejpam-590	105	39	from	from	ADP
ejpam-590	105	40	equations	equation	NOUN
ejpam-590	105	41	(	(	PUNCT
ejpam-590	105	42	6)-(9	6)-(9	NOUN
ejpam-590	105	43	)	)	PUNCT
ejpam-590	105	44	the	the	DET
ejpam-590	105	45	following	follow	VERB
ejpam-590	105	46	compatibility	compatibility	NOUN
ejpam-590	105	47	conditions	condition	NOUN
ejpam-590	105	48	on	on	ADP
ejpam-590	105	49	g	g	PROPN
ejpam-590	105	50	,	,	PUNCT
ejpam-590	105	51	h	h	NOUN
ejpam-590	105	52	,	,	PUNCT
ejpam-590	105	53	m	m	VERB
ejpam-590	105	54	and	and	CCONJ
ejpam-590	105	55	n	n	PRON
ejpam-590	105	56	can	can	AUX
ejpam-590	105	57	be	be	AUX
ejpam-590	105	58	obtained	obtain	VERB
ejpam-590	105	59	g(y	g(y	PROPN
ejpam-590	105	60	,	,	PUNCT
ejpam-590	105	61	0	0	NUM
ejpam-590	105	62	)	)	PUNCT
ejpam-590	105	63	=	=	SYM
ejpam-590	106	1	π	π	NOUN
ejpam-590	106	2	sin(πy	sin(πy	NOUN
ejpam-590	106	3	)	)	PUNCT
ejpam-590	106	4	;	;	PUNCT
ejpam-590	107	1	g(y	g(y	NOUN
ejpam-590	107	2	,	,	PUNCT
ejpam-590	107	3	1	1	NUM
ejpam-590	107	4	)	)	PUNCT
ejpam-590	107	5	=	=	SYM
ejpam-590	107	6	πexp(2π2ν	πexp(2π2ν	PROPN
ejpam-590	107	7	)	)	PUNCT
ejpam-590	107	8	sin(πy	sin(πy	NOUN
ejpam-590	107	9	)	)	PUNCT
ejpam-590	107	10	h(x	h(x	PROPN
ejpam-590	107	11	,	,	PUNCT
ejpam-590	107	12	0	0	NUM
ejpam-590	107	13	)	)	PUNCT
ejpam-590	107	14	=	=	SYM
ejpam-590	107	15	π	π	NOUN
ejpam-590	107	16	sin(πx	sin(πx	NOUN
ejpam-590	107	17	)	)	PUNCT
ejpam-590	107	18	;	;	PUNCT
ejpam-590	107	19	h(x	h(x	PROPN
ejpam-590	107	20	,	,	PUNCT
ejpam-590	107	21	1	1	X
ejpam-590	107	22	)	)	PUNCT
ejpam-590	107	23	=	=	SYM
ejpam-590	107	24	πexp(2π2ν	πexp(2π2ν	ADJ
ejpam-590	107	25	)	)	PUNCT
ejpam-590	107	26	sin(πx	sin(πx	NOUN
ejpam-590	107	27	)	)	PUNCT
ejpam-590	107	28	m(y	m(y	NOUN
ejpam-590	107	29	,	,	PUNCT
ejpam-590	107	30	0	0	NUM
ejpam-590	107	31	)	)	PUNCT
ejpam-590	107	32	=	=	SYM
ejpam-590	107	33	π	π	NOUN
ejpam-590	107	34	sin(πy	sin(πy	NOUN
ejpam-590	107	35	)	)	PUNCT
ejpam-590	107	36	;	;	PUNCT
ejpam-590	107	37	m(y	m(y	NOUN
ejpam-590	107	38	,	,	PUNCT
ejpam-590	107	39	1	1	NUM
ejpam-590	107	40	)	)	PUNCT
ejpam-590	107	41	=	=	SYM
ejpam-590	107	42	πexp(2π2ν	πexp(2π2ν	PROPN
ejpam-590	107	43	)	)	PUNCT
ejpam-590	107	44	sin(πy	sin(πy	NOUN
ejpam-590	107	45	)	)	PUNCT
ejpam-590	107	46	n(x	n(x	PROPN
ejpam-590	107	47	,	,	PUNCT
ejpam-590	107	48	0	0	NUM
ejpam-590	107	49	)	)	PUNCT
ejpam-590	107	50	=	=	SYM
ejpam-590	107	51	π	π	NOUN
ejpam-590	107	52	sin(πx	sin(πx	NOUN
ejpam-590	107	53	)	)	PUNCT
ejpam-590	107	54	;	;	PUNCT
ejpam-590	107	55	n(x	n(x	PRON
ejpam-590	107	56	,	,	PUNCT
ejpam-590	107	57	1	1	X
ejpam-590	107	58	)	)	PUNCT
ejpam-590	107	59	=	=	SYM
ejpam-590	107	60	πexp(2π2ν	πexp(2π2ν	ADJ
ejpam-590	107	61	)	)	PUNCT
ejpam-590	107	62	sin(πx	sin(πx	NOUN
ejpam-590	107	63	)	)	PUNCT
ejpam-590	107	64	(	(	PUNCT
ejpam-590	107	65	10	10	NUM
ejpam-590	107	66	)	)	PUNCT
ejpam-590	107	67	also	also	ADV
ejpam-590	107	68	g(0	g(0	PROPN
ejpam-590	107	69	,	,	PUNCT
ejpam-590	107	70	t	t	PROPN
ejpam-590	107	71	)	)	PUNCT
ejpam-590	107	72	=	=	SYM
ejpam-590	108	1	h(0	h(0	PROPN
ejpam-590	108	2	,	,	PUNCT
ejpam-590	108	3	t	t	PROPN
ejpam-590	108	4	)	)	PUNCT
ejpam-590	108	5	;	;	PUNCT
ejpam-590	108	6	g(1	g(1	PROPN
ejpam-590	108	7	,	,	PUNCT
ejpam-590	108	8	t	t	PROPN
ejpam-590	108	9	)	)	PUNCT
ejpam-590	108	10	=	=	SYM
ejpam-590	108	11	n(0	n(0	PROPN
ejpam-590	108	12	,	,	PUNCT
ejpam-590	108	13	t	t	PROPN
ejpam-590	108	14	)	)	PUNCT
ejpam-590	108	15	;	;	PUNCT
ejpam-590	108	16	h(1	h(1	PROPN
ejpam-590	108	17	,	,	PUNCT
ejpam-590	108	18	t	t	PROPN
ejpam-590	108	19	)	)	PUNCT
ejpam-590	108	20	=	=	SYM
ejpam-590	109	1	m(0	m(0	PROPN
ejpam-590	109	2	,	,	PUNCT
ejpam-590	109	3	t	t	PROPN
ejpam-590	109	4	)	)	PUNCT
ejpam-590	109	5	;	;	PUNCT
ejpam-590	109	6	m(1	m(1	PROPN
ejpam-590	109	7	,	,	PUNCT
ejpam-590	109	8	t	t	PROPN
ejpam-590	109	9	)	)	PUNCT
ejpam-590	109	10	=	=	SYM
ejpam-590	109	11	n(1	n(1	PROPN
ejpam-590	109	12	,	,	PUNCT
ejpam-590	109	13	t	t	PROPN
ejpam-590	109	14	)	)	PUNCT
ejpam-590	109	15	(	(	PUNCT
ejpam-590	109	16	11	11	NUM
ejpam-590	109	17	)	)	PUNCT
ejpam-590	109	18	hence	hence	ADV
ejpam-590	109	19	,	,	PUNCT
ejpam-590	109	20	we	we	PRON
ejpam-590	109	21	consider	consider	VERB
ejpam-590	109	22	the	the	DET
ejpam-590	109	23	neural	neural	ADJ
ejpam-590	109	24	network	network	NOUN
ejpam-590	109	25	approximation	approximation	NOUN
ejpam-590	109	26	of	of	ADP
ejpam-590	109	27	g	g	PROPN
ejpam-590	109	28	,	,	PUNCT
ejpam-590	109	29	h	h	NOUN
ejpam-590	109	30	,	,	PUNCT
ejpam-590	109	31	m	m	VERB
ejpam-590	109	32	and	and	CCONJ
ejpam-590	109	33	n	n	PROPN
ejpam-590	109	34	as	as	ADP
ejpam-590	109	35	g(y	g(y	PROPN
ejpam-590	109	36	,	,	PUNCT
ejpam-590	109	37	t	t	PROPN
ejpam-590	109	38	)	)	PUNCT
ejpam-590	109	39	=	=	PUNCT
ejpam-590	110	1	[	[	X
ejpam-590	110	2	1−	1−	NUM
ejpam-590	110	3	t	t	NOUN
ejpam-590	110	4	+	+	CCONJ
ejpam-590	110	5	t	t	PROPN
ejpam-590	110	6	exp(2π2ν)]π	exp(2π2ν)]π	PROPN
ejpam-590	110	7	sin(πy	sin(πy	VERB
ejpam-590	110	8	)	)	PUNCT
ejpam-590	111	1	+	+	NUM
ejpam-590	111	2	t(1−	t(1−	PROPN
ejpam-590	111	3	t)[y(1−	t)[y(1−	PROPN
ejpam-590	111	4	y)ng	y)ng	PROPN
ejpam-590	111	5	+	+	CCONJ
ejpam-590	111	6	(	(	PUNCT
ejpam-590	111	7	1−	1−	NUM
ejpam-590	111	8	y)n1	y)n1	PROPN
ejpam-590	111	9	+	+	CCONJ
ejpam-590	111	10	yn2	yn2	NOUN
ejpam-590	111	11	]	]	X
ejpam-590	111	12	h(x	h(x	PROPN
ejpam-590	111	13	,	,	PUNCT
ejpam-590	111	14	t	t	PROPN
ejpam-590	111	15	)	)	PUNCT
ejpam-590	111	16	=	=	PUNCT
ejpam-590	112	1	[	[	X
ejpam-590	112	2	1−	1−	NUM
ejpam-590	112	3	t	t	NOUN
ejpam-590	112	4	+	+	CCONJ
ejpam-590	112	5	t	t	PROPN
ejpam-590	112	6	exp(2π2ν)]π	exp(2π2ν)]π	PROPN
ejpam-590	112	7	sin(πx)+	sin(πx)+	VERB
ejpam-590	112	8	t(1−	t(1−	PROPN
ejpam-590	112	9	t)[x(1−	t)[x(1−	PROPN
ejpam-590	112	10	x)nh+	x)nh+	PROPN
ejpam-590	112	11	(	(	PUNCT
ejpam-590	112	12	1−	1−	NUM
ejpam-590	112	13	x)n1	x)n1	PROPN
ejpam-590	112	14	+	+	PROPN
ejpam-590	113	1	xn3	xn3	PROPN
ejpam-590	113	2	]	]	X
ejpam-590	113	3	m(y	m(y	PROPN
ejpam-590	113	4	,	,	PUNCT
ejpam-590	113	5	t	t	PROPN
ejpam-590	113	6	)	)	PUNCT
ejpam-590	113	7	=	=	PUNCT
ejpam-590	114	1	[	[	X
ejpam-590	114	2	1−	1−	NUM
ejpam-590	114	3	t	t	NOUN
ejpam-590	114	4	+	+	CCONJ
ejpam-590	114	5	t	t	PROPN
ejpam-590	114	6	exp(2π2ν)]π	exp(2π2ν)]π	PROPN
ejpam-590	114	7	sin(πy	sin(πy	VERB
ejpam-590	114	8	)	)	PUNCT
ejpam-590	115	1	+	+	NUM
ejpam-590	115	2	t(1−	t(1−	PROPN
ejpam-590	115	3	t)[y(1−	t)[y(1−	PROPN
ejpam-590	115	4	y)nm+	y)nm+	PROPN
ejpam-590	115	5	(	(	PUNCT
ejpam-590	115	6	1−	1−	NUM
ejpam-590	115	7	y)n3	y)n3	PROPN
ejpam-590	115	8	+	+	CCONJ
ejpam-590	115	9	yn4	yn4	NUM
ejpam-590	115	10	]	]	X
ejpam-590	115	11	n(x	n(x	PROPN
ejpam-590	115	12	,	,	PUNCT
ejpam-590	115	13	t	t	PROPN
ejpam-590	115	14	)	)	PUNCT
ejpam-590	115	15	=	=	PUNCT
ejpam-590	116	1	[	[	X
ejpam-590	116	2	1−	1−	NUM
ejpam-590	116	3	t	t	NOUN
ejpam-590	116	4	+	+	CCONJ
ejpam-590	116	5	t	t	PROPN
ejpam-590	116	6	exp(2π2ν)]π	exp(2π2ν)]π	PROPN
ejpam-590	116	7	sin(πx)+	sin(πx)+	VERB
ejpam-590	116	8	t(1−	t(1−	ADJ
ejpam-590	116	9	t)[x(1−	t)[x(1−	NOUN
ejpam-590	116	10	x)nn+	x)nn+	SYM
ejpam-590	116	11	(	(	PUNCT
ejpam-590	116	12	1−	1−	NUM
ejpam-590	116	13	x)n2	x)n2	PROPN
ejpam-590	116	14	+	+	X
ejpam-590	116	15	xn4	xn4	X
ejpam-590	116	16	]	]	X
ejpam-590	116	17	(	(	PUNCT
ejpam-590	116	18	12	12	NUM
ejpam-590	116	19	)	)	PUNCT
ejpam-590	116	20	where	where	SCONJ
ejpam-590	116	21	,	,	PUNCT
ejpam-590	116	22	ng	ng	PROPN
ejpam-590	116	23	=	=	SYM
ejpam-590	116	24	ng(y	ng(y	PROPN
ejpam-590	116	25	,	,	PUNCT
ejpam-590	116	26	t	t	PROPN
ejpam-590	116	27	,	,	PUNCT
ejpam-590	116	28	pg	pg	PROPN
ejpam-590	116	29	)	)	PUNCT
ejpam-590	117	1	=	=	PUNCT
ejpam-590	117	2	∑	∑	PUNCT
ejpam-590	117	3	vgσ(bg	vgσ(bg	NOUN
ejpam-590	117	4	y	y	PROPN
ejpam-590	118	1	+	+	CCONJ
ejpam-590	118	2	cg	cg	NOUN
ejpam-590	118	3	t	t	NOUN
ejpam-590	118	4	+	+	CCONJ
ejpam-590	118	5	dg	dg	PROPN
ejpam-590	118	6	)	)	PUNCT
ejpam-590	118	7	nh	nh	PROPN
ejpam-590	118	8	=	=	SYM
ejpam-590	118	9	ng(x	ng(x	X
ejpam-590	118	10	,	,	PUNCT
ejpam-590	118	11	t	t	PROPN
ejpam-590	118	12	,	,	PUNCT
ejpam-590	118	13	ph	ph	PROPN
ejpam-590	118	14	)	)	PUNCT
ejpam-590	118	15	=	=	SYM
ejpam-590	119	1	∑	∑	NOUN
ejpam-590	119	2	vhσ(ahx	vhσ(ahx	NOUN
ejpam-590	119	3	+	+	CCONJ
ejpam-590	119	4	ch	ch	PROPN
ejpam-590	119	5	t	t	PROPN
ejpam-590	119	6	+	+	CCONJ
ejpam-590	119	7	dh	dh	NOUN
ejpam-590	119	8	)	)	PUNCT
ejpam-590	119	9	nm	nm	NOUN
ejpam-590	120	1	=	=	NOUN
ejpam-590	120	2	nm(y	nm(y	NUM
ejpam-590	120	3	,	,	PUNCT
ejpam-590	120	4	t	t	PROPN
ejpam-590	120	5	,	,	PUNCT
ejpam-590	120	6	pm	pm	NOUN
ejpam-590	120	7	)	)	PUNCT
ejpam-590	120	8	=	=	PUNCT
ejpam-590	121	1	∑	∑	PUNCT
ejpam-590	121	2	vmσ(bm	vmσ(bm	ADJ
ejpam-590	121	3	y	y	PROPN
ejpam-590	121	4	+	+	CCONJ
ejpam-590	121	5	cm	cm	NOUN
ejpam-590	121	6	t	t	NOUN
ejpam-590	121	7	+	+	CCONJ
ejpam-590	121	8	dm	dm	X
ejpam-590	121	9	)	)	PUNCT
