id	sid	tid	token	lemma	pos
hjic-1083	1	1	hungarian	hungarian	ADJ
hjic-1083	1	2	journal	journal	NOUN
hjic-1083	1	3	of	of	ADP
hjic-1083	1	4	industrial	industrial	ADJ
hjic-1083	1	5	chemistry	chemistry	NOUN
hjic-1083	1	6	veszprem	veszprem	PROPN
hjic-1083	1	7	vol	vol	NOUN
hjic-1083	1	8	.	.	PROPN
hjic-1083	2	1	29	29	NUM
hjic-1083	2	2	.	.	PUNCT
hjic-1083	3	1	pp	pp	ADJ
hjic-1083	3	2	.	.	PUNCT
hjic-1083	4	1	129134	129134	NUM
hjic-1083	4	2	(	(	PUNCT
hjic-1083	4	3	2001	2001	NUM
hjic-1083	4	4	)	)	PUNCT
hjic-1083	4	5	identification	identification	NOUN
hjic-1083	4	6	of	of	ADP
hjic-1083	4	7	nonlinear	nonlinear	ADJ
hjic-1083	4	8	systems	system	NOUN
hjic-1083	4	9	using	use	VERB
hjic-1083	4	10	gaussian	gaussian	ADJ
hjic-1083	4	11	mixture	mixture	NOUN
hjic-1083	4	12	of	of	ADP
hjic-1083	4	13	local	local	ADJ
hjic-1083	4	14	models	model	NOUN
hjic-1083	4	15	j.	j.	PROPN
hjic-1083	4	16	abonyi	abonyi	PROPN
hjic-1083	4	17	,	,	PUNCT
hjic-1083	4	18	t.	t.	NOUN
hjic-1083	4	19	chovan	chovan	PROPN
hjic-1083	4	20	and	and	CCONJ
hjic-1083	4	21	f.	f.	PROPN
hjic-1083	4	22	szeifbrt	szeifbrt	PROPN
hjic-1083	4	23	(	(	PUNCT
hjic-1083	4	24	department	department	NOUN
hjic-1083	4	25	of	of	ADP
hjic-1083	4	26	process	process	NOUN
hjic-1083	4	27	engineering	engineering	NOUN
hjic-1083	4	28	,	,	PUNCT
hjic-1083	4	29	university	university	NOUN
hjic-1083	4	30	ofveszprem	ofveszprem	ADJ
hjic-1083	4	31	,	,	PUNCT
hjic-1083	4	32	p.o	p.o	PROPN
hjic-1083	4	33	.	.	PROPN
hjic-1083	4	34	box	box	PROPN
hjic-1083	4	35	158	158	NUM
hjic-1083	4	36	,	,	PUNCT
hjic-1083	4	37	h-8201	h-8201	PROPN
hjic-1083	4	38	,	,	PUNCT
hjic-1083	4	39	hungary	hungary	PROPN
hjic-1083	4	40	)	)	PUNCT
hjic-1083	4	41	received	receive	VERB
hjic-1083	4	42	:	:	PUNCT
hjic-1083	4	43	october	october	PROPN
hjic-1083	4	44	8	8	NUM
hjic-1083	4	45	,	,	PUNCT
hjic-1083	4	46	2001	2001	NUM
hjic-1083	4	47	identification	identification	NOUN
hjic-1083	4	48	of	of	ADP
hjic-1083	4	49	operating	operate	VERB
hjic-1083	4	50	regime	regime	NOUN
hjic-1083	4	51	based	base	VERB
hjic-1083	4	52	models	model	NOUN
hjic-1083	4	53	of	of	ADP
hjic-1083	4	54	nonlinear	nonlinear	ADJ
hjic-1083	4	55	dynamic	dynamic	ADJ
hjic-1083	4	56	systems	system	NOUN
hjic-1083	4	57	is	be	AUX
hjic-1083	4	58	addressed	address	VERB
hjic-1083	4	59	.	.	PUNCT
hjic-1083	5	1	the	the	DET
hjic-1083	5	2	operating	operate	VERB
hjic-1083	5	3	regimes	regime	NOUN
hjic-1083	5	4	and	and	CCONJ
hjic-1083	5	5	the	the	DET
hjic-1083	5	6	parameters	parameter	NOUN
hjic-1083	5	7	of	of	ADP
hjic-1083	5	8	the	the	DET
hjic-1083	5	9	local	local	ADJ
hjic-1083	5	10	linear	linear	NOUN
hjic-1083	5	11	models	model	NOUN
hjic-1083	5	12	are	be	AUX
hjic-1083	5	13	identified	identify	VERB
hjic-1083	5	14	directly	directly	ADV
hjic-1083	5	15	and	and	CCONJ
hjic-1083	5	16	simultaneously	simultaneously	ADV
hjic-1083	5	17	based	base	VERB
hjic-1083	5	18	on	on	ADP
hjic-1083	5	19	the	the	DET
hjic-1083	5	20	expectation	expectation	NOUN
hjic-1083	5	21	maximization	maximization	NOUN
hjic-1083	5	22	(	(	PUNCT
hjic-1083	5	23	em	em	NOUN
hjic-1083	5	24	)	)	PUNCT
hjic-1083	5	25	identification	identification	NOUN
hjic-1083	5	26	of	of	ADP
hjic-1083	5	27	gaussian	gaussian	ADJ
hjic-1083	5	28	mixture	mixture	NOUN
hjic-1083	5	29	model	model	NOUN
hjic-1083	5	30	(	(	PUNCT
hjic-1083	5	31	gmm	gmm	PROPN
hjic-1083	5	32	)	)	PUNCT
hjic-1083	5	33	.	.	PUNCT
hjic-1083	6	1	the	the	DET
hjic-1083	6	2	proposed	propose	VERB
hjic-1083	6	3	technique	technique	NOUN
hjic-1083	6	4	is	be	AUX
hjic-1083	6	5	demonstrated	demonstrate	VERB
hjic-1083	6	6	by	by	ADP
hjic-1083	6	7	means	mean	NOUN
hjic-1083	6	8	of	of	ADP
hjic-1083	6	9	the	the	DET
hjic-1083	6	10	identification	identification	NOUN
hjic-1083	6	11	of	of	ADP
hjic-1083	6	12	a	a	DET
hjic-1083	6	13	neutralization	neutralization	NOUN
hjic-1083	6	14	reaction	reaction	NOUN
hjic-1083	6	15	in	in	ADP
hjic-1083	6	16	a	a	DET
hjic-1083	6	17	continuously	continuously	ADV
hjic-1083	6	18	stirred	stir	VERB
hjic-1083	6	19	tank	tank	NOUN
hjic-1083	6	20	reactor	reactor	NOUN
hjic-1083	6	21	.	.	PUNCT
hjic-1083	7	1	keywords	keyword	NOUN
hjic-1083	7	2	:	:	PUNCT
hjic-1083	7	3	operating	operate	VERB
hjic-1083	7	4	regime	regime	NOUN
hjic-1083	7	5	based	base	VERB
hjic-1083	7	6	model	model	NOUN
hjic-1083	7	7	,	,	PUNCT
hjic-1083	7	8	expectation	expectation	NOUN
hjic-1083	7	9	maximization	maximization	NOUN
hjic-1083	7	10	,	,	PUNCT
hjic-1083	7	11	takagi	takagi	NOUN
hjic-1083	7	12	-	-	PUNCT
hjic-1083	7	13	sugeno	sugeno	NOUN
hjic-1083	7	14	fuzzy	fuzzy	ADJ
hjic-1083	7	15	model	model	NOUN
hjic-1083	7	16	,	,	PUNCT
hjic-1083	7	17	nonlinear	nonlinear	ADJ
hjic-1083	7	18	system	system	NOUN
hjic-1083	7	19	,	,	PUNCT
hjic-1083	7	20	neutralization	neutralization	NOUN
hjic-1083	7	21	reaction	reaction	NOUN
hjic-1083	7	22	introduction	introduction	NOUN
hjic-1083	7	23	the	the	DET
hjic-1083	7	24	problem	problem	NOUN
hjic-1083	7	25	of	of	ADP
hjic-1083	7	26	a	a	DET
hjic-1083	7	27	successful	successful	ADJ
hjic-1083	7	28	model	model	NOUN
hjic-1083	7	29	based	base	VERB
hjic-1083	7	30	control	control	NOUN
hjic-1083	7	31	application	application	NOUN
hjic-1083	7	32	arises	arise	VERB
hjic-1083	7	33	from	from	ADP
hjic-1083	7	34	difficulties	difficulty	NOUN
hjic-1083	7	35	in	in	ADP
hjic-1083	7	36	system	system	NOUN
hjic-1083	7	37	modeling	modeling	NOUN
hjic-1083	7	38	[	[	X
hjic-1083	7	39	1	1	NUM
hjic-1083	7	40	,	,	PUNCT
hjic-1083	7	41	2	2	NUM
hjic-1083	7	42	]	]	PUNCT
hjic-1083	7	43	.	.	PUNCT
hjic-1083	8	1	this	this	DET