ejpam-590	121	10	nn	nn	NOUN
ejpam-590	121	11	=	=	SYM
ejpam-590	121	12	nn(x	nn(x	X
ejpam-590	121	13	,	,	PUNCT
ejpam-590	121	14	t	t	PROPN
ejpam-590	121	15	,	,	PUNCT
ejpam-590	121	16	pn	pn	NOUN
ejpam-590	121	17	)	)	PUNCT
ejpam-590	121	18	=	=	PUNCT
ejpam-590	122	1	∑	∑	PUNCT
ejpam-590	122	2	vnσ(an	vnσ(an	NOUN
ejpam-590	122	3	x	x	PUNCT
ejpam-590	123	1	+	+	CCONJ
ejpam-590	123	2	cn	cn	PROPN
ejpam-590	123	3	t	t	PROPN
ejpam-590	123	4	+	+	CCONJ
ejpam-590	123	5	dn	dn	ADJ
ejpam-590	123	6	)	)	PUNCT
ejpam-590	123	7	n1	n1	NOUN
ejpam-590	123	8	=	=	SYM
ejpam-590	123	9	n1(t	n1(t	PROPN
ejpam-590	123	10	,	,	PUNCT
ejpam-590	123	11	p1	p1	NOUN
ejpam-590	123	12	)	)	PUNCT
ejpam-590	123	13	=	=	PUNCT
ejpam-590	124	1	∑	∑	PUNCT
ejpam-590	124	2	v1σ(c1	v1σ(c1	PROPN
ejpam-590	124	3	t	t	NOUN
ejpam-590	124	4	+	+	CCONJ
ejpam-590	124	5	d1	d1	NOUN
ejpam-590	124	6	)	)	PUNCT
ejpam-590	124	7	n2	n2	NOUN
ejpam-590	124	8	=	=	SYM
ejpam-590	124	9	n2(t	n2(t	PROPN
ejpam-590	124	10	,	,	PUNCT
ejpam-590	124	11	p2	p2	X
ejpam-590	124	12	)	)	PUNCT
ejpam-590	124	13	=	=	SYM
ejpam-590	124	14	∑	∑	PROPN
ejpam-590	124	15	v2σ(c2	v2σ(c2	PROPN
ejpam-590	124	16	t	t	PROPN
ejpam-590	124	17	+	+	CCONJ
ejpam-590	124	18	d2	d2	PROPN
ejpam-590	124	19	)	)	PUNCT
ejpam-590	124	20	n3	n3	NOUN
ejpam-590	124	21	=	=	SYM
ejpam-590	124	22	n3(t	n3(t	PROPN
ejpam-590	124	23	,	,	PUNCT
ejpam-590	124	24	p3	p3	NOUN
ejpam-590	124	25	)	)	PUNCT
ejpam-590	124	26	=	=	PUNCT
ejpam-590	125	1	∑	∑	PUNCT
ejpam-590	125	2	v3σ(c3	v3σ(c3	PROPN
ejpam-590	125	3	t	t	PROPN
ejpam-590	125	4	+	+	CCONJ
ejpam-590	125	5	d3	d3	PROPN
ejpam-590	125	6	)	)	PUNCT
ejpam-590	125	7	n4	n4	PROPN
ejpam-590	125	8	=	=	PROPN
ejpam-590	126	1	n4(t	n4(t	PROPN
ejpam-590	126	2	,	,	PUNCT
ejpam-590	126	3	p4	p4	ADJ
ejpam-590	126	4	)	)	PUNCT
ejpam-590	126	5	=	=	PUNCT
ejpam-590	127	1	∑	∑	PUNCT
ejpam-590	127	2	v4σ(c4	v4σ(c4	PROPN
ejpam-590	127	3	t	t	NOUN
ejpam-590	127	4	+	+	CCONJ
ejpam-590	127	5	d4	d4	PROPN
ejpam-590	127	6	)	)	PUNCT
ejpam-590	127	7	(	(	PUNCT
ejpam-590	127	8	13	13	NUM
ejpam-590	127	9	)	)	PUNCT
ejpam-590	127	10	where	where	SCONJ
ejpam-590	127	11	pα	pα	NOUN
ejpam-590	128	1	=	=	PUNCT
ejpam-590	128	2	[	[	X
ejpam-590	128	3	vα	vα	ADP
ejpam-590	128	4	,	,	PUNCT
ejpam-590	128	5	cα	cα	NOUN
ejpam-590	128	6	,	,	PUNCT
ejpam-590	128	7	dα	dα	PROPN
ejpam-590	128	8	]	]	X
ejpam-590	128	9	t	t	PROPN
ejpam-590	128	10	,	,	PUNCT
ejpam-590	128	11	α	α	NOUN
ejpam-590	128	12	=	=	NOUN
ejpam-590	128	13	1,2,3,4	1,2,3,4	NUM
ejpam-590	128	14	;	;	PUNCT
ejpam-590	128	15	pβ	pβ	ADP
ejpam-590	128	16	=	=	PUNCT
ejpam-590	129	1	[	[	X
ejpam-590	129	2	vβ	vβ	INTJ
ejpam-590	129	3	,	,	PUNCT
ejpam-590	129	4	aβ	aβ	INTJ
ejpam-590	129	5	,	,	PUNCT
ejpam-590	129	6	cβ	cβ	NOUN
ejpam-590	129	7	,	,	PUNCT
ejpam-590	129	8	dβ	dβ	PROPN
ejpam-590	129	9	]	]	PUNCT
ejpam-590	129	10	t	t	NOUN
ejpam-590	129	11	,	,	PUNCT
ejpam-590	129	12	β	β	X
ejpam-590	129	13	=	=	SYM
ejpam-590	129	14	h	h	NOUN
ejpam-590	129	15	,	,	PUNCT
ejpam-590	129	16	n	n	PROPN
ejpam-590	129	17	and	and	CCONJ
ejpam-590	129	18	pγ	pγ	VERB
ejpam-590	129	19	=	=	PUNCT
ejpam-590	130	1	[	[	X
ejpam-590	130	2	vγ	vγ	NOUN
ejpam-590	130	3	,	,	PUNCT
ejpam-590	130	4	bγ	bγ	ADV
ejpam-590	130	5	,	,	PUNCT
ejpam-590	130	6	cγ	cγ	NOUN
ejpam-590	130	7	,	,	PUNCT
ejpam-590	130	8	dγ	dγ	ADP
ejpam-590	130	9	]	]	X
ejpam-590	130	10	t	t	PROPN
ejpam-590	130	11	,	,	PUNCT
ejpam-590	130	12	γ	γ	PROPN
ejpam-590	130	13	=	=	SYM
ejpam-590	130	14	g	g	PROPN
ejpam-590	130	15	,	,	PUNCT
ejpam-590	130	16	m	m	VERB
ejpam-590	130	17	are	be	AUX
ejpam-590	130	18	the	the	DET
ejpam-590	130	19	weight	weight	NOUN
ejpam-590	130	20	vectors	vector	NOUN
ejpam-590	130	21	,	,	PUNCT
ejpam-590	130	22	and	and	CCONJ
ejpam-590	130	23	σ	σ	PROPN
ejpam-590	130	24	is	be	AUX
ejpam-590	130	25	sigmoid	sigmoid	NOUN
ejpam-590	130	26	function	function	NOUN
ejpam-590	130	27	.	.	PUNCT
ejpam-590	131	1	the	the	DET
ejpam-590	131	2	trial	trial	NOUN
ejpam-590	131	3	solution	solution	NOUN
ejpam-590	131	4	of	of	ADP
ejpam-590	131	5	the	the	DET
ejpam-590	131	6	system	system	NOUN
ejpam-590	131	7	(	(	PUNCT
ejpam-590	131	8	6	6	NUM
ejpam-590	131	9	)	)	PUNCT
ejpam-590	131	10	with	with	ADP
ejpam-590	131	11	given	give	VERB
ejpam-590	131	12	conditions	condition	NOUN
ejpam-590	131	13	is	be	AUX
ejpam-590	131	14	n.	n.	ADJ
ejpam-590	131	15	tomar	tomar	NOUN
ejpam-590	131	16	,	,	PUNCT
ejpam-590	131	17	n.	n.	NOUN
ejpam-590	131	18	sukavanam	sukavanam	NOUN
ejpam-590	131	19	,	,	PUNCT
ejpam-590	131	20	k.	k.	PROPN
ejpam-590	131	21	singh	singh	PROPN
ejpam-590	131	22	/	/	SYM
ejpam-590	131	23	eur	eur	PROPN
ejpam-590	131	24	.	.	PUNCT
ejpam-590	132	1	j.	j.	PROPN
ejpam-590	132	2	pure	pure	PROPN
ejpam-590	132	3	appl	appl	PROPN
ejpam-590	132	4	.	.	PROPN
ejpam-590	132	5	math	math	PROPN
ejpam-590	132	6	,	,	PUNCT
ejpam-590	132	7	4	4	NUM
ejpam-590	132	8	(	(	PUNCT
ejpam-590	132	9	2011	2011	NUM
ejpam-590	132	10	)	)	PUNCT
ejpam-590	132	11	,	,	PUNCT
ejpam-590	132	12	117	117	NUM
ejpam-590	132	13	-	-	SYM
ejpam-590	132	14	128	128	NUM
ejpam-590	132	15	122	122	NUM
ejpam-590	132	16	ωtr(x	ωtr(x	PROPN
ejpam-590	132	17	,	,	PUNCT
ejpam-590	132	18	y	y	PROPN
ejpam-590	132	19	,	,	PUNCT
ejpam-590	132	20	t	t	PROPN
ejpam-590	132	21	)	)	PUNCT
ejpam-590	132	22	=	=	PUNCT
ejpam-590	132	23	(	(	PUNCT
ejpam-590	132	24	1−	1−	NUM
ejpam-590	132	25	x)g(y	x)g(y	PROPN
ejpam-590	132	26	,	,	PUNCT
ejpam-590	132	27	t	t	PROPN
ejpam-590	132	28	)	)	PUNCT
ejpam-590	132	29	+	+	CCONJ
ejpam-590	132	30	xm(y	xm(y	PROPN
ejpam-590	132	31	,	,	PUNCT
ejpam-590	132	32	t	t	PROPN
ejpam-590	132	33	)	)	PUNCT
ejpam-590	132	34	+	+	CCONJ
ejpam-590	132	35	(	(	PUNCT
ejpam-590	132	36	1−	1−	NUM
ejpam-590	132	37	y)h(x	y)h(x	NOUN
ejpam-590	132	38	,	,	PUNCT
ejpam-590	132	39	t	t	PROPN
ejpam-590	132	40	)	)	PUNCT
ejpam-590	133	1	+	+	CCONJ
ejpam-590	133	2	yn(x	yn(x	NUM
ejpam-590	133	3	,	,	PUNCT
ejpam-590	133	4	t	t	PROPN
ejpam-590	133	5	)	)	PUNCT
ejpam-590	133	6	−(1−	−(1−	ADP
ejpam-590	133	7	y)(1−	y)(1−	PROPN
ejpam-590	133	8	x)h(0	x)h(0	PROPN
ejpam-590	133	9	,	,	PUNCT
ejpam-590	133	10	t)−	t)−	PROPN
ejpam-590	133	11	x(1−	x(1−	PROPN
ejpam-590	133	12	y)h(1	y)h(1	PROPN
ejpam-590	133	13	,	,	PUNCT
ejpam-590	133	14	t)−	t)−	PROPN
ejpam-590	133	15	y(1−	y(1−	PROPN
ejpam-590	133	16	x)n(0	x)n(0	PROPN
ejpam-590	133	17	,	,	PUNCT
ejpam-590	133	18	t)−	t)−	PROPN
ejpam-590	134	1	x	x	SYM
ejpam-590	134	2	yn(1	yn(1	PROPN
ejpam-590	134	3	,	,	PUNCT
ejpam-590	134	4	t	t	PROPN
ejpam-590	134	5	)	)	PUNCT
ejpam-590	134	6	+	+	PROPN
ejpam-590	134	7	(	(	PUNCT
ejpam-590	134	8	1−	1−	NUM
ejpam-590	134	9	t)[i(x	t)[i(x	NOUN
ejpam-590	134	10	,	,	PUNCT
ejpam-590	134	11	y)−	y)−	PROPN
ejpam-590	134	12	{	{	PUNCT
ejpam-590	134	13	(	(	PUNCT
ejpam-590	134	14	1−	1−	NUM
ejpam-590	134	15	x)g(y	x)g(y	PROPN
ejpam-590	134	16	,	,	PUNCT
ejpam-590	134	17	0	0	NUM
ejpam-590	134	18	)	)	PUNCT
ejpam-590	134	19	+	+	CCONJ
ejpam-590	134	20	xm(y	xm(y	NOUN
ejpam-590	134	21	,	,	PUNCT
ejpam-590	134	22	0)+	0)+	NUM
ejpam-590	134	23	(	(	PUNCT
ejpam-590	134	24	1−	1−	NUM
ejpam-590	134	25	y)h(x	y)h(x	NOUN
ejpam-590	134	26	,	,	PUNCT
ejpam-590	134	27	0	0	NUM
ejpam-590	134	28	)	)	PUNCT
ejpam-590	134	29	+	+	CCONJ
ejpam-590	134	30	yn(x	yn(x	NUM
ejpam-590	134	31	,	,	PUNCT
ejpam-590	134	32	0	0	NUM
ejpam-590	134	33	)	)	PUNCT
ejpam-590	134	34	−(1−	−(1−	ADP
ejpam-590	134	35	y)(1−	y)(1−	PROPN
ejpam-590	134	36	x)h(0,0)−	x)h(0,0)−	PROPN
ejpam-590	134	37	x(1−	x(1−	PROPN
ejpam-590	134	38	y)h(1,0)−	y)h(1,0)−	PROPN
ejpam-590	134	39	y(1−	y(1−	PROPN
ejpam-590	134	40	x)n(0,0)−	x)n(0,0)−	PROPN
ejpam-590	134	41	x	x	PROPN
ejpam-590	134	42	yn(1,0	yn(1,0	PROPN
ejpam-590	134	43	)	)	PUNCT
ejpam-590	134	44	}	}	PUNCT
ejpam-590	134	45	]	]	PUNCT
ejpam-590	135	1	+	+	NOUN
ejpam-590	135	2	t[f(x	t[f(x	NOUN
ejpam-590	135	3	,	,	PUNCT
ejpam-590	135	4	y)−	y)−	PROPN
ejpam-590	135	5	{	{	PUNCT
ejpam-590	135	6	(	(	PUNCT
ejpam-590	135	7	1−	1−	NUM
ejpam-590	135	8	x)g(y	x)g(y	PROPN
ejpam-590	135	9	,	,	PUNCT
ejpam-590	135	10	1	1	NUM
ejpam-590	135	11	)	)	PUNCT
ejpam-590	135	12	+	+	CCONJ
ejpam-590	135	13	xm(y	xm(y	NOUN
ejpam-590	135	14	,	,	PUNCT
ejpam-590	135	15	1	1	NUM
ejpam-590	135	16	)	)	PUNCT
ejpam-590	135	17	+	+	CCONJ
ejpam-590	135	18	(	(	PUNCT
ejpam-590	135	19	1−	1−	NUM
ejpam-590	135	20	y)h(x	y)h(x	NOUN
ejpam-590	135	21	,	,	PUNCT
ejpam-590	135	22	1	1	X
ejpam-590	135	23	)	)	PUNCT
ejpam-590	135	24	+	+	NUM
ejpam-590	135	25	yn(x	yn(x	NUM
ejpam-590	135	26	,	,	PUNCT
ejpam-590	135	27	1	1	X
ejpam-590	135	28	)	)	PUNCT
ejpam-590	135	29	−(1−	−(1−	ADP
ejpam-590	135	30	y)(1−	y)(1−	PROPN
ejpam-590	135	31	x)h(0,1)−	x)h(0,1)−	PROPN
ejpam-590	135	32	x(1−	x(1−	PROPN
ejpam-590	135	33	y)h(1,1)−	y)h(1,1)−	PROPN
ejpam-590	135	34	y(1−	y(1−	PROPN
ejpam-590	135	35	x)n(0,1)−	x)n(0,1)−	PROPN
ejpam-590	135	36	x	x	PROPN
ejpam-590	135	37	yn(1,1	yn(1,1	NOUN
ejpam-590	135	38	)	)	PUNCT
ejpam-590	135	39	}	}	PUNCT
ejpam-590	135	40	]	]	PUNCT
ejpam-590	136	1	+	+	PUNCT
ejpam-590	136	2	t(1−	t(1−	ADJ
ejpam-590	136	3	t)x(1−	t)x(1−	PROPN
ejpam-590	136	4	x)y(1−	x)y(1−	PROPN
ejpam-590	136	5	y)nω(x	y)nω(x	PROPN
ejpam-590	136	6	,	,	PUNCT
ejpam-590	136	7	y	y	PROPN
ejpam-590	136	8	,	,	PUNCT
ejpam-590	136	9	t	t	PROPN
ejpam-590	136	10	,	,	PUNCT
ejpam-590	136	11	p	p	NOUN
ejpam-590	136	12	)	)	PUNCT
ejpam-590	136	13	(	(	PUNCT
ejpam-590	136	14	14	14	NUM
ejpam-590	136	15	)	)	PUNCT
ejpam-590	136	16	where	where	SCONJ
ejpam-590	136	17	nω(x	nω(x	PUNCT
ejpam-590	136	18	,	,	PUNCT
ejpam-590	136	19	y	y	PROPN
ejpam-590	136	20	,	,	PUNCT
ejpam-590	136	21	t	t	PROPN
ejpam-590	136	22	,	,	PUNCT
ejpam-590	136	23	p	p	NOUN
ejpam-590	136	24	)	)	PUNCT
ejpam-590	136	25	=	=	SYM
ejpam-590	136	26	∑	∑	PUNCT
ejpam-590	136	27	vwσ(aw	vwσ(aw	NOUN
ejpam-590	136	28	x	x	PUNCT
ejpam-590	136	29	+	+	CCONJ
ejpam-590	136	30	bw	bw	PROPN
ejpam-590	136	31	y	y	PROPN
ejpam-590	136	32	+	+	PROPN
ejpam-590	136	33	cw	cw	PROPN
ejpam-590	136	34	t	t	PROPN
ejpam-590	136	35	+	+	CCONJ
ejpam-590	136	36	dw	dw	PROPN
ejpam-590	136	37	)	)	PUNCT
ejpam-590	136	38	;	;	PUNCT
ejpam-590	136	39	p	p	X
ejpam-590	136	40	=	=	X
ejpam-590	137	1	[	[	X
ejpam-590	137	2	vw	vw	X
ejpam-590	137	3	,	,	PUNCT
ejpam-590	137	4	aw	aw	INTJ
ejpam-590	137	5	,	,	PUNCT
ejpam-590	137	6	bw	bw	NOUN
ejpam-590	137	7	,	,	PUNCT
ejpam-590	137	8	cw	cw	NOUN
ejpam-590	137	9	,	,	PUNCT
ejpam-590	137	10	dw	dw	PROPN
ejpam-590	137	11	]	]	X
ejpam-590	137	12	t	t	PROPN
ejpam-590	137	13	is	be	AUX
ejpam-590	137	14	the	the	DET
ejpam-590	137	15	weight	weight	NOUN
ejpam-590	137	16	vector	vector	NOUN
ejpam-590	137	17	;	;	PUNCT
ejpam-590	137	18	i(x	i(x	PROPN
ejpam-590	137	19	,	,	PUNCT
ejpam-590	137	20	y	y	PROPN
ejpam-590	137	21	)	)	PUNCT
ejpam-590	137	22	=	=	SYM
ejpam-590	137	23	ω(x	ω(x	X
ejpam-590	137	24	,	,	PUNCT
ejpam-590	137	25	y	y	PROPN
ejpam-590	137	26	,	,	PUNCT
ejpam-590	137	27	0	0	NUM
ejpam-590	137	28	)	)	PUNCT
ejpam-590	137	29	is	be	AUX
ejpam-590	137	30	the	the	DET
ejpam-590	137	31	given	give	VERB
ejpam-590	137	32	initial	initial	ADJ
ejpam-590	137	33	condition	condition	NOUN
ejpam-590	137	34	and	and	CCONJ
ejpam-590	137	35	f(x	f(x	PROPN
ejpam-590	137	36	,	,	PUNCT
ejpam-590	137	37	y	y	PROPN
ejpam-590	137	38	)	)	PUNCT
ejpam-590	137	39	=	=	SYM
ejpam-590	137	40	ω(x	ω(x	X
ejpam-590	137	41	,	,	PUNCT
ejpam-590	137	42	y	y	PROPN
ejpam-590	137	43	,	,	PUNCT
ejpam-590	137	44	1	1	NUM
ejpam-590	137	45	)	)	PUNCT
ejpam-590	137	46	is	be	AUX
ejpam-590	137	47	the	the	DET
ejpam-590	137	48	final	final	ADJ
ejpam-590	137	49	required	require	VERB
ejpam-590	137	50	condition	condition	NOUN
ejpam-590	137	51	.	.	PUNCT
ejpam-590	138	1	using	use	VERB
ejpam-590	138	2	(	(	PUNCT
ejpam-590	138	3	10)-(11	10)-(11	NUM
ejpam-590	138	4	)	)	PUNCT
ejpam-590	138	5	the	the	DET
ejpam-590	138	6	trial	trial	NOUN
ejpam-590	138	7	solution	solution	NOUN
ejpam-590	138	8	becomes	become	VERB
ejpam-590	138	9	ωtr(x	ωtr(x	PROPN
ejpam-590	138	10	,	,	PUNCT
ejpam-590	138	11	y	y	PROPN
ejpam-590	138	12	,	,	PUNCT
ejpam-590	138	13	t	t	PROPN
ejpam-590	138	14	)	)	PUNCT
ejpam-590	138	15	=	=	PUNCT
ejpam-590	139	1	[	[	X
ejpam-590	139	2	1−	1−	NUM
ejpam-590	139	3	t	t	NOUN
ejpam-590	139	4	+	+	CCONJ
ejpam-590	139	5	t	t	PROPN
ejpam-590	139	6	exp(2π2ν)]π(sin(πx)+	exp(2π2ν)]π(sin(πx)+	PROPN
ejpam-590	139	7	sin(πy	sin(πy	NOUN
ejpam-590	139	8	)	)	PUNCT
ejpam-590	139	9	)	)	PUNCT
ejpam-590	140	1	+	+	CCONJ
ejpam-590	140	2	t(1−	t(1−	ADJ
ejpam-590	140	3	t)[(1−	t)[(1−	NOUN
ejpam-590	140	4	x)y(1−	x)y(1−	PROPN
ejpam-590	140	5	y)ng	y)ng	PROPN
ejpam-590	141	1	+	+	PROPN
ejpam-590	141	2	(	(	PUNCT
ejpam-590	141	3	1−	1−	NUM
ejpam-590	141	4	y)x(1−	y)x(1−	PROPN
ejpam-590	141	5	x)nh+	x)nh+	NUM
ejpam-590	141	6	x	x	PROPN
ejpam-590	141	7	y(1−	y(1−	PROPN
ejpam-590	141	8	y)nm+	y)nm+	PROPN
ejpam-590	142	1	y	y	PROPN
ejpam-590	142	2	x(1−	x(1−	PROPN
ejpam-590	142	3	x)nn+	x)nn+	PROPN
ejpam-590	142	4	(	(	PUNCT
ejpam-590	142	5	1−	1−	NUM
ejpam-590	142	6	x)(1−	x)(1−	PROPN
ejpam-590	142	7	y)n1	y)n1	PROPN
ejpam-590	142	8	+	+	CCONJ
ejpam-590	142	9	y(1−	y(1−	PROPN
ejpam-590	142	10	x)n2	x)n2	PROPN
ejpam-590	143	1	+	+	PROPN
ejpam-590	143	2	x(1−	x(1−	PROPN
ejpam-590	143	3	y)n3	y)n3	PROPN
ejpam-590	143	4	+	+	CCONJ
ejpam-590	143	5	x	x	SYM
ejpam-590	143	6	yn4	yn4	NOUN
ejpam-590	143	7	]	]	X
ejpam-590	143	8	+	+	CCONJ
ejpam-590	143	9	t(1−	t(1−	ADJ
ejpam-590	143	10	t)x(1−	t)x(1−	PROPN
ejpam-590	143	11	x)y(1−	x)y(1−	PROPN
ejpam-590	143	12	y)nω	y)nω	PROPN
ejpam-590	143	13	.	.	PUNCT
ejpam-590	144	1	(	(	PUNCT
ejpam-590	144	2	15	15	NUM
ejpam-590	144	3	)	)	PUNCT
ejpam-590	144	4	it	it	PRON
ejpam-590	144	5	can	can	AUX
ejpam-590	144	6	be	be	AUX
ejpam-590	144	7	easily	easily	ADV
ejpam-590	144	8	verified	verify	VERB
ejpam-590	144	9	that	that	SCONJ
ejpam-590	144	10	the	the	DET
ejpam-590	144	11	trial	trial	NOUN
ejpam-590	144	12	solution	solution	NOUN
ejpam-590	144	13	satisfies	satisfy	VERB
ejpam-590	144	14	all	all	DET
ejpam-590	144	15	initial	initial	ADJ
ejpam-590	144	16	and	and	CCONJ
ejpam-590	144	17	boundary	boundary	ADJ
ejpam-590	144	18	conditions	condition	NOUN
ejpam-590	144	19	.	.	PUNCT
ejpam-590	145	1	let	let	VERB
ejpam-590	145	2	us	we	PRON
ejpam-590	145	3	consider	consider	VERB
ejpam-590	145	4	the	the	DET
ejpam-590	145	5	grid	grid	NOUN
ejpam-590	145	6	points	point	NOUN
ejpam-590	145	7	in	in	ADP
ejpam-590	145	8	x	x	X
ejpam-590	145	9	,	,	PUNCT
ejpam-590	145	10	y	y	PROPN
ejpam-590	145	11	and	and	CCONJ
ejpam-590	145	12	t	t	PROPN
ejpam-590	145	13	as	as	ADP
ejpam-590	145	14	x	x	PROPN
ejpam-590	145	15	i	i	NOUN
ejpam-590	145	16	=	=	SYM
ejpam-590	145	17	(	(	PUNCT
ejpam-590	145	18	0.1)i	0.1)i	NOUN
ejpam-590	145	19	;	;	PUNCT
ejpam-590	145	20	i	i	NOUN
ejpam-590	145	21	=	=	NOUN
ejpam-590	145	22	0,1,2	0,1,2	NUM
ejpam-590	145	23	,	,	PUNCT
ejpam-590	145	24	.	.	PUNCT
ejpam-590	145	25	.	.	PUNCT
ejpam-590	146	1	.	.	PUNCT
ejpam-590	147	1	,	,	PUNCT
ejpam-590	147	2	9,10	9,10	NUM
ejpam-590	147	3	y	y	PROPN
ejpam-590	147	4	j	j	PROPN
ejpam-590	147	5	=	=	PUNCT
ejpam-590	147	6	(	(	PUNCT
ejpam-590	147	7	0.1	0.1	NUM
ejpam-590	147	8	)	)	PUNCT
ejpam-590	147	9	j	j	PROPN
ejpam-590	147	10	;	;	PUNCT
ejpam-590	147	11	j	j	PROPN
ejpam-590	147	12	=	=	SYM
ejpam-590	147	13	0,1,2	0,1,2	PROPN
ejpam-590	147	14	,	,	PUNCT
ejpam-590	147	15	.	.	PUNCT
ejpam-590	147	16	.	.	PUNCT
ejpam-590	147	17	.	.	PUNCT
ejpam-590	148	1	,	,	PUNCT
ejpam-590	148	2	9,10	9,10	NUM
ejpam-590	148	3	and	and	CCONJ
ejpam-590	148	4	tk	tk	PROPN
ejpam-590	148	5	=	=	SYM
ejpam-590	148	6	(	(	PUNCT
ejpam-590	148	7	0.1)k	0.1)k	NUM
ejpam-590	148	8	;	;	PUNCT
ejpam-590	148	9	k	k	PROPN
ejpam-590	148	10	=	=	PUNCT
ejpam-590	148	11	0,1,2	0,1,2	NUM
ejpam-590	148	12	,	,	PUNCT
ejpam-590	148	13	.	.	PUNCT
ejpam-590	148	14	.	.	PUNCT
ejpam-590	149	1	.	.	PUNCT
ejpam-590	150	1	,	,	PUNCT
ejpam-590	150	2	9,10	9,10	X
ejpam-590	150	3	.	.	PUNCT
ejpam-590	151	1	then	then	ADV
ejpam-590	151	2	the	the	DET
ejpam-590	151	3	error	error	NOUN
ejpam-590	151	4	function	function	NOUN
ejpam-590	151	5	is	be	AUX
ejpam-590	151	6	given	give	VERB
ejpam-590	151	7	by	by	ADP
ejpam-590	151	8	e	e	NOUN
ejpam-590	151	9	=	=	SYM
ejpam-590	151	10	∑	∑	PUNCT
ejpam-590	151	11	i	i	PRON
ejpam-590	151	12	∑	∑	PUNCT
ejpam-590	151	13	j	j	PROPN
ejpam-590	151	14	∑	∑	PROPN
ejpam-590	151	15	k	k	PROPN
ejpam-590	151	16	[	[	PUNCT
ejpam-590	151	17	∂	∂	NUM
ejpam-590	151	18	ωtr(xi	ωtr(xi	X
ejpam-590	151	19	,	,	PUNCT
ejpam-590	151	20	y	y	PROPN
ejpam-590	151	21	j	j	PROPN
ejpam-590	151	22	,	,	PUNCT
ejpam-590	151	23	tk	tk	PROPN
ejpam-590	151	24	)	)	PUNCT
ejpam-590	151	25	∂	∂	PROPN
ejpam-590	151	26	t	t	NOUN
ejpam-590	151	27	−	−	NOUN
ejpam-590	151	28	ν	ν	PROPN
ejpam-590	151	29	{	{	PUNCT
ejpam-590	151	30	∂	∂	NUM
ejpam-590	151	31	2ωtr(xi	2ωtr(xi	NUM
ejpam-590	151	32	,	,	PUNCT
ejpam-590	151	33	y	y	PROPN
ejpam-590	151	34	j	j	PROPN
ejpam-590	151	35	,	,	PUNCT
ejpam-590	151	36	tk	tk	PROPN
ejpam-590	151	37	)	)	PUNCT
ejpam-590	151	38	∂	∂	NOUN
ejpam-590	152	1	x2	x2	NOUN
ejpam-590	153	1	+	+	NUM
ejpam-590	153	2	∂	∂	NUM
ejpam-590	154	1	2ωtr(xi	2ωtr(xi	NUM
ejpam-590	154	2	,	,	PUNCT
ejpam-590	154	3	y	y	PROPN
ejpam-590	154	4	j	j	PROPN
ejpam-590	154	5	,	,	PUNCT
ejpam-590	154	6	tk	tk	PROPN
ejpam-590	154	7	)	)	PUNCT
ejpam-590	154	8	∂	∂	NOUN
ejpam-590	154	9	y2	y2	NOUN
ejpam-590	154	10	}	}	PUNCT
ejpam-590	154	11	−3π3ν	−3π3ν	ADJ
ejpam-590	154	12	exp(2π2ν	exp(2π2ν	PROPN
ejpam-590	154	13	tk)(sin(πx	tk)(sin(πx	NUM
ejpam-590	154	14	i	i	PROPN
ejpam-590	154	15	)	)	PUNCT
ejpam-590	154	16	+	+	CCONJ
ejpam-590	154	17	sin(πy	sin(πy	PROPN
ejpam-590	154	18	j	j	PROPN
ejpam-590	154	19	)	)	PUNCT
ejpam-590	154	20	)	)	PUNCT
ejpam-590	154	21	]	]	PUNCT
ejpam-590	154	22	2	2	NUM
ejpam-590	154	23	(	(	PUNCT
ejpam-590	154	24	16	16	NUM
ejpam-590	154	25	)	)	PUNCT
ejpam-590	154	26	which	which	PRON