hjic-1083	8	2	difficulty	difficulty	NOUN
hjic-1083	8	3	stems	stem	VERB
hjic-1083	8	4	from	from	ADP
hjic-1083	8	5	lack	lack	NOUN
hjic-1083	8	6	of	of	ADP
hjic-1083	8	7	knowledge	knowledge	NOUN
hjic-1083	8	8	or	or	CCONJ
hjic-1083	8	9	understanding	understanding	NOUN
hjic-1083	8	10	of	of	ADP
hjic-1083	8	11	the	the	DET
hjic-1083	8	12	process	process	NOUN
hjic-1083	8	13	to	to	PART
hjic-1083	8	14	be	be	AUX
hjic-1083	8	15	controlled	control	VERB
hjic-1083	8	16	[	[	PUNCT
hjic-1083	8	17	3	3	NUM
hjic-1083	8	18	]	]	PUNCT
hjic-1083	8	19	.	.	PUNCT
hjic-1083	9	1	while	while	SCONJ
hjic-1083	9	2	it	it	PRON
hjic-1083	9	3	may	may	AUX
hjic-1083	9	4	not	not	PART
hjic-1083	9	5	be	be	AUX
hjic-1083	9	6	possible	possible	ADJ
hjic-1083	9	7	to	to	PART
hjic-1083	9	8	find	find	VERB
hjic-1083	9	9	process	process	NOUN
hjic-1083	9	10	information	information	NOUN
hjic-1083	9	11	that	that	PRON
hjic-1083	9	12	is	be	AUX
hjic-1083	9	13	universally	universally	ADV
hjic-1083	9	14	applicable	applicable	ADJ
hjic-1083	9	15	,	,	PUNCT
hjic-1083	9	16	.it	.it	PUNCT
hjic-1083	9	17	would	would	AUX
hjic-1083	9	18	certainly	certainly	ADV
hjic-1083	9	19	be	be	AUX
hjic-1083	9	20	worthwhile	worthwhile	ADJ
hjic-1083	9	21	to	to	PART
hjic-1083	9	22	examine	examine	VERB
hjic-1083	9	23	what	what	PRON
hjic-1083	9	24	types	type	NOUN
hjic-1083	9	25	of	of	ADP
hjic-1083	9	26	process	process	NOUN
hjic-1083	9	27	-	-	PUNCT
hjic-1083	9	28	knowledge	knowledge	NOUN
hjic-1083	9	29	would	would	AUX
hjic-1083	9	30	be	be	AUX
hjic-1083	9	31	most	most	ADV
hjic-1083	9	32	relevant	relevant	ADJ
hjic-1083	9	33	for	for	ADP
hjic-1083	9	34	specific	specific	ADJ
hjic-1083	9	35	operating	operating	NOUN
hjic-1083	9	36	points	point	NOUN
hjic-1083	9	37	of	of	ADP
hjic-1083	9	38	the	the	DET
hjic-1083	9	39	process	process	NOUN
hjic-1083	9	40	.	.	PUNCT
hjic-1083	10	1	this	this	DET
hjic-1083	10	2	type	type	NOUN
hjic-1083	10	3	of	of	ADP
hjic-1083	10	4	local	local	ADJ
hjic-1083	10	5	understanding	understanding	NOUN
hjic-1083	10	6	,	,	PUNCT
hjic-1083	10	7	in	in	ADP
hjic-1083	10	8	fact	fact	NOUN
hjic-1083	10	9	,	,	PUNCT
hjic-1083	10	10	will	will	AUX
hjic-1083	10	11	be	be	AUX
hjic-1083	10	12	a	a	DET
hjic-1083	10	13	key	key	NOUN
hjic-1083	10	14	to	to	ADP
hjic-1083	10	15	identifying	identify	VERB
hjic-1083	10	16	reliable	reliable	ADJ
hjic-1083	10	17	local	local	ADJ
hjic-1083	10	18	models	model	NOUN
hjic-1083	10	19	with	with	ADP
hjic-1083	10	20	a	a	DET
hjic-1083	10	21	limited	limited	ADJ
hjic-1083	10	22	amount	amount	NOUN
hjic-1083	10	23	of	of	ADP
hjic-1083	10	24	data	datum	NOUN
hjic-1083	10	25	.	.	PUNCT
hjic-1083	11	1	the	the	DET
hjic-1083	11	2	model	model	NOUN
hjic-1083	11	3	that	that	PRON
hjic-1083	11	4	has	have	VERB
hjic-1083	11	5	a	a	DET
hjic-1083	11	6	range	range	NOUN
hjic-1083	11	7	of	of	ADP
hjic-1083	11	8	validity	validity	NOUN
hjic-1083	11	9	less	less	ADJ
hjic-1083	11	10	than	than	ADP
hjic-1083	11	11	the	the	DET
hjic-1083	11	12	operating	operate	VERB
hjic-1083	11	13	regime	regime	NOUN
hjic-1083	11	14	of	of	ADP
hjic-1083	11	15	the	the	DET
hjic-1083	11	16	process	process	NOUN
hjic-1083	11	17	is	be	AUX
hjic-1083	11	18	called	call	VERB
hjic-1083	11	19	local	local	ADJ
hjic-1083	11	20	model	model	NOUN
hjic-1083	11	21	,	,	PUNCT
hjic-1083	11	22	as	as	SCONJ
hjic-1083	11	23	opposed	oppose	VERB
hjic-1083	11	24	to	to	ADP
hjic-1083	11	25	a	a	DET
hjic-1083	11	26	global	global	ADJ
hjic-1083	11	27	model	model	NOUN
hjic-1083	11	28	that	that	PRON
hjic-1083	11	29	is	be	AUX
hjic-1083	11	30	valid	valid	ADJ
hjic-1083	11	31	in	in	ADP
hjic-1083	11	32	the	the	DET
hjic-1083	11	33	full	full	ADJ
hjic-1083	11	34	range	range	NOUN
hjic-1083	11	35	of	of	ADP
hjic-1083	11	36	operation	operation	NOUN
hjic-1083	11	37	.	.	PUNCT
hjic-1083	12	1	global	global	ADJ
hjic-1083	12	2	modeling	modeling	NOUN
hjic-1083	12	3	is	be	AUX
hjic-1083	12	4	a	a	DET
hjic-1083	12	5	complicated	complicated	ADJ
hjic-1083	12	6	task	task	NOUN
hjic-1083	12	7	because	because	SCONJ
hjic-1083	12	8	of	of	ADP
hjic-1083	12	9	the	the	DET
hjic-1083	12	10	need	need	NOUN
hjic-1083	12	11	to	to	PART
hjic-1083	12	12	describe	describe	VERB
hjic-1083	12	13	the	the	DET
hjic-1083	12	14	interactions	interaction	NOUN
hjic-1083	12	15	between	between	ADP
hjic-1083	12	16	a	a	DET
hjic-1083	12	17	large	large	ADJ
hjic-1083	12	18	number	number	NOUN
hjic-1083	12	19	of	of	ADP
hjic-1083	12	20	phenomena	phenomenon	NOUN
hjic-1083	12	21	that	that	PRON
hjic-1083	12	22	appear	appear	VERB
hjic-1083	12	23	globally	globally	ADV
hjic-1083	12	24	.	.	PUNCT
hjic-1083	13	1	local	local	ADJ
hjic-1083	13	2	modeling	modeling	NOUN
hjic-1083	13	3	,	,	PUNCT
hjic-1083	13	4	on	on	ADP
hjic-1083	13	5	the	the	DET
hjic-1083	13	6	other	other	ADJ
hjic-1083	13	7	hand	hand	NOUN
hjic-1083	13	8	,	,	PUNCT
hjic-1083	13	9	may	may	AUX
hjic-1083	13	10	be	be	AUX
hjic-1083	13	11	considerably	considerably	ADV
hjic-1083	13	12	simpler	simple	ADJ
hjic-1083	13	13	,	,	PUNCT
hjic-1083	13	14	because	because	SCONJ
hjic-1083	13	15	locally	locally	ADV
hjic-1083	13	16	there	there	PRON
hjic-1083	13	17	may	may	AUX
hjic-1083	13	18	be	be	AUX
hjic-1083	13	19	a	a	DET
hjic-1083	13	20	smaller	small	ADJ
hjic-1083	13	21	number	number	NOUN
hjic-1083	13	22	of	of	ADP
hjic-1083	13	23	phenomena	phenomenon	NOUN
hjic-1083	13	24	that	that	PRON
hjic-1083	13	25	are	be	AUX
hjic-1083	13	26	relevant	relevant	ADJ
hjic-1083	13	27	,	,	PUNCT
hjic-1083	13	28	and	and	CCONJ
hjic-1083	13	29	their	their	PRON
hjic-1083	13	30	interactions	interaction	NOUN
hjic-1083	13	31	are	be	AUX
hjic-1083	13	32	simpler	simple	ADJ
hjic-1083	13	33	[	[	PUNCT
hjic-1083	13	34	4	4	NUM
hjic-1083	13	35	]	]	PUNCT
hjic-1083	13	36	.	.	PUNCT
hjic-1083	14	1	the	the	DET
hjic-1083	14	2	modeling	modeling	NOUN
hjic-1083	14	3	framework	framework	NOUN
hjic-1083	14	4	that	that	PRON
hjic-1083	14	5	is	be	AUX
hjic-1083	14	6	based	base	VERB
hjic-1083	14	7	on	on	ADP
hjic-1083	14	8	combining	combine	VERB
hjic-1083	14	9	a	a	DET
hjic-1083	14	10	number	number	NOUN
hjic-1083	14	11	of	of	ADP
hjic-1083	14	12	local	local	ADJ
hjic-1083	14	13	models	model	NOUN
hjic-1083	14	14	.	.	PUNCT
hjic-1083	15	1	where	where	SCONJ
hjic-1083	15	2	each	each	DET
hjic-1083	15	3	local	local	ADJ
hjic-1083	15	4	model	model	NOUN
hjic-1083	15	5	has	have	VERB
hjic-1083	15	6	a	a	DET
hjic-1083	15	7	predefined	predefine	VERB
hjic-1083	15	8	operating	operating	NOUN
hjic-1083	15	9	region	region	NOUN
hjic-1083	15	10	in	in	ADP
hjic-1083	15	11	which	which	PRON
hjic-1083	15	12	the	the	DET
hjic-1083	15	13	local	local	ADJ
hjic-1083	15	14	model	model	NOUN
hjic-1083	15	15	is	be	AUX
hjic-1083	15	16	valid	valid	ADJ
hjic-1083	15	17	is	be	AUX
hjic-1083	15	18	called	call	VERB
hjic-1083	15	19	operating	operating	NOUN
hjic-1083	15	20	regime	regime	NOUN
hjic-1083	15	21	based	base	VERB
hjic-1083	15	22	model	model	NOUN
hjic-1083	15	23	[	[	X
hjic-1083	15	24	5	5	NUM
hjic-1083	15	25	]	]	PUNCT
hjic-1083	15	26	,	,	PUNCT
hjic-1083	15	27	where	where	SCONJ
hjic-1083	15	28	the	the	DET
hjic-1083	15	29	local	local	ADJ
hjic-1083	15	30	models	model	NOUN
hjic-1083	15	31	are	be	AUX
hjic-1083	15	32	combined	combine	VERB
hjic-1083	15	33	into	into	ADP
hjic-1083	15	34	a	a	DET
hjic-1083	15	35	global	global	ADJ
hjic-1083	15	36	model	model	NOUN
hjic-1083	15	37	using	use	VERB
hjic-1083	15	38	an	an	DET
hjic-1083	15	39	interpolation	interpolation	NOUN
hjic-1083	15	40	technique	technique	NOUN
hjic-1083	15	41	as	as	SCONJ
hjic-1083	15	42	it	it	PRON
hjic-1083	15	43	is	be	AUX
hjic-1083	15	44	illustrated	illustrate	VERB
hjic-1083	15	45	in	in	ADP
hjic-1083	15	46	fig	fig	NOUN
hjic-1083	15	47	.	.	PUNCT
hjic-1083	16	1	i.	i.	PROPN
hjic-1083	16	2	the	the	DET
hjic-1083	16	3	main	main	ADJ
hjic-1083	16	4	advantage	advantage	NOUN
hjic-1083	16	5	of	of	ADP
hjic-1083	16	6	this	this	DET
hjic-1083	16	7	framework	framework	NOUN
hjic-1083	16	8	is	be	AUX
hjic-1083	16	9	its	its	PRON
hjic-1083	16	10	transparency	transparency	NOUN
hjic-1083	16	11	.	.	PUNCT
hjic-1083	17	1	both	both	CCONJ
hjic-1083	17	2	the	the	DET
hjic-1083	17	3	concept	concept	NOUN
hjic-1083	17	4	of	of	ADP
hjic-1083	17	5	operating	operate	VERB
hjic-1083	17	6	regimes	regime	NOUN
hjic-1083	17	7	and	and	CCONJ
hjic-1083	17	8	the	the	DET
hjic-1083	17	9	model	model	NOUN
hjic-1083	17	10	structure	structure	NOUN
hjic-1083	17	11	are	be	AUX
hjic-1083	17	12	easy	easy	ADJ
hjic-1083	17	13	to	to	PART
hjic-1083	17	14	understand	understand	VERB
hjic-1083	17	15	.	.	PUNCT
hjic-1083	18	1	this	this	PRON
hjic-1083	18	2	is	be	AUX
hjic-1083	18	3	important	important	ADJ
hjic-1083	18	4	,	,	PUNCT
hjic-1083	18	5	since	since	SCONJ
hjic-1083	18	6	the	the	DET
hjic-1083	18	7	model	model	NOUN
hjic-1083	18	8	structure	structure	NOUN
hjic-1083	18	9	can	can	AUX
hjic-1083	18	10	be	be	AUX
hjic-1083	18	11	interpreted	interpret	VERB
hjic-1083	18	12	in	in	ADP
hjic-1083	18	13	terms	term	NOUN
hjic-1083	18	14	of	of	ADP
hjic-1083	18	15	operating	operate	VERB
hjic-1083	18	16	regimes	regime	NOUN
hjic-1083	18	17	,	,	PUNCT
hjic-1083	18	18	but	but	CCONJ
hjic-1083	18	19	also	also	ADV
hjic-1083	18	20	quantitatively	quantitatively	ADV
hjic-1083	18	21	in	in	ADP
hjic-1083	18	22	terms	term	NOUN
hjic-1083	18	23	of	of	ADP
hjic-1083	18	24	individual	individual	ADJ
hjic-1083	18	25	local	local	ADJ
hjic-1083	18	26	models	model	NOUN
hjic-1083	18	27	.	.	PUNCT
hjic-1083	19	1	the	the	DET
hjic-1083	19	2	operating	operate	VERB
hjic-1083	19	3	regime	regime	NOUN
hjic-1083	19	4	of	of	ADP
hjic-1083	19	5	the	the	DET
hjic-1083	19	6	local	local	ADJ
hjic-1083	19	7	models	model	NOUN
hjic-1083	19	8	can	can	AUX
hjic-1083	19	9	be	be	AUX
hjic-1083	19	10	also	also	ADV
hjic-1083	19	11	represented	represent	VERB
hjic-1083	19	12	by	by	ADP
hjic-1083	19	13	fuzzy	fuzzy	ADJ
hjic-1083	19	14	sets	set	NOUN
hjic-1083	19	15	[	[	X
hjic-1083	19	16	6	6	NUM
hjic-1083	19	17	]	]	PUNCT
hjic-1083	19	18	.	.	PUNCT
hjic-1083	20	1	this	this	DET
hjic-1083	20	2	representation	representation	NOUN
hjic-1083	20	3	is	be	AUX
hjic-1083	20	4	appealing	appealing	ADJ
hjic-1083	20	5	,	,	PUNCT
hjic-1083	20	6	since	since	SCONJ
hjic-1083	20	7	many	many	ADJ
hjic-1083	20	8	systems	system	NOUN
hjic-1083	20	9	change	change	NOUN
hjic-1083	20	10	behaviors	behavior	NOUN
hjic-1083	20	11	smoothly	smoothly	ADV
hjic-1083	20	12	as	as	ADP
hjic-1083	20	13	a	a	DET
hjic-1083	20	14	function	function	NOUN
hjic-1083	20	15	of	of	ADP
hjic-1083	20	16	the	the	DET
hjic-1083	20	17	operating	operating	NOUN
hjic-1083	20	18	point	point	NOUN
hjic-1083	20	19	,	,	PUNCT
hjic-1083	20	20	and	and	CCONJ
hjic-1083	20	21	the	the	DET
hjic-1083	20	22	soft	soft	ADJ
hjic-1083	20	23	transition	transition	NOUN
hjic-1083	20	24	between	between	ADP
hjic-1083	20	25	the	the	DET
hjic-1083	20	26	regimes	regime	NOUN
hjic-1083	20	27	introduced	introduce	VERB
hjic-1083	20	28	by	by	ADP
hjic-1083	20	29	the	the	DET
hjic-1083	20	30	fuzzy	fuzzy	ADJ
hjic-1083	20	31	set	set	VERB
hjic-1083	20	32	representation	representation	NOUN
hjic-1083	20	33	captures	capture	VERB