ejpam-590	154	27	is	be	AUX
ejpam-590	154	28	to	to	PART
ejpam-590	154	29	be	be	AUX
ejpam-590	154	30	minimized	minimize	VERB
ejpam-590	154	31	with	with	ADP
ejpam-590	154	32	respect	respect	NOUN
ejpam-590	154	33	to	to	ADP
ejpam-590	154	34	all	all	DET
ejpam-590	154	35	weight	weight	NOUN
ejpam-590	154	36	parameters	parameter	NOUN
ejpam-590	154	37	p	p	X
ejpam-590	154	38	’s	’s	NOUN
ejpam-590	154	39	.	.	PUNCT
ejpam-590	155	1	now	now	ADV
ejpam-590	155	2	,	,	PUNCT
ejpam-590	155	3	the	the	DET
ejpam-590	155	4	real	real	ADJ
ejpam-590	155	5	coded	code	VERB
ejpam-590	155	6	ga	ga	PROPN
ejpam-590	155	7	,	,	PUNCT
ejpam-590	155	8	mi	mi	PROPN
ejpam-590	155	9	-	-	NOUN
ejpam-590	155	10	lxpm	lxpm	NOUN
ejpam-590	155	11	[	[	X
ejpam-590	155	12	5	5	NUM
ejpam-590	155	13	]	]	PUNCT
ejpam-590	155	14	,	,	PUNCT
ejpam-590	155	15	is	be	AUX
ejpam-590	155	16	used	use	VERB
ejpam-590	155	17	to	to	PART
ejpam-590	155	18	find	find	VERB
ejpam-590	155	19	out	out	ADP
ejpam-590	155	20	the	the	DET
ejpam-590	155	21	optimal	optimal	ADJ
ejpam-590	155	22	weight	weight	NOUN
ejpam-590	155	23	parameters	parameter	NOUN
ejpam-590	155	24	.	.	PUNCT
ejpam-590	156	1	the	the	DET
ejpam-590	156	2	exact	exact	ADJ
ejpam-590	156	3	solution	solution	NOUN
ejpam-590	156	4	of	of	ADP
ejpam-590	156	5	the	the	DET
ejpam-590	156	6	above	above	ADJ
ejpam-590	156	7	problem	problem	NOUN
ejpam-590	156	8	is	be	AUX
ejpam-590	156	9	given	give	VERB
ejpam-590	156	10	in	in	ADP
ejpam-590	156	11	[	[	X
ejpam-590	156	12	2	2	NUM
ejpam-590	156	13	]	]	PUNCT
ejpam-590	156	14	as	as	SCONJ
ejpam-590	156	15	follows	follow	VERB
ejpam-590	156	16	:	:	PUNCT
ejpam-590	156	17	the	the	DET
ejpam-590	156	18	(	(	PUNCT
ejpam-590	156	19	optimal	optimal	ADJ
ejpam-590	156	20	)	)	PUNCT
ejpam-590	156	21	control	control	NOUN
ejpam-590	156	22	function	function	NOUN
ejpam-590	156	23	is	be	AUX
ejpam-590	156	24	πexp(2π2ν	πexp(2π2ν	PROPN
ejpam-590	156	25	t	t	PROPN
ejpam-590	156	26	)	)	PUNCT
ejpam-590	156	27	sin(πx	sin(πx	NOUN
ejpam-590	156	28	)	)	PUNCT
ejpam-590	156	29	;	;	PUNCT
ejpam-590	156	30	for	for	ADP
ejpam-590	156	31	0	0	NUM
ejpam-590	156	32	<	<	X
ejpam-590	156	33	x	x	X
ejpam-590	156	34	<	<	X
ejpam-590	156	35	1	1	NUM
ejpam-590	156	36	;	;	PUNCT
ejpam-590	156	37	y	y	PROPN
ejpam-590	156	38	=	=	SYM
ejpam-590	156	39	0,1	0,1	NUM
ejpam-590	156	40	and	and	CCONJ
ejpam-590	156	41	πexp(2π2ν	πexp(2π2ν	PROPN
ejpam-590	156	42	t	t	PROPN
ejpam-590	156	43	)	)	PUNCT
ejpam-590	156	44	sin(πy	sin(πy	NOUN
ejpam-590	156	45	)	)	PUNCT
ejpam-590	156	46	;	;	PUNCT
ejpam-590	156	47	for	for	ADP
ejpam-590	156	48	0	0	NUM
ejpam-590	156	49	<	<	X
ejpam-590	156	50	y	y	X
ejpam-590	156	51	<	<	X
ejpam-590	156	52	1	1	NUM
ejpam-590	156	53	;	;	PUNCT
ejpam-590	156	54	x	x	SYM
ejpam-590	156	55	=	=	SYM
ejpam-590	156	56	0,1	0,1	NUM
ejpam-590	156	57	and	and	CCONJ
ejpam-590	156	58	the	the	DET
ejpam-590	156	59	temperature	temperature	NOUN
ejpam-590	156	60	ω	ω	PROPN
ejpam-590	156	61	being	be	AUX
ejpam-590	156	62	defined	define	VERB
ejpam-590	156	63	by	by	ADP
ejpam-590	156	64	ω(x	ω(x	X
ejpam-590	156	65	,	,	PUNCT
ejpam-590	156	66	y	y	PROPN
ejpam-590	156	67	,	,	PUNCT
ejpam-590	156	68	t	t	PROPN
ejpam-590	156	69	)	)	PUNCT
ejpam-590	156	70	=	=	SYM
ejpam-590	156	71	πexp(2π2ν	πexp(2π2ν	ADJ
ejpam-590	156	72	t)(sin(πx)+	t)(sin(πx)+	NOUN
ejpam-590	156	73	sin(πy	sin(πy	NOUN
ejpam-590	156	74	)	)	PUNCT
ejpam-590	156	75	)	)	PUNCT
ejpam-590	156	76	n.	n.	PROPN
ejpam-590	156	77	tomar	tomar	PROPN
ejpam-590	156	78	,	,	PUNCT
ejpam-590	156	79	n.	n.	NOUN
ejpam-590	156	80	sukavanam	sukavanam	NOUN
ejpam-590	156	81	,	,	PUNCT
ejpam-590	156	82	k.	k.	PROPN
ejpam-590	156	83	singh	singh	PROPN
ejpam-590	156	84	/	/	SYM
ejpam-590	156	85	eur	eur	PROPN
ejpam-590	156	86	.	.	PUNCT
ejpam-590	157	1	j.	j.	PROPN
ejpam-590	157	2	pure	pure	PROPN
ejpam-590	157	3	appl	appl	PROPN
ejpam-590	157	4	.	.	PROPN
ejpam-590	157	5	math	math	PROPN
ejpam-590	157	6	,	,	PUNCT
ejpam-590	157	7	4	4	NUM
ejpam-590	157	8	(	(	PUNCT
ejpam-590	157	9	2011	2011	NUM
ejpam-590	157	10	)	)	PUNCT
ejpam-590	157	11	,	,	PUNCT
ejpam-590	157	12	117	117	NUM
ejpam-590	157	13	-	-	SYM
ejpam-590	157	14	128	128	NUM
ejpam-590	157	15	123	123	NUM
ejpam-590	157	16	0	0	NUM
ejpam-590	157	17	0.5	0.5	NUM
ejpam-590	157	18	1	1	NUM
ejpam-590	157	19	0	0	NUM
ejpam-590	157	20	0.5	0.5	NUM
ejpam-590	157	21	1	1	NUM
ejpam-590	158	1	−0.02	−0.02	NOUN
ejpam-590	159	1	−0.01	−0.01	NOUN
ejpam-590	159	2	0	0	NUM
ejpam-590	159	3	0.01	0.01	NUM
ejpam-590	159	4	ty	ty	INTJ
ejpam-590	159	5	er	er	INTJ
ejpam-590	159	6	ro	ro	INTJ
ejpam-590	159	7	r	r	NOUN
ejpam-590	159	8	0	0	NUM
ejpam-590	159	9	0.5	0.5	NUM
ejpam-590	159	10	1	1	NUM
ejpam-590	159	11	0	0	NUM
ejpam-590	159	12	0.5	0.5	NUM
ejpam-590	159	13	1	1	NUM
ejpam-590	159	14	−0.02	−0.02	NOUN
ejpam-590	159	15	0	0	NUM
ejpam-590	159	16	0.02	0.02	NUM
ejpam-590	159	17	tx	tx	INTJ
ejpam-590	159	18	er	er	INTJ
ejpam-590	159	19	ro	ro	INTJ
ejpam-590	159	20	r	r	NOUN
ejpam-590	159	21	0	0	NUM
ejpam-590	159	22	0.5	0.5	NUM
ejpam-590	159	23	1	1	NUM
ejpam-590	159	24	0	0	NUM
ejpam-590	159	25	0.5	0.5	NUM
ejpam-590	159	26	1	1	NUM
ejpam-590	159	27	−0.01	−0.01	DET
ejpam-590	159	28	0	0	NUM
ejpam-590	159	29	0.01	0.01	NUM
ejpam-590	159	30	0.02	0.02	NUM
ejpam-590	160	1	ty	ty	INTJ
ejpam-590	161	1	er	er	INTJ
ejpam-590	161	2	ro	ro	INTJ
ejpam-590	161	3	r	r	NOUN
ejpam-590	161	4	0	0	NUM
ejpam-590	161	5	0.5	0.5	NUM
ejpam-590	161	6	1	1	NUM
ejpam-590	161	7	0	0	NUM
ejpam-590	161	8	0.5	0.5	NUM
ejpam-590	161	9	1	1	NUM
ejpam-590	161	10	−0.01	−0.01	DET
ejpam-590	161	11	0	0	NUM
ejpam-590	161	12	0.01	0.01	NUM
ejpam-590	161	13	tx	tx	INTJ
ejpam-590	161	14	er	er	INTJ
ejpam-590	161	15	ro	ro	INTJ
ejpam-590	161	16	r	r	NOUN
ejpam-590	161	17	(	(	PUNCT
ejpam-590	161	18	a	a	NOUN
ejpam-590	161	19	)	)	PUNCT
ejpam-590	161	20	(	(	PUNCT
ejpam-590	161	21	b	b	NOUN
ejpam-590	161	22	)	)	PUNCT
ejpam-590	161	23	(	(	PUNCT
ejpam-590	161	24	d)(c)figure	d)(c)figure	NOUN
ejpam-590	161	25	1	1	NUM
ejpam-590	161	26	:	:	PUNCT
ejpam-590	161	27	di	di	PROPN
ejpam-590	161	28	�	�	PROPN
ejpam-590	161	29	eren	eren	PROPN
ejpam-590	161	30	e	e	X
ejpam-590	161	31	between	between	ADP
ejpam-590	161	32	the	the	DET
ejpam-590	161	33	exa	exa	PROPN
ejpam-590	161	34	t	t	PROPN
ejpam-590	161	35	and	and	CCONJ
ejpam-590	161	36	omputed	omputed	ADJ
ejpam-590	161	37	values	value	NOUN
ejpam-590	161	38	of	of	ADP
ejpam-590	161	39	ontrol	ontrol	NOUN
ejpam-590	161	40	at	at	ADP
ejpam-590	161	41	boundary	boundary	NOUN
ejpam-590	161	42	(	(	PUNCT
ejpam-590	161	43	a)x	a)x	X
ejpam-590	161	44	=	=	SYM
ejpam-590	161	45	0	0	NUM
ejpam-590	161	46	(	(	PUNCT
ejpam-590	161	47	b)y	b)y	X
ejpam-590	161	48	=	=	SYM
ejpam-590	161	49	0	0	NUM
ejpam-590	161	50	(	(	PUNCT
ejpam-590	161	51	)	)	PUNCT
ejpam-590	161	52	x	x	SYM
ejpam-590	161	53	=	=	SYM
ejpam-590	161	54	1	1	NUM
ejpam-590	161	55	(	(	PUNCT
ejpam-590	161	56	d)y	d)y	NOUN
ejpam-590	161	57	=	=	SYM
ejpam-590	161	58	1	1	NUM
ejpam-590	161	59	the	the	DET
ejpam-590	161	60	figure	figure	NOUN
ejpam-590	161	61	1	1	NUM
ejpam-590	161	62	represents	represent	VERB
ejpam-590	161	63	the	the	DET
ejpam-590	161	64	error	error	NOUN
ejpam-590	161	65	between	between	ADP
ejpam-590	161	66	exact	exact	ADJ
ejpam-590	161	67	and	and	CCONJ
ejpam-590	161	68	computed	compute	VERB
ejpam-590	161	69	control	control	NOUN
ejpam-590	161	70	functions	function	NOUN
ejpam-590	161	71	at	at	ADP
ejpam-590	161	72	the	the	DET
ejpam-590	161	73	boundary	boundary	NOUN
ejpam-590	161	74	.	.	PUNCT
ejpam-590	162	1	the	the	DET
ejpam-590	162	2	figure	figure	NOUN
ejpam-590	162	3	2	2	NUM
ejpam-590	162	4	and	and	CCONJ
ejpam-590	162	5	tables	table	NOUN
ejpam-590	162	6	1	1	NUM
ejpam-590	162	7	-	-	SYM
ejpam-590	162	8	6	6	NUM
ejpam-590	162	9	describe	describe	VERB
ejpam-590	162	10	the	the	DET
ejpam-590	162	11	pointwise	pointwise	NOUN
ejpam-590	162	12	error	error	NOUN
ejpam-590	162	13	between	between	ADP
ejpam-590	162	14	exact	exact	ADJ
ejpam-590	162	15	and	and	CCONJ
ejpam-590	162	16	calculated	calculate	VERB
ejpam-590	162	17	temperature	temperature	NOUN
ejpam-590	162	18	distribution	distribution	NOUN
ejpam-590	162	19	on	on	ADP
ejpam-590	162	20	the	the	DET
ejpam-590	162	21	region	region	NOUN
ejpam-590	162	22	ω	ω	NOUN
ejpam-590	162	23	at	at	ADP
ejpam-590	162	24	some	some	DET
ejpam-590	162	25	intermediate	intermediate	ADJ
ejpam-590	162	26	time	time	NOUN
ejpam-590	162	27	points	point	NOUN
ejpam-590	162	28	between	between	ADP
ejpam-590	162	29	0	0	NUM
ejpam-590	162	30	and	and	CCONJ
ejpam-590	162	31	1.table	1.table	NUM
ejpam-590	162	32	1	1	NUM
ejpam-590	162	33	:	:	PUNCT
ejpam-590	162	34	di	di	PROPN
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ejpam-590	167	1	-0.00029	-0.00029	PROPN
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ejpam-590	168	1	0.00044	0.00044	NUM