hjic-1083	20	34	this	this	DET
hjic-1083	20	35	feature	feature	NOUN
hjic-1083	20	36	in	in	ADP
hjic-1083	20	37	an	an	DET
hjic-1083	20	38	elegant	elegant	ADJ
hjic-1083	20	39	fashion	fashion	NOUN
hjic-1083	20	40	.	.	PUNCT
hjic-1083	21	1	fuzzy	fuzzy	ADJ
hjic-1083	21	2	modeling	modeling	NOUN
hjic-1083	21	3	and	and	CCONJ
hjic-1083	21	4	identification	identification	NOUN
hjic-1083	21	5	proved	prove	VERB
hjic-1083	21	6	to	to	PART
hjic-1083	21	7	be	be	AUX
hjic-1083	21	8	effective	effective	ADJ
hjic-1083	21	9	tools	tool	NOUN
hjic-1083	21	10	for	for	ADP
hjic-1083	21	11	the	the	DET
hjic-1083	21	12	approximation	approximation	NOUN
hjic-1083	21	13	of	of	ADP
hjic-1083	21	14	uncertain	uncertain	ADJ
hjic-1083	21	15	nonlinear	nonlinear	ADJ
hjic-1083	21	16	systems	system	NOUN
hjic-1083	21	17	because	because	SCONJ
hjic-1083	21	18	of	of	ADP
hjic-1083	21	19	the	the	DET
hjic-1083	21	20	ability	ability	NOUN
hjic-1083	21	21	to	to	PART
hjic-1083	21	22	combine	combine	VERB
hjic-1083	21	23	expert	expert	ADJ
hjic-1083	21	24	knowledge	knowledge	NOUN
hjic-1083	21	25	and	and	CCONJ
hjic-1083	21	26	measured	measured	ADJ
hjic-1083	21	27	data	datum	NOUN
hjic-1083	21	28	.	.	PUNCT
hjic-1083	22	1	fuzzy	fuzzy	ADJ
hjic-1083	22	2	models	model	NOUN
hjic-1083	22	3	use	use	VERB
hjic-1083	22	4	if	if	SCONJ
hjic-1083	22	5	-	-	PUNCT
hjic-1083	22	6	then	then	ADV
hjic-1083	22	7	rules	rule	VERB
hjic-1083	22	8	to	to	PART
hjic-1083	22	9	describe	describe	VERB
hjic-1083	22	10	the	the	DET
hjic-1083	22	11	process	process	NOUN
hjic-1083	22	12	through	through	ADP
hjic-1083	22	13	a	a	DET
hjic-1083	22	14	collection	collection	NOUN
hjic-1083	22	15	of	of	ADP
hjic-1083	22	16	locally	locally	ADV
hjic-1083	22	17	valid	valid	ADJ
hjic-1083	22	18	relationships	relationship	NOUN
hjic-1083	22	19	.	.	PUNCT
hjic-1083	23	1	the	the	DET
hjic-1083	23	2	antecedents	antecedent	NOUN
hjic-1083	23	3	(	(	PUNCT
hjic-1083	23	4	if	if	SCONJ
hjic-1083	23	5	-	-	PUNCT
hjic-1083	23	6	parts	part	NOUN
hjic-1083	23	7	)	)	PUNCT
hjic-1083	23	8	of	of	ADP
hjic-1083	23	9	the	the	DET
hjic-1083	23	10	rules	rule	NOUN
hjic-1083	23	11	divide	divide	VERB
hjic-1083	23	12	the	the	DET
hjic-1083	23	13	input	input	NOUN
hjic-1083	23	14	space	space	NOUN
hjic-1083	23	15	into	into	ADP
hjic-1083	23	16	several	several	ADJ
hjic-1083	23	17	fuzzy	fuzzy	ADJ
hjic-1083	23	18	subspaces	subspace	NOUN
hjic-1083	23	19	,	,	PUNCT
hjic-1083	23	20	while	while	SCONJ
hjic-1083	23	21	the	the	DET
hjic-1083	23	22	consequents	consequent	NOUN
hjic-1083	23	23	(	(	PUNCT
hjic-1083	23	24	then	then	ADV
hjic-1083	23	25	-	-	PUNCT
hjic-1083	23	26	parts	part	NOUN
hjic-1083	23	27	)	)	PUNCT
hjic-1083	23	28	describe	describe	VERB
hjic-1083	23	29	the	the	DET
hjic-1083	23	30	local	local	ADJ
hjic-1083	23	31	behavior	behavior	NOUN
hjic-1083	23	32	of	of	ADP
hjic-1083	23	33	the	the	DET
hjic-1083	23	34	system	system	NOUN
hjic-1083	23	35	in	in	ADP
hjic-1083	23	36	these	these	DET
hjic-1083	23	37	fuzzy	fuzzy	ADJ
hjic-1083	23	38	subspaces	subspace	NOUN
hjic-1083	23	39	[	[	X
hjic-1083	23	40	7	7	NUM
hjic-1083	23	41	]	]	PUNCT
hjic-1083	23	42	.	.	PUNCT
hjic-1083	24	1	in	in	ADP
hjic-1083	24	2	this	this	DET
hjic-1083	24	3	paper	paper	NOUN
hjic-1083	24	4	the	the	DET
hjic-1083	24	5	local	local	ADJ
hjic-1083	24	6	models	model	NOUN
hjic-1083	24	7	are	be	AUX
hjic-1083	24	8	linear	linear	ADJ
hjic-1083	24	9	.	.	PUNCT
hjic-1083	25	1	the	the	DET
hjic-1083	25	2	contribution	contribution	NOUN
hjic-1083	25	3	of	of	ADP
hjic-1083	25	4	this	this	DET
hjic-1083	25	5	paper	paper	NOUN
hjic-1083	25	6	is	be	AUX
hjic-1083	25	7	two	two	NUM
hjic-1083	25	8	-	-	ADJ
hjic-1083	25	9	fold	fold	VERB
hjic-1083	25	10	:	:	PUNCT
hjic-1083	25	11	•	•	ADP
hjic-1083	25	12	a	a	DET
hjic-1083	25	13	new	new	ADJ
hjic-1083	25	14	method	method	NOUN
hjic-1083	25	15	for	for	ADP
hjic-1083	25	16	the	the	DET
hjic-1083	25	17	identification	identification	NOUN
hjic-1083	25	18	of	of	ADP
hjic-1083	25	19	operating	operate	VERB
hjic-1083	25	20	regime	regime	NOUN
hjic-1083	25	21	based	base	VERB
hjic-1083	25	22	models	model	NOUN
hjic-1083	25	23	is	be	AUX
hjic-1083	25	24	proposed	propose	VERB
hjic-1083	25	25	based	base	VERB
hjic-1083	25	26	on	on	ADP
hjic-1083	25	27	em	em	PRON
hjic-1083	25	28	identification	identification	NOUN
hjic-1083	25	29	of	of	ADP
hjic-1083	25	30	gaussian	gaussian	ADJ
hjic-1083	25	31	mixtures	mixture	NOUN
hjic-1083	25	32	model	model	NOUN
hjic-1083	25	33	.	.	PUNCT
hjic-1083	26	1	•	•	NOUN
hjic-1083	26	2	method	method	NOUN
hjic-1083	26	3	to	to	PART
hjic-1083	26	4	transform	transform	VERB
hjic-1083	26	5	the	the	DET
hjic-1083	26	6	obtained	obtain	VERB
hjic-1083	26	7	mt1del	mt1del	PROPN
hjic-1083	26	8	imo	imo	ADV
hjic-1083	26	9	takagi	takagi	PROPN
hjic-1083	26	10	-	-	PUNCT
hjic-1083	26	11	sugeno	sugeno	NOUN
hjic-1083	26	12	fuzzy	fuzzy	ADJ
hjic-1083	26	13	model	model	NOUN
hjic-1083	26	14	is	be	AUX
hjic-1083	26	15	presented	present	VERB
hjic-1083	26	16	.	.	PUNCT
hjic-1083	27	1	the	the	DET
hjic-1083	27	2	paper	paper	NOUN
hjic-1083	27	3	is	be	AUX
hjic-1083	27	4	organized	organize	VERB
hjic-1083	27	5	as	as	SCONJ
hjic-1083	27	6	follows	follow	VERB
hjic-1083	27	7	.	.	PUNCT
hjic-1083	28	1	section	section	NOUN
hjic-1083	28	2	2	2	NUM
hjic-1083	28	3	pre	pre	X
hjic-1083	28	4	~	~	PROPN
hjic-1083	28	5	ents	ent	NOUN
hjic-1083	28	6	the	the	DET
hjic-1083	28	7	structure	structure	NOUN
hjic-1083	28	8	of	of	ADP
hjic-1083	28	9	the	the	DET
hjic-1083	28	10	operating	operate	VERB
hjic-1083	28	11	regime	regime	NOUN
hjic-1083	28	12	based	base	VERB
hjic-1083	28	13	model	model	NOUN
hjic-1083	28	14	along	along	ADP
hjic-1083	28	15	with	with	ADP
hjic-1083	28	16	the	the	DET
hjic-1083	28	17	methods	method	NOUN
hjic-1083	28	18	for	for	ADP
hjic-1083	28	19	its	its	PRON
hjic-1083	28	20	transformation	transformation	NOUN
hjic-1083	28	21	into	into	ADP
hjic-1083	28	22	a	a	DET
hjic-1083	28	23	fuzzy	fuzzy	ADJ
hjic-1083	28	24	model	model	NOUN
hjic-1083	28	25	.	.	PUNCT
hjic-1083	29	1	in	in	ADP
hjic-1083	29	2	section	section	NOUN
hjic-1083	29	3	3	3	NUM
hjic-1083	29	4	,	,	PUNCT
hjic-1083	29	5	the	the	DET
hjic-1083	29	6	identification	identification	NOUN
hjic-1083	29	7	algorithm	algorithm	NOUN
hjic-1083	29	8	of	of	ADP
hjic-1083	29	9	the	the	DET
hjic-1083	29	10	130	130	NUM
hjic-1083	29	11	y(k	y(k	NOUN
hjic-1083	29	12	)	)	PUNCT
hjic-1083	29	13	where	where	SCONJ
hjic-1083	29	14	the	the	DET
hjic-1083	29	15	l	l	NOUN
hjic-1083	29	16	/	/	SYM
hjic-1083	29	17	j;(xk	j;(xk	NOUN
hjic-1083	29	18	)	)	PUNCT
hjic-1083	29	19	function	function	NOUN
hjic-1083	29	20	describes	describe	VERB
hjic-1083	29	21	the	the	DET
hjic-1083	29	22	operating	operate	VERB
hjic-1083	29	23	regime	regime	NOUN
hjic-1083	29	24	of	of	ADP
hjic-1083	29	25	the	the	DET
hjic-1083	29	26	i	i	PROPN
hjic-1083	29	27	-th	-th	INTJ
hjic-1083	29	28	local	local	ADJ
hjic-1083	29	29	linear	linear	NOUN
hjic-1083	29	30	model	model	NOUN
hjic-1083	29	31	defined	define	VERB
hjic-1083	29	32	by	by	ADP
hjic-1083	29	33	the	the	DET
hjic-1083	29	34	ei	ei	X
hjic-1083	29	35	=[	=[	NOUN
hjic-1083	29	36	a	a	NOUN
hjic-1083	29	37	;	;	PUNCT
hjic-1083	29	38	,	,	PUNCT
hjic-1083	29	39	bi	bi	NOUN
hjic-1083	29	40	r	r	NOUN
hjic-1083	29	41	parameter	parameter	NOUN
hjic-1083	29	42	vector	vector	NOUN
hjic-1083	29	43	.	.	PUNCT
hjic-1083	30	1	the	the	DET
hjic-1083	30	2	operating	operate	VERB
hjic-1083	30	3	regime	regime	NOUN
hjic-1083	30	4	of	of	ADP
hjic-1083	30	5	the	the	DET
hjic-1083	30	6	local	local	ADJ
hjic-1083	30	7	models	model	NOUN
hjic-1083	30	8	can	can	AUX
hjic-1083	30	9	also	also	ADV
hjic-1083	30	10	be	be	AUX
hjic-1083	30	11	represented	represent	VERB
hjic-1083	30	12	by	by	ADP
hjic-1083	30	13	fuzzy	fuzzy	ADJ
hjic-1083	30	14	sets	set	NOUN
hjic-1083	30	15	[	[	X
hjic-1083	30	16	6	6	NUM
hjic-1083	30	17	]	]	PUNCT
hjic-1083	30	18	.	.	PUNCT
hjic-1083	31	1	hence	hence	ADV
hjic-1083	31	2	,	,	PUNCT
hjic-1083	31	3	the	the	DET
hjic-1083	31	4	entire	entire	ADJ
hjic-1083	31	5	global	global	ADJ
hjic-1083	31	6	model	model	NOUN
hjic-1083	31	7	eq.(3	eq.(3	NOUN
hjic-1083	31	8	)	)	PUNCT
hjic-1083	31	9	can	can	AUX
hjic-1083	31	10	be	be	AUX
hjic-1083	31	11	conveniently	conveniently	ADV
hjic-1083	31	12	represented	represent	VERB
hjic-1083	31	13	by	by	ADP
hjic-1083	31	14	takagi	takagi	NOUN
hjic-1083	31	15	-	-	PUNCT
hjic-1083	31	16	sugeno	sugeno	NOUN
hjic-1083	31	17	fuzzy	fuzzy	ADJ
hjic-1083	31	18	rules	rule	NOUN
hjic-1083	31	19	:	:	PUNCT
hjic-1083	32	1	r	r	X
hjic-1083	32	2	;	;	PUNCT
hjic-1083	32	3	:	:	PUNCT
hjic-1083	32	4	if	if	SCONJ
hjic-1083	32	5	xk	xk	PROPN
hjic-1083	32	6	is	be	AUX
hjic-1083	32	7	a;(xk	a;(xk	PROPN
hjic-1083	32	8	)	)	PUNCT
hjic-1083	32	9	then	then	ADV
hjic-1083	32	10	yk	yk	PROPN
hjic-1083	32	11	=	=	PROPN
hjic-1083	32	12	a	a	PROPN
hjic-1083	32	13	;	;	PUNCT
hjic-1083	32	14	xk	xk	PROPN
hjic-1083	32	15	+	+	PROPN
hjic-1083	32	16	hi	hi	INTJ
hjic-1083	32	17	'	'	PUNCT
hjic-1083	32	18	i	i	NOUN
hjic-1083	32	19	=	=	SYM
hjic-1083	32	20	l	l	NOUN
hjic-1083	32	21	,	,	PUNCT
hjic-1083	32	22	...	...	PUNCT
hjic-1083	32	23	,	,	PUNCT
hjic-1083	32	24	c	c	X
hjic-1083	32	25	(	(	PUNCT
hjic-1083	32	26	4	4	NUM
hjic-1083	32	27	)	)	PUNCT
hjic-1083	32	28	u(k	u(k	PROPN
hjic-1083	32	29	)	)	PUNCT
hjic-1083	32	30	where	where	SCONJ
hjic-1083	32	31	a	a	PRON
hjic-1083	32	32	;	;	PUNCT
hjic-1083	32	33	(	(	PUNCT
hjic-1083	32	34	xk	xk	X
hjic-1083	32	35	)	)	PUNCT
hjic-1083	32	36	represents	represent	VERB
hjic-1083	32	37	the	the	DET
hjic-1083	32	38	multi	multi	ADJ
hjic-1083	32	39	variable	variable	ADJ
hjic-1083	32	40	membership	membership	NOUN
hjic-1083	32	41	function	function	NOUN
hjic-1083	32	42	that	that	PRON
hjic-1083	32	43	describes	describe	VERB
hjic-1083	32	44	the	the	DET
hjic-1083	32	45	fuzzy	fuzzy	ADJ
hjic-1083	32	46	set	set	NOUN
hjic-1083	32	47	a	a	PRON
hjic-1083	32	48	;	;	PUNCT
hjic-1083	32	49	while	while	SCONJ
hjic-1083	32	50	a	a	PRON
hjic-1083	32	51	;	;	PUNCT
hjic-1083	32	52	and	and	CCONJ
hjic-1083	32	53	fig	fig	NOUN
hjic-1083	32	54	.	.	PUNCT
hjic-1083	33	1	i	i	PRON
hjic-1083	33	2	example	example	VERB
hjic-1083	33	3	for	for	ADP
hjic-1083	33	4	an	an	DET
hjic-1083	33	5	operating	operate	VERB
hjic-1083	33	6	regime	regime	NOUN
hjic-1083	33	7	based	base	VERB
hjic-1083	33	8	model	model	NOUN
hjic-1083	33	9	.	.	PUNCT
hjic-1083	34	1	the	the	DET
hjic-1083	34	2	operating	operating	NOUN
hjic-1083	34	3	region	region	NOUN
hjic-1083	34	4	defined	define	VERB
hjic-1083	34	5	by	by	ADP
hjic-1083	34	6	the	the	DET
hjic-1083	34	7	current	current	ADJ
hjic-1083	34	8	input	input	NOUN
hjic-1083	34	9	u(k	u(k	PROPN
hjic-1083	34	10	)	)	PUNCT
hjic-1083	34	11	and	and	CCONJ
hjic-1083	34	12	output	output	PROPN
hjic-1083	34	13	y(k	y(k	PROPN
hjic-1083	34	14	)	)	PUNCT
hjic-1083	34	15	of	of	ADP
hjic-1083	34	16	the	the	DET
hjic-1083	34	17	system	system	NOUN
hjic-1083	34	18	is	be	AUX
hjic-1083	34	19	decomposed	decompose	VERB
hjic-1083	34	20	into	into	ADP
hjic-1083	34	21	four	four	NUM
hjic-1083	34	22	regimes	regime	NOUN
hjic-1083	34	23	.	.	PUNCT