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ejpam-590	168	5	-0.00051	-0.00051	NOUN
ejpam-590	169	1	0.000356	0.000356	NUM
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ejpam-590	169	12	1.0	1.0	NUM
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ejpam-590	170	14	128	128	NUM
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ejpam-590	170	17	0.5	0.5	NUM
ejpam-590	170	18	1	1	NUM
ejpam-590	170	19	0	0	NUM
ejpam-590	170	20	0.5	0.5	NUM
ejpam-590	170	21	1	1	NUM
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ejpam-590	171	11	0	0	NUM
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ejpam-590	173	6	1	1	NUM
ejpam-590	173	7	0	0	NUM
ejpam-590	173	8	0.5	0.5	NUM
ejpam-590	173	9	1	1	NUM
ejpam-590	173	10	−0.02	−0.02	NOUN
ejpam-590	173	11	0	0	NUM
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ejpam-590	173	18	0.5	0.5	NUM
ejpam-590	173	19	1	1	NUM
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ejpam-590	173	21	0.5	0.5	NUM
ejpam-590	173	22	1	1	NUM
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ejpam-590	173	24	0	0	NUM
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ejpam-590	173	35	1	1	NUM
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ejpam-590	173	50	0	0	NUM
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ejpam-590	173	76	0	0	NUM
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ejpam-590	174	36	d)t	d)t	NOUN
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ejpam-590	174	40	e)t	e)t	NOUN
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ejpam-590	174	44	f)t	f)t	VERB
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ejpam-590	174	52	h)t	h)t	NOUN
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ejpam-590	178	5	0.4	0.4	NUM
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ejpam-590	203	3	0.000539	0.000539	NUM
ejpam-590	203	4	0.000527	0.000527	NUM
ejpam-590	203	5	0.001222	0.001222	NUM
ejpam-590	203	6	0.000816	0.000816	NUM
ejpam-590	203	7	-0.00134	-0.00134	NOUN
ejpam-590	203	8	1.0	1.0	NUM
ejpam-590	203	9	0.009157	0.009157	NUM
ejpam-590	203	10	-0.00121	-0.00121	NOUN
ejpam-590	204	1	-1.4e-05	-1.4e-05	PUNCT
ejpam-590	205	1	0.001639	0.001639	NUM
ejpam-590	205	2	0.001541	0.001541	NUM
ejpam-590	205	3	-0.00121	-0.00121	NOUN
ejpam-590	205	4	table	table	NOUN
ejpam-590	205	5	6	6	NUM
ejpam-590	205	6	:	:	PUNCT
ejpam-590	205	7	di	di	PROPN
ejpam-590	205	8	�	�	PROPN
ejpam-590	205	9	eren	eren	PROPN
ejpam-590	205	10	e	e	X
ejpam-590	205	11	between	between	ADP
ejpam-590	205	12	the	the	DET
ejpam-590	205	13	exa	exa	PROPN
ejpam-590	205	14	t	t	PROPN
ejpam-590	205	15	and	and	CCONJ
ejpam-590	205	16	computed	compute	VERB
ejpam-590	205	17	values	value	NOUN
ejpam-590	205	18	of	of	ADP
ejpam-590	205	19	temperature	temperature	NOUN
ejpam-590	205	20	distribution	distribution	NOUN
ejpam-590	205	21	at	at	ADP
ejpam-590	205	22	time	time	NOUN
ejpam-590	205	23	t	t	NOUN
ejpam-590	205	24	=	=	PUNCT
ejpam-590	205	25	0.9	0.9	NUM
ejpam-590	205	26	y	y	NOUN
ejpam-590	205	27	x	x	PROPN
ejpam-590	205	28	0.0	0.0	NUM
ejpam-590	205	29	0.2	0.2	NUM
ejpam-590	205	30	0.4	0.4	NUM
ejpam-590	205	31	0.6	0.6	NUM
ejpam-590	205	32	0.8	0.8	NUM
ejpam-590	205	33	1.0	1.0	NUM
ejpam-590	205	34	0.0	0.0	NUM
ejpam-590	205	35	-0.00116	-0.00116	NOUN
ejpam-590	205	36	-0.00142	-0.00142	PROPN
ejpam-590	206	1	-0.00136	-0.00136	PROPN
ejpam-590	206	2	-0.00099	-0.00099	PUNCT
ejpam-590	207	1	-0.0003	-0.0003	VERB
ejpam-590	207	2	0.00255	0.00255	NUM
ejpam-590	207	3	0.1	0.1	NUM
ejpam-590	207	4	-0.00037	-0.00037	NOUN
ejpam-590	207	5	-0.00128	-0.00128	NOUN
ejpam-590	207	6	-0.0014	-0.0014	PROPN
ejpam-590	207	7	-0.00101	-0.00101	PROPN
ejpam-590	207	8	-0.0006	-0.0006	NOUN
ejpam-590	208	1	0.001097	0.001097	NUM
ejpam-590	208	2	0.2	0.2	NUM
ejpam-590	208	3	0.000944	0.000944	NUM
ejpam-590	208	4	-0.00064	-0.00064	NOUN
ejpam-590	208	5	-0.00109	-0.00109	VERB
ejpam-590	208	6	-0.00085	-0.00085	PUNCT
ejpam-590	209	1	-0.00072	-0.00072	VERB
ejpam-590	210	1	0.000112	0.000112	NUM
ejpam-590	210	2	0.3	0.3	NUM
ejpam-590	210	3	0.002166	0.002166	NUM
ejpam-590	210	4	5.63e-06	5.63e-06	NUM
ejpam-590	210	5	-0.00071	-0.00071	NOUN
ejpam-590	210	6	-0.00061	-0.00061	PROPN
ejpam-590	210	7	-0.00064	-0.00064	PROPN
ejpam-590	210	8	-0.00034	-0.00034	PROPN
ejpam-590	211	1	0.4	0.4	NUM
ejpam-590	211	2	0.002943	0.002943	NUM
ejpam-590	211	3	0.000227	0.000227	NUM
ejpam-590	211	4	-0.00072	-0.00072	NOUN
ejpam-590	211	5	-0.00078	-0.00078	PROPN
ejpam-590	211	6	-0.00097	-0.00097	PROPN
ejpam-590	211	7	-0.00102	-0.00102	PROPN
ejpam-590	211	8	0.5	0.5	NUM
ejpam-590	211	9	0.003754	0.003754	NUM
ejpam-590	211	10	0.000505	0.000505	NUM
ejpam-590	211	11	-0.00065	-0.00065	NOUN
ejpam-590	211	12	-0.00088	-0.00088	NOUN
ejpam-590	211	13	-0.00125	-0.00125	NOUN
ejpam-590	211	14	-0.00154	-0.00154	VERB
ejpam-590	211	15	0.6	0.6	NUM
ejpam-590	211	16	0.004704	0.004704	NUM
ejpam-590	211	17	0.001148	0.001148	NUM
ejpam-590	211	18	-0.0001	-0.0001	NOUN
ejpam-590	211	19	-0.00036	-0.00036	NOUN
ejpam-590	211	20	-0.0008	-0.0008	NOUN
ejpam-590	211	21	-0.00116	-0.00116	VERB
ejpam-590	211	22	0.7	0.7	NUM
ejpam-590	211	23	0.005135	0.005135	NUM
ejpam-590	211	24	0.001674	0.001674	NUM
ejpam-590	211	25	0.000597	0.000597	NUM
ejpam-590	211	26	0.00056	0.00056	NUM
ejpam-590	211	27	0.000276	0.000276	NUM
ejpam-590	211	28	6.22e-05	6.22e-05	NUM
ejpam-590	211	29	0.8	0.8	NUM
ejpam-590	211	30	0.004602	0.004602	NUM
ejpam-590	212	1	0.001318	0.001318	NUM
ejpam-590	212	2	0.000459	0.000459	NUM
ejpam-590	212	3	0.000643	0.000643	NUM
ejpam-590	212	4	0.00043	0.00043	NUM
ejpam-590	212	5	0.000228	0.000228	NUM
ejpam-590	212	6	0.9	0.9	NUM
ejpam-590	212	7	0.003754	0.003754	NUM
ejpam-590	212	8	0.000394	0.000394	NUM
ejpam-590	212	9	-0.00013	-0.00013	NOUN
ejpam-590	212	10	0.000315	0.000315	NUM
ejpam-590	212	11	5.77e-05	5.77e-05	NUM
ejpam-590	212	12	-0.00041	-0.00041	NOUN
ejpam-590	212	13	1.0	1.0	NUM
ejpam-590	212	14	0.004129	0.004129	NUM
ejpam-590	212	15	-0.0002	-0.0002	NOUN
ejpam-590	212	16	-8.6e-05	-8.6e-05	PUNCT
ejpam-590	213	1	0.000899	0.000899	NUM
ejpam-590	213	2	0.000611	0.000611	NUM
ejpam-590	213	3	-0.00043	-0.00043	NOUN
ejpam-590	213	4	references	reference	VERB
ejpam-590	213	5	127	127	NUM
ejpam-590	213	6	conclusions	conclusion	NOUN
ejpam-590	213	7	a	a	DET
ejpam-590	213	8	numerical	numerical	ADJ
ejpam-590	213	9	method	method	NOUN
ejpam-590	213	10	has	have	AUX
ejpam-590	213	11	been	be	AUX
ejpam-590	213	12	presented	present	VERB
ejpam-590	213	13	for	for	ADP
ejpam-590	213	14	computation	computation	NOUN
ejpam-590	213	15	of	of	ADP
ejpam-590	213	16	boundary	boundary	ADJ
ejpam-590	213	17	control	control	NOUN
ejpam-590	213	18	of	of	ADP
ejpam-590	213	19	controlled	control	VERB
ejpam-590	213	20	heat	heat	NOUN
ejpam-590	213	21	equation	equation	NOUN
ejpam-590	213	22	.	.	PUNCT
ejpam-590	214	1	it	it	PRON
ejpam-590	214	2	is	be	AUX
ejpam-590	214	3	hybridization	hybridization	NOUN
ejpam-590	214	4	of	of	ADP
ejpam-590	214	5	the	the	DET
ejpam-590	214	6	function	function	NOUN
ejpam-590	214	7	approximation	approximation	NOUN
ejpam-590	214	8	capabilities	capability	NOUN
ejpam-590	214	9	of	of	ADP
ejpam-590	214	10	feed	feed	NOUN
ejpam-590	214	11	forward	forward	ADV
ejpam-590	214	12	neural	neural	ADJ
ejpam-590	214	13	network	network	NOUN
ejpam-590	214	14	and	and	CCONJ
ejpam-590	214	15	global	global	ADJ
ejpam-590	214	16	optimization	optimization	NOUN
ejpam-590	214	17	capabilities	capability	NOUN
ejpam-590	214	18	of	of	ADP
ejpam-590	214	19	genetic	genetic	ADJ
ejpam-590	214	20	algorithm	algorithm	NOUN
ejpam-590	214	21	.	.	PUNCT
ejpam-590	215	1	the	the	DET
ejpam-590	215	2	solutions	solution	NOUN
ejpam-590	215	3	of	of	ADP
ejpam-590	215	4	controlled	control	VERB
ejpam-590	215	5	heat	heat	NOUN
ejpam-590	215	6	equation	equation	NOUN
ejpam-590	215	7	problems	problem	NOUN
ejpam-590	215	8	obtained	obtain	VERB
ejpam-590	215	9	through	through	ADP
ejpam-590	215	10	this	this	DET
ejpam-590	215	11	approach	approach	NOUN
ejpam-590	215	12	compare	compare	VERB
ejpam-590	215	13	very	very	ADV
ejpam-590	215	14	well	well	ADV
ejpam-590	215	15	with	with	ADP
ejpam-590	215	16	the	the	DET
ejpam-590	215	17	exact	exact	ADJ
ejpam-590	215	18	solutions	solution	NOUN
ejpam-590	215	19	.	.	PUNCT
ejpam-590	216	1	computational	computational	ADJ
ejpam-590	216	2	experience	experience	NOUN
ejpam-590	216	3	in	in	ADP
ejpam-590	216	4	using	use	VERB
ejpam-590	216	5	proposed	propose	VERB
ejpam-590	216	6	ann	ann	PROPN
ejpam-590	216	7	-	-	PUNCT
ejpam-590	216	8	ga	ga	PROPN
ejpam-590	216	9	algorithm	algorithm	NOUN
ejpam-590	216	10	in	in	ADP
ejpam-590	216	11	solving	solve	VERB
ejpam-590	216	12	this	this	DET
ejpam-590	216	13	heat	heat	NOUN
ejpam-590	216	14	equation	equation	NOUN
ejpam-590	216	15	problem	problem	NOUN
ejpam-590	216	16	has	have	AUX
ejpam-590	216	17	shown	show	VERB
ejpam-590	216	18	that	that	SCONJ
ejpam-590	216	19	the	the	DET
ejpam-590	216	20	total	total	ADJ
ejpam-590	216	21	time	time	NOUN
ejpam-590	216	22	requirement	requirement	NOUN
ejpam-590	216	23	of	of	ADP
ejpam-590	216	24	this	this	DET
ejpam-590	216	25	technique	technique	NOUN
ejpam-590	216	26	is	be	AUX
ejpam-590	216	27	less	less	ADJ
ejpam-590	216	28	then	then	ADV
ejpam-590	216	29	to	to	PART
ejpam-590	216	30	compare	compare	VERB
ejpam-590	216	31	with	with	ADP
ejpam-590	216	32	other	other	ADJ
ejpam-590	216	33	local	local	ADJ
ejpam-590	216	34	search	search	NOUN
ejpam-590	216	35	techniques	technique	NOUN
ejpam-590	216	36	like	like	ADP
ejpam-590	216	37	gradient	gradient	ADJ
ejpam-590	216	38	descent	descent	NOUN
ejpam-590	216	39	method	method	NOUN
ejpam-590	216	40	,	,	PUNCT
ejpam-590	216	41	because	because	SCONJ
ejpam-590	216	42	the	the	DET
ejpam-590	216	43	time	time	NOUN
ejpam-590	216	44	has	have	AUX
ejpam-590	216	45	been	be	AUX
ejpam-590	216	46	compared	compare	VERB
ejpam-590	216	47	to	to	ADP
ejpam-590	216	48	those	those	PRON
ejpam-590	216	49	taken	take	VERB
ejpam-590	216	50	by	by	ADP
ejpam-590	216	51	conventional	conventional	ADJ
ejpam-590	216	52	method	method	NOUN
ejpam-590	216	53	used	use	VERB
ejpam-590	216	54	by	by	ADP
ejpam-590	216	55	sukavanam	sukavanam	NOUN
ejpam-590	216	56	and	and	CCONJ
ejpam-590	216	57	panwar	panwar	VERB
ejpam-590	216	58	[	[	X
ejpam-590	216	59	15	15	NUM
ejpam-590	216	60	]	]	PUNCT
ejpam-590	216	61	.	.	PUNCT
ejpam-590	217	1	conventional	conventional	ADJ
ejpam-590	217	2	search	search	NOUN
ejpam-590	217	3	techniques	technique	NOUN
ejpam-590	217	4	depend	depend	VERB
ejpam-590	217	5	on	on	ADP
ejpam-590	217	6	an	an	DET
ejpam-590	217	7	initial	initial	ADJ
ejpam-590	217	8	guess	guess	NOUN
ejpam-590	217	9	,	,	PUNCT
ejpam-590	217	10	so	so	SCONJ
ejpam-590	217	11	these	these	DET
ejpam-590	217	12	techniques	technique	NOUN
ejpam-590	217	13	generally	generally	ADV
ejpam-590	217	14	give	give	VERB
ejpam-590	217	15	local	local	ADJ
ejpam-590	217	16	optimal	optimal	ADJ
ejpam-590	217	17	solutions	solution	NOUN
ejpam-590	217	18	.	.	PUNCT
ejpam-590	218	1	however	however	ADV
ejpam-590	218	2	,	,	PUNCT
ejpam-590	218	3	initial	initial	ADJ
ejpam-590	218	4	guess	guess	NOUN
ejpam-590	218	5	is	be	AUX
ejpam-590	218	6	not	not	PART
ejpam-590	218	7	required	require	VERB
ejpam-590	218	8	in	in	ADP
ejpam-590	218	9	proposed	propose	VERB
ejpam-590	218	10	annga	annga	NOUN
ejpam-590	218	11	technique	technique	NOUN
ejpam-590	218	12	.	.	PUNCT
ejpam-590	219	1	since	since	SCONJ
ejpam-590	219	2	,	,	PUNCT
ejpam-590	219	3	ga	ga	PROPN
ejpam-590	219	4	works	work	VERB
ejpam-590	219	5	on	on	ADP
ejpam-590	219	6	population	population	NOUN
ejpam-590	219	7	of	of	ADP
ejpam-590	219	8	almost	almost	ADV
ejpam-590	219	9	all	all	PRON
ejpam-590	219	10	possible	possible	ADJ
ejpam-590	219	11	solutions	solution	NOUN
ejpam-590	219	12	,	,	PUNCT
ejpam-590	219	13	it	it	PRON
ejpam-590	219	14	gives	give	VERB
ejpam-590	219	15	,	,	PUNCT
ejpam-590	219	16	mostly	mostly	ADV
ejpam-590	219	17	,	,	PUNCT
ejpam-590	219	18	global	global	ADJ
ejpam-590	219	19	optimal	optimal	ADJ
ejpam-590	219	20	solution	solution	NOUN
ejpam-590	219	21	.	.	PUNCT
ejpam-590	220	1	the	the	DET
ejpam-590	220	2	methodology	methodology	NOUN
ejpam-590	220	3	discussed	discuss	VERB
ejpam-590	220	4	here	here	ADV
ejpam-590	220	5	can	can	AUX
ejpam-590	220	6	be	be	AUX
ejpam-590	220	7	applied	apply	VERB
ejpam-590	220	8	to	to	ADP
ejpam-590	220	9	both	both	CCONJ
ejpam-590	220	10	linear	linear	ADJ
ejpam-590	220	11	and	and	CCONJ
ejpam-590	220	12	nonlinear	nonlinear	ADJ
ejpam-590	220	13	state	state	NOUN
ejpam-590	220	14	equation	equation	NOUN
ejpam-590	220	15	and	and	CCONJ
ejpam-590	220	16	this	this	DET
ejpam-590	220	17	technique	technique	NOUN
ejpam-590	220	18	may	may	AUX
ejpam-590	220	19	be	be	AUX
ejpam-590	220	20	further	far	ADV
ejpam-590	220	21	hybridized	hybridize	VERB
ejpam-590	220	22	with	with	ADP
ejpam-590	220	23	local	local	ADJ
ejpam-590	220	24	search	search	NOUN
ejpam-590	220	25	techniques	technique	NOUN
ejpam-590	220	26	to	to	PART
ejpam-590	220	27	find	find	VERB
ejpam-590	220	28	more	more	ADJ
ejpam-590	220	29	precise	precise	ADJ
ejpam-590	220	30	solutions	solution	NOUN
ejpam-590	220	31	.	.	PUNCT
ejpam-590	221	1	the	the	DET
ejpam-590	221	2	operational	operational	ADJ
ejpam-590	221	3	range	range	NOUN
ejpam-590	221	4	of	of	ADP
ejpam-590	221	5	the	the	DET
ejpam-590	221	6	proposed	propose	VERB
ejpam-590	221	7	,	,	PUNCT
ejpam-590	221	8	ann	ann	PROPN
ejpam-590	221	9	-	-	PUNCT
ejpam-590	221	10	ga	ga	PROPN
ejpam-590	221	11	,	,	PUNCT
ejpam-590	221	12	technique	technique	NOUN
ejpam-590	221	13	can	can	AUX
ejpam-590	221	14	also	also	ADV
ejpam-590	221	15	be	be	AUX
ejpam-590	221	16	extended	extend	VERB
ejpam-590	221	17	for	for	ADP
ejpam-590	221	18	the	the	DET
ejpam-590	221	19	optimal	optimal	ADJ
ejpam-590	221	20	control	control	NOUN
ejpam-590	221	21	problems	problem	NOUN
ejpam-590	221	22	by	by	ADP
ejpam-590	221	23	converting	convert	VERB
ejpam-590	221	24	them	they	PRON
ejpam-590	221	25	into	into	ADP
ejpam-590	221	26	constrained	constrain	VERB
ejpam-590	221	27	optimization	optimization	NOUN
ejpam-590	221	28	problems	problem	NOUN
ejpam-590	221	29	via	via	ADP
ejpam-590	221	30	neural	neural	ADJ
ejpam-590	221	31	networks	network	NOUN
ejpam-590	221	32	or	or	CCONJ
ejpam-590	221	33	any	any	DET
ejpam-590	221	34	other	other	ADJ
ejpam-590	221	35	discretization	discretization	NOUN
ejpam-590	221	36	method	method	NOUN
ejpam-590	221	37	.	.	PUNCT
ejpam-590	222	1	references	reference	NOUN
ejpam-590	222	2	[	[	X
ejpam-590	222	3	1	1	NUM
ejpam-590	222	4	]	]	PUNCT
ejpam-590	222	5	y	y	PROPN
ejpam-590	222	6	arfiadi	arfiadi	NOUN
ejpam-590	222	7	and	and	CCONJ
ejpam-590	222	8	m	m	VERB
ejpam-590	222	9	n	n	NOUN
ejpam-590	222	10	s	s	PART
ejpam-590	222	11	hadi	hadi	NOUN
ejpam-590	222	12	.	.	PUNCT
ejpam-590	223	1	optimal	optimal	ADJ
ejpam-590	223	2	direct	direct	ADJ
ejpam-590	223	3	(	(	PUNCT
ejpam-590	223	4	static	static	ADJ
ejpam-590	223	5	)	)	PUNCT
ejpam-590	223	6	output	output	NOUN
ejpam-590	223	7	feedback	feedback	NOUN
ejpam-590	223	8	controller	controller	NOUN
ejpam-590	223	9	using	use	VERB
ejpam-590	223	10	real	real	ADJ
ejpam-590	223	11	coded	code	VERB
ejpam-590	223	12	genetic	genetic	ADJ
ejpam-590	223	13	algorithms	algorithm	NOUN
ejpam-590	223	14	.	.	PUNCT
ejpam-590	224	1	computers	computer	NOUN
ejpam-590	224	2	and	and	CCONJ
ejpam-590	224	3	structures	structure	NOUN
ejpam-590	224	4	,	,	PUNCT
ejpam-590	224	5	79:1625–1634	79:1625–1634	NUM
ejpam-590	224	6	,	,	PUNCT
ejpam-590	224	7	2001	2001	NUM
ejpam-590	224	8	.	.	PUNCT
ejpam-590	225	1	[	[	X
ejpam-590	225	2	2	2	NUM
ejpam-590	225	3	]	]	X
ejpam-590	225	4	c	c	X
ejpam-590	225	5	carthel	carthel	PROPN
ejpam-590	225	6	,	,	PUNCT
ejpam-590	225	7	r	r	NOUN
ejpam-590	225	8	glowinski	glowinski	NOUN
ejpam-590	225	9	,	,	PUNCT
ejpam-590	225	10	and	and	CCONJ
ejpam-590	225	11	j	j	PROPN
ejpam-590	225	12	l	l	NOUN
ejpam-590	225	13	lions	lion	NOUN
ejpam-590	225	14	.	.	PUNCT
ejpam-590	226	1	on	on	ADP
ejpam-590	226	2	exact	exact	ADJ
ejpam-590	226	3	and	and	CCONJ
ejpam-590	226	4	approximate	approximate	ADJ
ejpam-590	226	5	boundary	boundary	ADJ
ejpam-590	226	6	controllabilities	controllabilitie	NOUN
ejpam-590	226	7	for	for	ADP
ejpam-590	226	8	the	the	DET
ejpam-590	226	9	heat	heat	NOUN
ejpam-590	226	10	equation	equation	NOUN
ejpam-590	226	11	:	:	PUNCT
ejpam-590	226	12	a	a	DET
ejpam-590	226	13	numerical	numerical	ADJ
ejpam-590	226	14	approach	approach	NOUN
ejpam-590	226	15	.	.	PUNCT
ejpam-590	227	1	journal	journal	NOUN
ejpam-590	227	2	of	of	ADP
ejpam-590	227	3	optimization	optimization	NOUN
ejpam-590	227	4	theory	theory	NOUN
ejpam-590	227	5	and	and	CCONJ
ejpam-590	227	6	applications	application	NOUN
ejpam-590	227	7	,	,	PUNCT
ejpam-590	227	8	82(2):429–484	82(2):429–484	PROPN
ejpam-590	227	9	,	,	PUNCT
ejpam-590	227	10	1994	1994	NUM
ejpam-590	227	11	.	.	PUNCT
ejpam-590	228	1	[	[	X
ejpam-590	228	2	3	3	X
ejpam-590	228	3	]	]	X
ejpam-590	228	4	w	w	PROPN
ejpam-590	228	5	d	d	PROPN
ejpam-590	228	6	chang	chang	PROPN
ejpam-590	228	7	.	.	PUNCT
ejpam-590	229	1	nonlinear	nonlinear	ADJ
ejpam-590	229	2	system	system	NOUN
ejpam-590	229	3	identification	identification	NOUN
ejpam-590	229	4	and	and	CCONJ
ejpam-590	229	5	control	control	NOUN
ejpam-590	229	6	using	use	VERB
ejpam-590	229	7	a	a	DET
ejpam-590	229	8	real	real	ADV
ejpam-590	229	9	-	-	PUNCT
ejpam-590	229	10	coded	code	VERB
ejpam-590	229	11	genetic	genetic	ADJ
ejpam-590	229	12	algorithm	algorithm	NOUN
ejpam-590	229	13	.	.	PUNCT
ejpam-590	230	1	applied	apply	VERB
ejpam-590	230	2	mathematical	mathematical	ADJ
ejpam-590	230	3	modelling	modelling	NOUN
ejpam-590	230	4	,	,	PUNCT
ejpam-590	230	5	31:541–550	31:541–550	PROPN
ejpam-590	230	6	,	,	PUNCT