hjic-1083	35	1	·	·	PUNCT
hjic-1083	35	2	model	model	NOUN
hjic-1083	35	3	is	be	AUX
hjic-1083	35	4	proposed	propose	VERB
hjic-1083	35	5	.	.	PUNCT
hjic-1083	36	1	an	an	DET
hjic-1083	36	2	application	application	NOUN
hjic-1083	36	3	example	example	NOUN
hjic-1083	36	4	the	the	DET
hjic-1083	36	5	identification	identification	NOUN
hjic-1083	36	6	of	of	ADP
hjic-1083	36	7	a	a	DET
hjic-1083	36	8	ph	ph	ADJ
hjic-1083	36	9	process	process	NOUN
hjic-1083	36	10	is	be	AUX
hjic-1083	36	11	given	give	VERB
hjic-1083	36	12	in	in	ADP
hjic-1083	36	13	section	section	NOUN
hjic-1083	36	14	3	3	NUM
hjic-1083	36	15	.	.	PUNCT
hjic-1083	37	1	conclusions	conclusion	NOUN
hjic-1083	37	2	are	be	AUX
hjic-1083	37	3	given	give	VERB
hjic-1083	37	4	in	in	ADP
hjic-1083	37	5	section	section	NOUN
hjic-1083	37	6	4	4	NUM
hjic-1083	37	7	.	.	PUNCT
hjic-1083	37	8	operating	operate	VERB
hjic-1083	37	9	regime	regime	NOUN
hjic-1083	37	10	based	base	VERB
hjic-1083	37	11	modeling	modeling	NOUN
hjic-1083	37	12	of	of	ADP
hjic-1083	37	13	dynamical	dynamical	ADJ
hjic-1083	37	14	system	system	NOUN
hjic-1083	37	15	nonlinear	nonlinear	ADJ
hjic-1083	37	16	dynamic	dynamic	ADJ
hjic-1083	37	17	systems	system	NOUN
hjic-1083	37	18	are	be	AUX
hjic-1083	37	19	often	often	ADV
hjic-1083	37	20	represented	represent	VERB
hjic-1083	37	21	in	in	ADP
hjic-1083	37	22	the	the	DET
hjic-1083	37	23	nonlinear	nonlinear	NOUN
hjic-1083	37	24	autoregressive	autoregressive	ADJ
hjic-1083	37	25	with	with	ADP
hjic-1083	37	26	exogenous	exogenous	ADJ
hjic-1083	37	27	input	input	NOUN
hjic-1083	37	28	(	(	PUNCT
hjic-1083	37	29	narx	narx	NOUN
hjic-1083	37	30	)	)	PUNCT
hjic-1083	37	31	model	model	NOUN
hjic-1083	37	32	form	form	NOUN
hjic-1083	37	33	,	,	PUNCT
hjic-1083	37	34	which	which	PRON
hjic-1083	37	35	establishes	establish	VERB
hjic-1083	37	36	a	a	DET
hjic-1083	37	37	nonlinear	nonlinear	ADJ
hjic-1083	37	38	relationship	relationship	NOUN
hjic-1083	37	39	between	between	ADP
hjic-1083	37	40	the	the	DET
hjic-1083	37	41	past	past	ADJ
hjic-1083	37	42	inputs	input	NOUN
hjic-1083	37	43	and	and	CCONJ
hjic-1083	37	44	outputs	output	NOUN
hjic-1083	37	45	and	and	CCONJ
hjic-1083	37	46	the	the	DET
hjic-1083	37	47	predicted	predict	VERB
hjic-1083	37	48	output	output	NOUN
hjic-1083	37	49	:	:	PUNCT
hjic-1083	37	50	y(k	y(k	PROPN
hjic-1083	37	51	+1	+1	PROPN
hjic-1083	37	52	)	)	PUNCT
hjic-1083	37	53	=	=	SYM
hjic-1083	37	54	f(y(k	f(y(k	NOUN
hjic-1083	37	55	)	)	PUNCT
hjic-1083	37	56	•.•.	•.•.	PROPN
hjic-1083	37	57	,	,	PUNCT
hjic-1083	37	58	y(k	y(k	PROPN
hjic-1083	37	59	-ny),u(~-nd	-ny),u(~-nd	PROPN
hjic-1083	37	60	)	)	PUNCT
hjic-1083	37	61	,	,	PUNCT
hjic-1083	37	62	.•.	.•.	PUNCT
hjic-1083	37	63	,	,	PUNCT
hjic-1083	37	64	u(k	u(k	PROPN
hjic-1083	37	65	-n	-n	NOUN
hjic-1083	37	66	"	"	PUNCT
hjic-1083	37	67	)	)	PUNCT
hjic-1083	37	68	)	)	PUNCT
hjic-1083	38	1	(	(	PUNCT
hjic-1083	38	2	1	1	X
hjic-1083	38	3	)	)	PUNCT
hjic-1083	38	4	here	here	ADV
hjic-1083	38	5	,	,	PUNCT
hjic-1083	38	6	n.	n.	NOUN
hjic-1083	38	7	,	,	PUNCT
hjic-1083	38	8	.	.	PUNCT
hjic-1083	39	1	and	and	CCONJ
hjic-1083	39	2	n	n	DET
hjic-1083	39	3	11	11	NUM
hjic-1083	39	4	denote	denote	VERB
hjic-1083	39	5	the	the	DET
hjic-1083	39	6	maximum	maximum	ADJ
hjic-1083	39	7	lags	lag	NOUN
hjic-1083	39	8	considered	consider	VERB
hjic-1083	39	9	for	for	ADP
hjic-1083	39	10	the	the	DET
hjic-1083	39	11	output	output	NOUN
hjic-1083	39	12	,	,	PUNCT
hjic-1083	39	13	and	and	CCONJ
hjic-1083	39	14	input	input	NOUN
hjic-1083	39	15	terms	term	NOUN
hjic-1083	39	16	,	,	PUNCT
hjic-1083	39	17	respectively	respectively	ADV
hjic-1083	39	18	,	,	PUNCT
hjic-1083	39	19	nd	nd	PRON
hjic-1083	39	20	<	<	X
hjic-1083	39	21	nil	nil	NOUN
hjic-1083	39	22	is	be	AUX
hjic-1083	39	23	the	the	DET
hjic-1083	39	24	discrete	discrete	ADJ
hjic-1083	39	25	dead	dead	ADJ
hjic-1083	39	26	time	time	NOUN
hjic-1083	39	27	,	,	PUNCT
hjic-1083	39	28	and	and	CCONJ
hjic-1083	39	29	f	f	PROPN
hjic-1083	39	30	represents	represent	VERB
hjic-1083	39	31	the	the	DET
hjic-1083	39	32	mapping	mapping	NOUN
hjic-1083	39	33	of	of	ADP
hjic-1083	39	34	the	the	DET
hjic-1083	39	35	narx	narx	PROPN
hjic-1083	39	36	model	model	NOUN
hjic-1083	39	37	.	.	PUNCT
hjic-1083	40	1	the	the	DET
hjic-1083	40	2	aim	aim	NOUN
hjic-1083	40	3	of	of	ADP
hjic-1083	40	4	this	this	DET
hjic-1083	40	5	paper	paper	NOUN
hjic-1083	40	6	is	be	AUX
hjic-1083	40	7	to	to	PART
hjic-1083	40	8	develop	develop	VERB
hjic-1083	40	9	an	an	DET
hjic-1083	40	10	algorithm	algorithm	NOUN
hjic-1083	40	11	for	for	ADP
hjic-1083	40	12	the	the	DET
hjic-1083	40	13	identification	identification	NOUN
hjic-1083	40	14	of	of	ADP
hjic-1083	40	15	a	a	DET
hjic-1083	40	16	transparent	transparent	ADJ
hjic-1083	40	17	and	and	CCONJ
hjic-1083	40	18	easily	easily	ADV
hjic-1083	40	19	interpretable	interpretable	ADJ
hjic-1083	40	20	model	model	NOUN
hjic-1083	40	21	(	(	PUNCT
hjic-1083	40	22	2	2	NUM
hjic-1083	40	23	)	)	PUNCT
hjic-1083	40	24	based	base	VERB
hjic-1083	40	25	on	on	ADP
hjic-1083	40	26	some	some	DET
hjic-1083	40	27	available	available	ADJ
hjic-1083	40	28	training	training	NOUN
hjic-1083	40	29	pattern	pattern	NOUN
hjic-1083	40	30	y1	y1	NOUN
hjic-1083	40	31	and	and	CCONJ
hjic-1083	40	32	x4	x4	NOUN
hjic-1083	40	33	=	=	PUNCT
hjic-1083	41	1	[	[	X
hjic-1083	41	2	tu	tu	X
hjic-1083	41	3	~	~	PUNCT
hjic-1083	41	4	....	....	PUNCT
hjic-1083	41	5	.xd	.xd	PUNCT
hjic-1083	41	6	y	y	PROPN
hjic-1083	41	7	t	t	PROPN
hjic-1083	41	8	where	where	SCONJ
hjic-1083	41	9	k	k	NOUN
hjic-1083	41	10	=	=	PUNCT