ejpam-590	230	7	2007	2007	NUM
ejpam-590	230	8	.	.	PUNCT
ejpam-590	231	1	[	[	X
ejpam-590	231	2	4	4	X
ejpam-590	231	3	]	]	X
ejpam-590	231	4	j	j	PROPN
ejpam-590	231	5	m	m	X
ejpam-590	231	6	coron	coron	ADJ
ejpam-590	231	7	and	and	CCONJ
ejpam-590	231	8	e	e	NOUN
ejpam-590	231	9	trelat	trelat	NOUN
ejpam-590	231	10	.	.	PUNCT
ejpam-590	232	1	global	global	ADJ
ejpam-590	232	2	steady	steady	ADJ
ejpam-590	232	3	-	-	PUNCT
ejpam-590	232	4	state	state	NOUN
ejpam-590	232	5	controllability	controllability	NOUN
ejpam-590	232	6	of	of	ADP
ejpam-590	232	7	one	one	NUM
ejpam-590	232	8	-	-	PUNCT
ejpam-590	232	9	dimensional	dimensional	ADJ
ejpam-590	232	10	semilinear	semilinear	ADJ
ejpam-590	232	11	heat	heat	NOUN
ejpam-590	232	12	equation	equation	NOUN
ejpam-590	232	13	.	.	PUNCT
ejpam-590	233	1	siam	siam	PROPN
ejpam-590	233	2	j.	j.	PROPN
ejpam-590	233	3	control	control	PROPN
ejpam-590	233	4	,	,	PUNCT
ejpam-590	233	5	43(2):549–569	43(2):549–569	PROPN
ejpam-590	233	6	,	,	PUNCT
ejpam-590	233	7	2004	2004	NUM
ejpam-590	233	8	.	.	PUNCT
ejpam-590	234	1	[	[	X
ejpam-590	234	2	5	5	NUM
ejpam-590	234	3	]	]	X
ejpam-590	234	4	k	k	X
ejpam-590	234	5	deep	deep	ADJ
ejpam-590	234	6	,	,	PUNCT
ejpam-590	234	7	k	k	PROPN
ejpam-590	234	8	p	p	PROPN
ejpam-590	234	9	singh	singh	PROPN
ejpam-590	234	10	,	,	PUNCT
ejpam-590	234	11	m	m	PROPN
ejpam-590	234	12	l	l	NOUN
ejpam-590	234	13	kansal	kansal	NOUN
ejpam-590	234	14	,	,	PUNCT
ejpam-590	234	15	and	and	CCONJ
ejpam-590	234	16	c	c	PROPN
ejpam-590	234	17	mohan	mohan	PROPN
ejpam-590	234	18	.	.	PUNCT
ejpam-590	235	1	a	a	DET
ejpam-590	235	2	real	real	ADV
ejpam-590	235	3	coded	code	VERB
ejpam-590	235	4	genetic	genetic	ADJ
ejpam-590	235	5	algorithm	algorithm	NOUN
ejpam-590	235	6	for	for	ADP
ejpam-590	235	7	solving	solve	VERB
ejpam-590	235	8	integer	integer	NOUN
ejpam-590	235	9	and	and	CCONJ
ejpam-590	235	10	mixed	mixed	ADJ
ejpam-590	235	11	integer	integer	NOUN
ejpam-590	235	12	optimization	optimization	NOUN
ejpam-590	235	13	problems	problem	NOUN
ejpam-590	235	14	.	.	PUNCT
ejpam-590	236	1	applied	apply	VERB
ejpam-590	236	2	mathematics	mathematic	NOUN
ejpam-590	236	3	and	and	CCONJ
ejpam-590	236	4	computation	computation	NOUN
ejpam-590	236	5	,	,	PUNCT
ejpam-590	236	6	212(2):505–518	212(2):505–518	NUM
ejpam-590	236	7	,	,	PUNCT
ejpam-590	236	8	2009	2009	NUM
ejpam-590	236	9	.	.	PUNCT
ejpam-590	237	1	[	[	X
ejpam-590	237	2	6	6	NUM
ejpam-590	237	3	]	]	X
ejpam-590	237	4	c	c	PROPN
ejpam-590	237	5	fabre	fabre	PROPN
ejpam-590	237	6	,	,	PUNCT
ejpam-590	237	7	j	j	PROPN
ejpam-590	237	8	p	p	PROPN
ejpam-590	237	9	puel	puel	NOUN
ejpam-590	237	10	,	,	PUNCT
ejpam-590	237	11	and	and	CCONJ
ejpam-590	237	12	e	e	PROPN
ejpam-590	237	13	zuazua	zuazua	PROPN
ejpam-590	237	14	.	.	PUNCT
ejpam-590	237	15	approximate	approximate	ADJ
ejpam-590	237	16	controllability	controllability	NOUN
ejpam-590	237	17	of	of	ADP
ejpam-590	237	18	the	the	DET
ejpam-590	237	19	semilinear	semilinear	ADJ
ejpam-590	237	20	heat	heat	NOUN
ejpam-590	237	21	equation	equation	NOUN
ejpam-590	237	22	.	.	PUNCT
ejpam-590	238	1	proceedings	proceeding	NOUN
ejpam-590	238	2	of	of	ADP
ejpam-590	238	3	the	the	DET
ejpam-590	238	4	royal	royal	ADJ
ejpam-590	238	5	society	society	NOUN
ejpam-590	238	6	of	of	ADP
ejpam-590	238	7	edinburgh	edinburgh	PROPN
ejpam-590	238	8	,	,	PUNCT
ejpam-590	238	9	125a:31–61	125a:31–61	NOUN
ejpam-590	238	10	,	,	PUNCT
ejpam-590	238	11	1995	1995	NUM
ejpam-590	238	12	.	.	PUNCT
ejpam-590	239	1	[	[	X
ejpam-590	239	2	7	7	X
ejpam-590	239	3	]	]	X
ejpam-590	239	4	p	p	X
ejpam-590	239	5	j	j	PROPN
ejpam-590	239	6	fleming	fleming	NOUN
ejpam-590	239	7	and	and	CCONJ
ejpam-590	239	8	r	r	NOUN
ejpam-590	239	9	c	c	PROPN
ejpam-590	239	10	purshouse	purshouse	NOUN
ejpam-590	239	11	.	.	PUNCT
ejpam-590	240	1	evolutionary	evolutionary	ADJ
ejpam-590	240	2	algorithms	algorithm	NOUN
ejpam-590	240	3	in	in	ADP
ejpam-590	240	4	control	control	NOUN
ejpam-590	240	5	systems	system	NOUN
ejpam-590	240	6	engineering	engineering	NOUN
ejpam-590	240	7	:	:	PUNCT
ejpam-590	240	8	a	a	DET
ejpam-590	240	9	survey	survey	NOUN
ejpam-590	240	10	.	.	PUNCT
ejpam-590	241	1	control	control	NOUN
ejpam-590	241	2	engineering	engineering	NOUN
ejpam-590	241	3	practice	practice	NOUN
ejpam-590	241	4	,	,	PUNCT
ejpam-590	241	5	10:1233–1241	10:1233–1241	NUM
ejpam-590	241	6	,	,	PUNCT
ejpam-590	241	7	2002	2002	NUM
ejpam-590	241	8	.	.	PUNCT
ejpam-590	242	1	references	reference	NOUN
ejpam-590	242	2	128	128	NUM
ejpam-590	243	1	[	[	NOUN
ejpam-590	243	2	8	8	NUM
ejpam-590	243	3	]	]	PUNCT
ejpam-590	243	4	a	a	DET
ejpam-590	243	5	friedman	friedman	NOUN
ejpam-590	243	6	and	and	CCONJ
ejpam-590	243	7	l	l	NOUN
ejpam-590	243	8	s	s	PROPN
ejpam-590	244	1	jiang	jiang	PROPN
ejpam-590	244	2	.	.	PUNCT
ejpam-590	245	1	nonlinear	nonlinear	ADJ
ejpam-590	245	2	optimal	optimal	ADJ
ejpam-590	245	3	control	control	NOUN
ejpam-590	245	4	in	in	ADP
ejpam-590	245	5	heat	heat	NOUN
ejpam-590	245	6	conduction	conduction	NOUN
ejpam-590	245	7	.	.	PUNCT
ejpam-590	246	1	siam	siam	PROPN
ejpam-590	246	2	journal	journal	PROPN
ejpam-590	246	3	on	on	ADP
ejpam-590	246	4	control	control	NOUN
ejpam-590	246	5	and	and	CCONJ
ejpam-590	246	6	optimization	optimization	NOUN
ejpam-590	246	7	,	,	PUNCT
ejpam-590	246	8	21(6):940–951	21(6):940–951	PROPN
ejpam-590	246	9	,	,	PUNCT
ejpam-590	246	10	1983	1983	NUM
ejpam-590	246	11	.	.	PUNCT
ejpam-590	247	1	[	[	X
ejpam-590	247	2	9	9	NUM
ejpam-590	247	3	]	]	SYM
ejpam-590	247	4	r	r	NOUN
ejpam-590	247	5	glowinski	glowinski	NOUN
ejpam-590	247	6	.	.	PUNCT
ejpam-590	248	1	boundary	boundary	ADJ
ejpam-590	248	2	controllability	controllability	NOUN
ejpam-590	248	3	problems	problem	NOUN
ejpam-590	248	4	for	for	ADP
ejpam-590	248	5	wave	wave	NOUN
ejpam-590	248	6	and	and	CCONJ
ejpam-590	248	7	heat	heat	NOUN
ejpam-590	248	8	equations	equation	NOUN
ejpam-590	248	9	.	.	PUNCT
ejpam-590	249	1	in	in	ADP
ejpam-590	249	2	j	j	PROPN
ejpam-590	249	3	p	p	PROPN
ejpam-590	249	4	zelensio	zelensio	PROPN
ejpam-590	249	5	,	,	PUNCT
ejpam-590	249	6	editor	editor	NOUN
ejpam-590	249	7	,	,	PUNCT
ejpam-590	249	8	boundary	boundary	ADJ
ejpam-590	249	9	control	control	NOUN
ejpam-590	249	10	and	and	CCONJ
ejpam-590	249	11	boundary	boundary	ADJ
ejpam-590	249	12	variation	variation	NOUN
ejpam-590	249	13	,	,	PUNCT
ejpam-590	249	14	lecture	lecture	NOUN
ejpam-590	249	15	notes	note	NOUN
ejpam-590	249	16	in	in	ADP
ejpam-590	249	17	control	control	NOUN
ejpam-590	249	18	and	and	CCONJ
ejpam-590	249	19	information	information	NOUN
ejpam-590	249	20	sciences	science	NOUN
ejpam-590	249	21	.	.	PUNCT
ejpam-590	249	22	,	,	PUNCT
ejpam-590	249	23	volume	volume	NOUN
ejpam-590	249	24	178	178	NUM
ejpam-590	249	25	,	,	PUNCT
ejpam-590	249	26	pages	page	NOUN
ejpam-590	249	27	221–237	221–237	NUM
ejpam-590	249	28	.	.	PUNCT
ejpam-590	250	1	springer	springer	NOUN
ejpam-590	250	2	verlag	verlag	PROPN
ejpam-590	250	3	,	,	PUNCT
ejpam-590	250	4	berlin	berlin	PROPN
ejpam-590	250	5	,	,	PUNCT
ejpam-590	250	6	germany	germany	PROPN
ejpam-590	250	7	,	,	PUNCT
ejpam-590	250	8	1992	1992	NUM
ejpam-590	250	9	.	.	PUNCT
ejpam-590	251	1	[	[	X
ejpam-590	251	2	10	10	NUM
ejpam-590	251	3	]	]	X
ejpam-590	251	4	k	k	PROPN
ejpam-590	251	5	krishnakumar	krishnakumar	PROPN
ejpam-590	251	6	and	and	CCONJ
ejpam-590	251	7	d	d	PROPN
ejpam-590	251	8	e	e	PROPN
ejpam-590	251	9	goldberg	goldberg	PROPN
ejpam-590	251	10	.	.	PUNCT
ejpam-590	252	1	control	control	PROPN
ejpam-590	252	2	system	system	NOUN
ejpam-590	252	3	optimization	optimization	NOUN
ejpam-590	252	4	using	use	VERB
ejpam-590	252	5	genetic	genetic	ADJ
ejpam-590	252	6	algorithms	algorithm	NOUN
ejpam-590	252	7	.	.	PUNCT
ejpam-590	253	1	j	j	PROPN
ejpam-590	253	2	guidance	guidance	NOUN
ejpam-590	253	3	,	,	PUNCT
ejpam-590	253	4	control	control	NOUN
ejpam-590	253	5	and	and	CCONJ
ejpam-590	253	6	dynamics	dynamic	NOUN
ejpam-590	253	7	,	,	PUNCT
ejpam-590	253	8	15(3):735–742	15(3):735–742	NUM
ejpam-590	253	9	,	,	PUNCT
ejpam-590	253	10	1992	1992	NUM
ejpam-590	253	11	.	.	PUNCT
ejpam-590	254	1	[	[	X
ejpam-590	254	2	11	11	NUM
ejpam-590	254	3	]	]	X
ejpam-590	254	4	i	i	PROPN
ejpam-590	254	5	e	e	PROPN
ejpam-590	254	6	lagaris	lagaris	PROPN
ejpam-590	254	7	,	,	PUNCT
ejpam-590	254	8	a	a	DET
ejpam-590	254	9	c	c	NOUN
ejpam-590	254	10	likas	likas	X
ejpam-590	254	11	,	,	PUNCT
ejpam-590	254	12	and	and	CCONJ
ejpam-590	254	13	d	d	NOUN
ejpam-590	254	14	i	i	PRON
ejpam-590	254	15	fotiadis	fotiadis	VERB
ejpam-590	254	16	.	.	PUNCT
ejpam-590	255	1	artificial	artificial	ADJ
ejpam-590	255	2	neural	neural	ADJ
ejpam-590	255	3	networks	network	NOUN
ejpam-590	255	4	for	for	ADP
ejpam-590	255	5	solving	solve	VERB
ejpam-590	255	6	ordinary	ordinary	ADJ
ejpam-590	255	7	and	and	CCONJ
ejpam-590	255	8	partial	partial	ADJ
ejpam-590	255	9	differential	differential	ADJ