hjic-1083	41	11	1~	1~	NUM
hjic-1083	41	12	...	...	PUNCT
hjic-1083	41	13	~	~	PUNCT
hjic-1083	41	14	n	n	PRON
hjic-1083	41	15	denotes	denote	VERB
hjic-1083	41	16	the	the	DET
hjic-1083	41	17	index	index	NOUN
hjic-1083	41	18	:	:	PUNCT
hjic-1083	41	19	of	of	ADP
hjic-1083	41	20	the	the	DET
hjic-1083	41	21	k	k	PROPN
hjic-1083	41	22	..	..	PUNCT
hjic-1083	41	23	th	th	PROPN
hjic-1083	41	24	data	datum	NOUN
hjic-1083	41	25	that	that	PRON
hjic-1083	41	26	can	can	AUX
hjic-1083	41	27	be	be	AUX
hjic-1083	41	28	used	use	VERB
hjic-1083	41	29	for	for	ADP
hjic-1083	41	30	identification	identification	NOUN
hjic-1083	41	31	.	.	PUNCT
hjic-1083	42	1	when	when	SCONJ
hjic-1083	42	2	eq.(2	eq.(2	NOUN
hjic-1083	42	3	)	)	PUNCT
hjic-1083	42	4	is	be	AUX
hjic-1083	42	5	used	use	VERB
hjic-1083	42	6	to	to	PART
hjic-1083	42	7	represent	represent	VERB
hjic-1083	42	8	a	a	DET
hjic-1083	42	9	narx	narx	NOUN
hjic-1083	42	10	modet	modet	NOUN
hjic-1083	42	11	the	the	DET
hjic-1083	42	12	training	training	NOUN
hjic-1083	42	13	pattern	pattern	NOUN
hjic-1083	42	14	is	be	AUX
hjic-1083	42	15	formed	form	VERB
hjic-1083	42	16	to	to	PART
hjic-1083	42	17	have	have	VERB
hjic-1083	42	18	a	a	DET
hjic-1083	42	19	model	model	NOUN
hjic-1083	42	20	that	that	PRON
hjic-1083	42	21	gives	give	VERB
hjic-1083	42	22	one	one	NUM
hjic-1083	42	23	-	-	PUNCT
hjic-1083	42	24	step	step	NOUN
hjic-1083	42	25	-	-	PUNCT
hjic-1083	42	26	ahead	ahead	NOUN
hjic-1083	42	27	prediction	prediction	NOUN
hjic-1083	42	28	:	:	PUNCT
hjic-1083	42	29	yt	yt	PROPN
hjic-1083	42	30	=	=	PUNCT
hjic-1083	42	31	y(k	y(k	PROPN
hjic-1083	42	32	+	+	PROPN
hjic-1083	42	33	ll	ll	NOUN
hjic-1083	42	34	,	,	PUNCT
hjic-1083	42	35	xt	xt	X
hjic-1083	43	1	=	=	PUNCT
hjic-1083	44	1	[	[	X
hjic-1083	44	2	v(k	v(k	NOUN
hjic-1083	44	3	)	)	PUNCT
hjic-1083	44	4	•	•	NUM
hjic-1083	44	5	...	...	PUNCT
hjic-1083	45	1	~y(k	~y(k	ADJ
hjic-1083	45	2	-n~),u(k	-n~),u(k	ADJ
hjic-1083	45	3	-nj)•	-nj)•	PROPN
hjic-1083	45	4	...	...	PUNCT
hjic-1083	45	5	•	•	NUM
hjic-1083	45	6	u(k	u(k	PROPN
hjic-1083	45	7	-n,	-n,	NOUN
hjic-1083	45	8	.	.	PUNCT
hjic-1083	45	9	,).f	,).f	PROPN
hjic-1083	45	10	.	.	PUNCT
hjic-1083	46	1	the	the	DET
hjic-1083	46	2	operating	operate	VERB
hjic-1083	46	3	regime	regime	NOUN
hjic-1083	46	4	based	base	VERB
hjic-1083	46	5	model	model	NOUN
hjic-1083	46	6	of	of	ADP
hjic-1083	46	7	the	the	DET
hjic-1083	46	8	system	system	NOUN
hjic-1083	46	9	given	give	VERB
hjic-1083	46	10	by	by	ADP
hjic-1083	46	11	eq.(2j	eq.(2j	NOUN
hjic-1083	46	12	is	be	AUX
hjic-1083	46	13	formulated	formulate	VERB
hjic-1083	46	14	as	as	ADP
hjic-1083	46	15	:	:	PUNCT
hjic-1083	46	16	r	r	NOUN
hjic-1083	46	17	5	5	NUM
hjic-1083	46	18	,	,	PUNCT
hjic-1083	46	19	.	.	PUNCT
hjic-1083	46	20	,	,	PUNCT
hjic-1083	46	21	=	=	PUNCT
hjic-1083	46	22	l9i(x	l9i(x	ADJ
hjic-1083	46	23	,	,	PUNCT
hjic-1083	46	24	)	)	PUNCT
hjic-1083	46	25	(	(	PUNCT
hjic-1083	46	26	al	al	PROPN
hjic-1083	46	27	xh	xh	PROPN
hjic-1083	46	28	+	+	PROPN
hjic-1083	46	29	hi	hi	INTJ
hjic-1083	46	30	)	)	PUNCT
hjic-1083	46	31	(	(	PUNCT
hjic-1083	46	32	3	3	X
hjic-1083	46	33	)	)	PUNCT
hjic-1083	46	34	l	l	NOUN
hjic-1083	46	35	=	=	NOUN
hjic-1083	46	36	l	l	NOUN
hjic-1083	46	37	bi	bi	NOUN
hjic-1083	46	38	are	be	AUX
hjic-1083	46	39	the	the	DET
hjic-1083	46	40	parameters	parameter	NOUN
hjic-1083	46	41	of	of	ADP
hjic-1083	46	42	the	the	DET
hjic-1083	46	43	local	local	ADJ
hjic-1083	46	44	linear	linear	PROPN
hjic-1083	46	45	model	model	NOUN
hjic-1083	46	46	.	.	PUNCT
hjic-1083	47	1	usually	usually	ADV
hjic-1083	47	2	,	,	PUNCT
hjic-1083	47	3	the	the	DET
hjic-1083	47	4	antecedent	antecedent	NOUN
hjic-1083	47	5	proposition	proposition	NOUN
hjic-1083	47	6	"	"	PUNCT
hjic-1083	47	7	xk	xk	PROPN
hjic-1083	47	8	is	be	AUX
hjic-1083	47	9	a;(xk	a;(xk	PROPN
hjic-1083	47	10	)	)	PUNCT
hjic-1083	47	11	"	"	PUNCT
hjic-1083	47	12	is	be	AUX
hjic-1083	47	13	expressed	express	VERB
hjic-1083	47	14	as	as	ADP
hjic-1083	47	15	a	a	DET
hjic-1083	47	16	logical	logical	ADJ
hjic-1083	47	17	combination	combination	NOUN
hjic-1083	47	18	of	of	ADP
hjic-1083	47	19	simple	simple	ADJ
hjic-1083	47	20	propositions	proposition	NOUN
hjic-1083	47	21	with	with	ADP
hjic-1083	47	22	univariate	univariate	ADJ
hjic-1083	47	23	fuzzy	fuzzy	ADJ
hjic-1083	47	24	sets	set	NOUN
hjic-1083	47	25	defined	define	VERB
hjic-1083	47	26	for	for	ADP
hjic-1083	47	27	the	the	DET
hjic-1083	47	28	individual	individual	ADJ
hjic-1083	47	29	components	component	NOUN
hjic-1083	47	30	of	of	ADP
hjic-1083	47	31	xk	xk	PROPN
hjic-1083	47	32	,	,	PUNCT
hjic-1083	47	33	often	often	ADV
hjic-1083	47	34	in	in	ADP
hjic-1083	47	35	a	a	DET
hjic-1083	47	36	conjunction	conjunction	NOUN
hjic-1083	47	37	form	form	NOUN
hjic-1083	47	38	:	:	PUNCT
hjic-1083	47	39	r1•	r1•	PUNCT
hjic-1083	47	40	:	:	PUNCT
hjic-1083	47	41	if	if	SCONJ
hjic-1083	47	42	x	x	SYM
hjic-1083	47	43	1	1	NUM
hjic-1083	47	44	k	k	NOUN
hjic-1083	47	45	is	be	AUX
hjic-1083	47	46	a1•	a1•	NUM
hjic-1083	47	47	1	1	NUM
hjic-1083	47	48	(	(	PUNCT
hjic-1083	47	49	x1	x1	PROPN
hjic-1083	47	50	k	k	NOUN
hjic-1083	47	51	)	)	PUNCT
hjic-1083	47	52	and	and	CCONJ
hjic-1083	47	53	...	...	PUNCT
hjic-1083	48	1	and	and	CCONJ
hjic-1083	48	2	xn	xn	X
hjic-1083	48	3	k	k	PROPN
hjic-1083	48	4	is	be	AUX
hjic-1083	48	5	a	a	PRON
hjic-1083	48	6	;	;	PUNCT
hjic-1083	48	7	n	n	X
hjic-1083	48	8	(	(	PUNCT
hjic-1083	48	9	xn	xn	PROPN
hjic-1083	48	10	k	k	NOUN
hjic-1083	48	11	)	)	PUNCT
hjic-1083	48	12	,	,	PUNCT
hjic-1083	48	13	,	,	PUNCT
hjic-1083	48	14	,	,	PUNCT