ejpam-590	255	10	equations	equation	NOUN
ejpam-590	255	11	.	.	PUNCT
ejpam-590	256	1	ieee	ieee	NOUN
ejpam-590	256	2	transactions	transaction	NOUN
ejpam-590	256	3	on	on	ADP
ejpam-590	256	4	neural	neural	ADJ
ejpam-590	256	5	networks	network	NOUN
ejpam-590	256	6	,	,	PUNCT
ejpam-590	256	7	9(5):987	9(5):987	NUM
ejpam-590	256	8	–	–	PUNCT
ejpam-590	256	9	1000	1000	NUM
ejpam-590	256	10	,	,	PUNCT
ejpam-590	256	11	1998	1998	NUM
ejpam-590	256	12	.	.	PUNCT
ejpam-590	257	1	[	[	X
ejpam-590	257	2	12	12	NUM
ejpam-590	257	3	]	]	PUNCT
ejpam-590	257	4	i	i	PROPN
ejpam-590	257	5	e	e	PROPN
ejpam-590	257	6	lagaris	lagaris	PROPN
ejpam-590	257	7	,	,	PUNCT
ejpam-590	257	8	a	a	DET
ejpam-590	257	9	c	c	NOUN
ejpam-590	257	10	likas	likas	X
ejpam-590	257	11	,	,	PUNCT
ejpam-590	257	12	and	and	CCONJ
ejpam-590	257	13	d	d	ADP
ejpam-590	257	14	g	g	NOUN
ejpam-590	257	15	papageorgiou	papageorgiou	NOUN
ejpam-590	257	16	.	.	PUNCT
ejpam-590	258	1	neural	neural	ADJ
ejpam-590	258	2	network	network	NOUN
ejpam-590	258	3	methods	method	NOUN
ejpam-590	258	4	for	for	ADP
ejpam-590	258	5	boundary	boundary	ADJ
ejpam-590	258	6	value	value	NOUN
ejpam-590	258	7	problems	problem	NOUN
ejpam-590	258	8	with	with	ADP
ejpam-590	258	9	irregular	irregular	ADJ
ejpam-590	258	10	boundaries	boundary	NOUN
ejpam-590	258	11	.	.	PUNCT
ejpam-590	259	1	ieee	ieee	NOUN
ejpam-590	259	2	transactions	transaction	NOUN
ejpam-590	259	3	on	on	ADP
ejpam-590	259	4	neural	neural	ADJ
ejpam-590	259	5	networks	network	NOUN
ejpam-590	259	6	,	,	PUNCT
ejpam-590	259	7	11(5):1041–1049	11(5):1041–1049	NUM
ejpam-590	259	8	,	,	PUNCT
ejpam-590	259	9	2000	2000	NUM
ejpam-590	259	10	.	.	PUNCT
ejpam-590	260	1	[	[	X
ejpam-590	260	2	13	13	NUM
ejpam-590	260	3	]	]	SYM
ejpam-590	260	4	z	z	NOUN
ejpam-590	260	5	michalewicz	michalewicz	NOUN
ejpam-590	260	6	,	,	PUNCT
ejpam-590	260	7	c	c	PROPN
ejpam-590	260	8	z	z	PROPN
ejpam-590	260	9	janikow	janikow	PROPN
ejpam-590	260	10	,	,	PUNCT
ejpam-590	260	11	and	and	CCONJ
ejpam-590	260	12	j	j	PROPN
ejpam-590	260	13	b	b	PROPN
ejpam-590	260	14	krawczyk	krawczyk	PROPN
ejpam-590	260	15	.	.	PUNCT
ejpam-590	261	1	a	a	DET
ejpam-590	261	2	modified	modify	VERB
ejpam-590	261	3	genetic	genetic	ADJ
ejpam-590	261	4	algorithm	algorithm	NOUN
ejpam-590	261	5	for	for	ADP
ejpam-590	261	6	optimal	optimal	ADJ
ejpam-590	261	7	control	control	NOUN
ejpam-590	261	8	problems	problem	NOUN
ejpam-590	261	9	.	.	PUNCT
ejpam-590	262	1	computers	computer	NOUN
ejpam-590	262	2	math	math	PROPN
ejpam-590	262	3	.	.	PUNCT
ejpam-590	263	1	applic	applic	PROPN
ejpam-590	263	2	.	.	PUNCT
ejpam-590	263	3	,	,	PUNCT
ejpam-590	263	4	23(12):83–94	23(12):83–94	NUM
ejpam-590	263	5	,	,	PUNCT
ejpam-590	263	6	1992	1992	NUM
ejpam-590	263	7	.	.	PUNCT
ejpam-590	264	1	[	[	X
ejpam-590	264	2	14	14	NUM
ejpam-590	264	3	]	]	X
ejpam-590	264	4	m	m	VERB
ejpam-590	264	5	sirbu	sirbu	PROPN
ejpam-590	264	6	.	.	PUNCT
ejpam-590	265	1	feedback	feedback	PROPN
ejpam-590	265	2	null	null	ADJ
ejpam-590	265	3	controllability	controllability	NOUN
ejpam-590	265	4	of	of	ADP
ejpam-590	265	5	the	the	DET
ejpam-590	265	6	semilinear	semilinear	ADJ
ejpam-590	265	7	heat	heat	NOUN
ejpam-590	265	8	equation	equation	NOUN
ejpam-590	265	9	.	.	PUNCT
ejpam-590	266	1	differential	differential	ADJ
ejpam-590	266	2	and	and	CCONJ
ejpam-590	266	3	integral	integral	ADJ
ejpam-590	266	4	equation	equation	NOUN
ejpam-590	266	5	,	,	PUNCT
ejpam-590	266	6	15(1):115–128	15(1):115–128	PROPN
ejpam-590	266	7	,	,	PUNCT
ejpam-590	266	8	2002	2002	NUM
ejpam-590	266	9	.	.	PUNCT
ejpam-590	267	1	[	[	X
ejpam-590	267	2	15	15	NUM
ejpam-590	267	3	]	]	SYM
ejpam-590	267	4	n	n	PRON
ejpam-590	267	5	sukavanam	sukavanam	NOUN
ejpam-590	267	6	and	and	CCONJ
ejpam-590	267	7	v	v	ADP
ejpam-590	267	8	panwar	panwar	ADJ
ejpam-590	267	9	.	.	PUNCT
ejpam-590	268	1	computation	computation	NOUN
ejpam-590	268	2	of	of	ADP
ejpam-590	268	3	boundary	boundary	ADJ
ejpam-590	268	4	control	control	NOUN
ejpam-590	268	5	of	of	ADP
ejpam-590	268	6	controlled	control	VERB
ejpam-590	268	7	heat	heat	NOUN
ejpam-590	268	8	equation	equation	NOUN
ejpam-590	268	9	using	use	VERB
ejpam-590	268	10	artificial	artificial	ADJ
ejpam-590	268	11	neural	neural	ADJ
ejpam-590	268	12	networks	network	NOUN
ejpam-590	268	13	.	.	PUNCT
ejpam-590	269	1	int	int	NOUN
ejpam-590	269	2	.	.	PUNCT
ejpam-590	270	1	comm	comm	NOUN
ejpam-590	270	2	.	.	PUNCT
ejpam-590	271	1	heat	heat	NOUN
ejpam-590	271	2	mass	mass	NOUN
ejpam-590	271	3	transfer	transfer	NOUN
ejpam-590	271	4	,	,	PUNCT
ejpam-590	271	5	30(8):1137–1146	30(8):1137–1146	NUM
ejpam-590	271	6	,	,	PUNCT
ejpam-590	271	7	2003	2003	NUM
ejpam-590	271	8	.	.	PUNCT
ejpam-590	272	1	[	[	X
ejpam-590	272	2	16	16	NUM
ejpam-590	272	3	]	]	PUNCT
ejpam-590	272	4	n	n	CCONJ
ejpam-590	272	5	sukavanam	sukavanam	NOUN
ejpam-590	272	6	and	and	CCONJ
ejpam-590	272	7	n	n	CCONJ
ejpam-590	272	8	k	k	PROPN
ejpam-590	272	9	tomar	tomar	PROPN
ejpam-590	272	10	.	.	PUNCT
ejpam-590	273	1	approximate	approximate	ADJ
ejpam-590	273	2	controllability	controllability	NOUN
ejpam-590	273	3	of	of	ADP
ejpam-590	273	4	semilinear	semilinear	PROPN
ejpam-590	273	5	delay	delay	PROPN
ejpam-590	273	6	control	control	PROPN
ejpam-590	273	7	systems	system	NOUN
ejpam-590	273	8	.	.	PUNCT
ejpam-590	274	1	nonlinear	nonlinear	ADJ
ejpam-590	274	2	functional	functional	ADJ
ejpam-590	274	3	analysis	analysis	NOUN
ejpam-590	274	4	and	and	CCONJ
ejpam-590	274	5	applications	application	NOUN
ejpam-590	274	6	,	,	PUNCT
ejpam-590	274	7	12(1):53–59	12(1):53–59	NUM
ejpam-590	274	8	,	,	PUNCT
ejpam-590	274	9	2007	2007	NUM
ejpam-590	274	10	.	.	PUNCT
ejpam-590	275	1	[	[	X
ejpam-590	275	2	17	17	NUM
ejpam-590	275	3	]	]	X
ejpam-590	275	4	l	l	NOUN
ejpam-590	275	5	d	d	X
ejpam-590	275	6	teresa	teresa	PROPN
ejpam-590	275	7	.	.	PROPN
ejpam-590	275	8	approximate	approximate	ADJ
ejpam-590	275	9	controllability	controllability	NOUN
ejpam-590	275	10	of	of	ADP
ejpam-590	275	11	a	a	DET
ejpam-590	275	12	semilinear	semilinear	ADJ
ejpam-590	275	13	heat	heat	NOUN
ejpam-590	275	14	equation	equation	NOUN
ejpam-590	275	15	.	.	PUNCT
ejpam-590	276	1	siam	siam	PROPN
ejpam-590	276	2	journal	journal	PROPN
ejpam-590	276	3	on	on	ADP
ejpam-590	276	4	control	control	NOUN
ejpam-590	276	5	and	and	CCONJ
ejpam-590	276	6	optimization	optimization	NOUN
ejpam-590	276	7	,	,	PUNCT
ejpam-590	276	8	36(6):2128–2147	36(6):2128–2147	NUM
ejpam-590	276	9	,	,	PUNCT
ejpam-590	276	10	1998	1998	NUM
ejpam-590	276	11	.	.	PUNCT
ejpam-590	277	1	[	[	X
ejpam-590	277	2	18	18	NUM
ejpam-590	277	3	]	]	X
ejpam-590	277	4	y	y	PROPN
ejpam-590	277	5	yamashita	yamashita	PROPN
ejpam-590	277	6	and	and	CCONJ
ejpam-590	277	7	m	m	PROPN
ejpam-590	277	8	shima	shima	PROPN
ejpam-590	277	9	.	.	PROPN
ejpam-590	278	1	numerical	numerical	PROPN
ejpam-590	278	2	computational	computational	ADJ
ejpam-590	278	3	method	method	NOUN
ejpam-590	278	4	using	use	VERB
ejpam-590	278	5	genetic	genetic	ADJ
ejpam-590	278	6	algorithm	algorithm	NOUN
ejpam-590	278	7	for	for	ADP
ejpam-590	278	8	the	the	DET
ejpam-590	278	9	optimal	optimal	ADJ
ejpam-590	278	10	control	control	NOUN
ejpam-590	278	11	problem	problem	NOUN
ejpam-590	278	12	with	with	ADP
ejpam-590	278	13	terminal	terminal	ADJ
ejpam-590	278	14	constraints	constraint	NOUN
ejpam-590	278	15	and	and	CCONJ
ejpam-590	278	16	free	free	ADJ
ejpam-590	278	17	parameters	parameter	NOUN
ejpam-590	278	18	.	.	PUNCT
ejpam-590	279	1	nonlinear	nonlinear	ADJ
ejpam-590	279	2	analysis	analysis	NOUN
ejpam-590	279	3	,	,	PUNCT
ejpam-590	279	4	theory	theory	NOUN
ejpam-590	279	5	,	,	PUNCT
ejpam-590	279	6	method	method	NOUN
ejpam-590	279	7	and	and	CCONJ
ejpam-590	279	8	applications	application	NOUN
ejpam-590	279	9	,	,	PUNCT
ejpam-590	279	10	30(4):2285–2290	30(4):2285–2290	NUM
ejpam-590	279	11	,	,	PUNCT
ejpam-590	279	12	1997	1997	NUM
ejpam-590	279	13	.	.	PUNCT
ejpam-590	280	1	[	[	X
ejpam-590	280	2	19	19	NUM
ejpam-590	280	3	]	]	X
ejpam-590	280	4	h	h	NOUN
ejpam-590	280	5	x	x	PUNCT
ejpam-590	280	6	zhou	zhou	PROPN
ejpam-590	280	7	.	.	PUNCT
ejpam-590	281	1	a	a	DET
ejpam-590	281	2	note	note	NOUN
ejpam-590	281	3	on	on	ADP
ejpam-590	281	4	approximate	approximate	ADJ
ejpam-590	281	5	controllability	controllability	NOUN
ejpam-590	281	6	for	for	ADP
ejpam-590	281	7	semilinear	semilinear	NOUN
ejpam-590	281	8	one	one	NUM
ejpam-590	281	9	-	-	PUNCT
ejpam-590	281	10	dimensional	dimensional	ADJ
ejpam-590	281	11	heat	heat	NOUN
ejpam-590	281	12	equation	equation	NOUN
ejpam-590	281	13	.	.	PUNCT
ejpam-590	282	1	appl	appl	PROPN
ejpam-590	282	2	.	.	PROPN
ejpam-590	282	3	math	math	PROPN
ejpam-590	282	4	.	.	PUNCT
ejpam-590	283	1	optim	optim	PROPN
ejpam-590	283	2	.	.	PROPN
ejpam-590	283	3	,	,	PUNCT
ejpam-590	283	4	8:275–285	8:275–285	NUM
ejpam-590	283	5	,	,	PUNCT
ejpam-590	283	6	1982	1982	NUM
ejpam-590	283	7	.	.	PUNCT