hjic-1083	48	15	,	,	PUNCT
hjic-1083	48	16	'	'	PUNCT
hjic-1083	48	17	'	'	PUNCT
hjic-1083	48	18	(	(	PUNCT
hjic-1083	48	19	5	5	NUM
hjic-1083	48	20	)	)	PUNCT
hjic-1083	48	21	then	then	ADV
hjic-1083	48	22	yk	yk	PROPN
hjic-1083	48	23	=	=	PROPN
hjic-1083	48	24	a	a	PROPN
hjic-1083	48	25	;	;	PUNCT
hjic-1083	49	1	xk	xk	PROPN
hjic-1083	49	2	+	+	PROPN
hjic-1083	49	3	h	h	NOUN
hjic-1083	49	4	;	;	PUNCT
hjic-1083	49	5	in	in	ADP
hjic-1083	49	6	this	this	DET
hjic-1083	49	7	case	case	NOUN
hjic-1083	49	8	,	,	PUNCT
hjic-1083	49	9	the	the	DET
hjic-1083	49	10	degree	degree	NOUN
hjic-1083	49	11	of	of	ADP
hjic-1083	49	12	fulfillment	fulfillment	NOUN
hjic-1083	49	13	of	of	ADP
hjic-1083	49	14	a	a	DET
hjic-1083	49	15	rule	rule	NOUN
hjic-1083	49	16	is	be	AUX
hjic-1083	49	17	calculated	calculate	VERB
hjic-1083	49	18	as	as	ADP
hjic-1083	49	19	the	the	DET
hjic-1083	49	20	product	product	NOUN
hjic-1083	49	21	of	of	ADP
hjic-1083	49	22	the	the	DET
hjic-1083	49	23	degree	degree	NOUN
hjic-1083	49	24	of	of	ADP
hjic-1083	49	25	fulfillment	fulfillment	NOUN
hjic-1083	49	26	of	of	ADP
hjic-1083	49	27	the	the	DET
hjic-1083	49	28	fuzzy	fuzzy	ADJ
hjic-1083	49	29	sets	set	NOUN
hjic-1083	49	30	in	in	ADP
hjic-1083	49	31	the	the	DET
hjic-1083	49	32	rule	rule	NOUN
hjic-1083	49	33	/3;(xk	/3;(xk	PUNCT
hjic-1083	49	34	)	)	PUNCT
hjic-1083	49	35	=	=	SYM
hjic-1083	49	36	a;(xk	a;(xk	PROPN
hjic-1083	49	37	)	)	PUNCT
hjic-1083	49	38	=	=	SYM
hjic-1083	49	39	ii	ii	PROPN
hjic-1083	49	40	:	:	PUNCT
hjic-1083	49	41	ai	ai	VERB
hjic-1083	49	42	,	,	PUNCT
hjic-1083	49	43	j(xj	j(xj	ADV
hjic-1083	49	44	,	,	PUNCT
hjic-1083	49	45	k	k	NOUN
hjic-1083	49	46	)	)	PUNCT
hjic-1083	49	47	(	(	PUNCT
hjic-1083	49	48	6	6	NUM
hjic-1083	49	49	)	)	PUNCT
hjic-1083	49	50	j	j	NOUN
hjic-1083	50	1	=	=	PROPN
hjic-1083	50	2	l	l	NOUN
hjic-1083	50	3	'	'	PUNCT
hjic-1083	50	4	the	the	DET
hjic-1083	50	5	rules	rule	NOUN
hjic-1083	50	6	of	of	ADP
hjic-1083	50	7	the	the	DET
hjic-1083	50	8	fuzzy	fuzzy	ADJ
hjic-1083	50	9	model	model	NOUN
hjic-1083	50	10	are	be	AUX
hjic-1083	50	11	aggregated	aggregate	VERB
hjic-1083	50	12	using	use	VERB
hjic-1083	50	13	the	the	DET
hjic-1083	50	14	fuzzy	fuzzy	ADJ
hjic-1083	50	15	mean	mean	NOUN
hjic-1083	50	16	formula	formula	NOUN
hjic-1083	50	17	c	c	PROPN
hjic-1083	50	18	l	l	NOUN
hjic-1083	50	19	wi	wi	PROPN
hjic-1083	50	20	/3;(xk)(a;xk	/3;(xk)(a;xk	PUNCT
hjic-1083	51	1	+	+	PROPN
hjic-1083	51	2	b	b	X
hjic-1083	51	3	)	)	PUNCT
hjic-1083	51	4	yk=~~~~---c----------(7	yk=~~~~---c----------(7	PROPN
hjic-1083	51	5	)	)	PUNCT
hjic-1083	51	6	lw	lw	PROPN
hjic-1083	51	7	;	;	PUNCT
hjic-1083	51	8	f3;(xk	f3;(xk	PROPN
hjic-1083	51	9	)	)	PUNCT
hjic-1083	51	10	i	i	PROPN
hjic-1083	52	1	=	=	NOUN
hjic-1083	52	2	l	l	X
hjic-1083	52	3	where	where	SCONJ
hjic-1083	52	4	w	w	NOUN
hjic-1083	52	5	;	;	PUNCT
hjic-1083	52	6	=	=	SYM
hjic-1083	53	1	[	[	X
hjic-1083	53	2	0,1	0,1	NUM
hjic-1083	53	3	]	]	PUNCT
hjic-1083	53	4	is	be	AUX
hjic-1083	53	5	the	the	DET
hjic-1083	53	6	weight	weight	NOUN
hjic-1083	53	7	of	of	ADP
hjic-1083	53	8	the	the	DET
hjic-1083	53	9	rule	rule	NOUN
hjic-1083	53	10	that	that	PRON
hjic-1083	53	11	represents	represent	VERB
hjic-1083	53	12	the	the	DET
hjic-1083	53	13	desired	desire	VERB
hjic-1083	53	14	impact	impact	NOUN
hjic-1083	53	15	of	of	ADP
hjic-1083	53	16	the	the	DET
hjic-1083	53	17	rule	rule	NOUN
hjic-1083	53	18	.	.	PUNCT
hjic-1083	54	1	the	the	DET
hjic-1083	54	2	value	value	NOUN
hjic-1083	54	3	of	of	ADP
hjic-1083	54	4	w	w	NOUN
hjic-1083	54	5	;	;	PUNCT
hjic-1083	54	6	is	be	AUX
hjic-1083	54	7	often	often	ADV
hjic-1083	54	8	chosen	choose	VERB
hjic-1083	54	9	by	by	ADP
hjic-1083	54	10	the	the	DET
hjic-1083	54	11	designer	designer	NOUN
hjic-1083	54	12	of	of	ADP
hjic-1083	54	13	the	the	DET
hjic-1083	54	14	fuzzy	fuzzy	ADJ
hjic-1083	54	15	system	system	NOUN
hjic-1083	54	16	based	base	VERB
hjic-1083	54	17	on	on	ADP
hjic-1083	54	18	his	his	PRON
hjic-1083	54	19	or	or	CCONJ
hjic-1083	54	20	her	her	PRON
hjic-1083	54	21	belief	belief	NOUN
hjic-1083	54	22	in	in	ADP
hjic-1083	54	23	the	the	DET
hjic-1083	54	24	goodness	goodness	NOUN
hjic-1083	54	25	and	and	CCONJ
hjic-1083	54	26	accuracy	accuracy	NOUN
hjic-1083	54	27	of	of	ADP
hjic-1083	54	28	the	the	DET
hjic-1083	54	29	i	i	PROPN
hjic-1083	54	30	-th	-th	NOUN
hjic-1083	54	31	rule	rule	NOUN
hjic-1083	54	32	.	.	PUNCT
hjic-1083	55	1	when	when	SCONJ
hjic-1083	55	2	such	such	ADJ
hjic-1083	55	3	knowledge	knowledge	NOUN
hjic-1083	55	4	is	be	AUX
hjic-1083	55	5	not	not	PART
hjic-1083	55	6	available	available	ADJ
hjic-1083	55	7	w	w	NOUN
hjic-1083	55	8	;	;	PUNCT
hjic-1083	55	9	is	be	AUX
hjic-1083	55	10	set	set	VERB
hjic-1083	55	11	as	as	ADP
hjic-1083	55	12	w	w	NOUN
hjic-1083	55	13	;	;	PUNCT
hjic-1083	55	14	=	=	SYM
hjic-1083	55	15	1	1	NUM
hjic-1083	55	16	,	,	PUNCT
hjic-1083	55	17	\;fj	\;fj	NOUN
hjic-1083	55	18	.	.	PUNCT
hjic-1083	55	19	as	as	ADP
hjic-1083	55	20	eq.(7	eq.(7	NOUN
hjic-1083	55	21	)	)	PUNCT
hjic-1083	55	22	and	and	CCONJ
hjic-1083	55	23	eq.(3	eq.(3	NOUN
hjic-1083	55	24	)	)	PUNCT
hjic-1083	55	25	show	show	NOUN
hjic-1083	55	26	,	,	PUNCT
hjic-1083	55	27	fuzzy	fuzzy	ADJ
hjic-1083	55	28	models	model	NOUN
hjic-1083	55	29	are	be	AUX
hjic-1083	55	30	identical	identical	ADJ
hjic-1083	55	31	to	to	ADP
hjic-1083	55	32	operating	operate	VERB
hjic-1083	55	33	regime	regime	NOUN
hjic-1083	55	34	based	base	VERB
hjic-1083	55	35	models	model	NOUN
hjic-1083	55	36	as	as	SCONJ
hjic-1083	55	37	the	the	DET
hjic-1083	55	38	operating	operating	NOUN
hjic-1083	55	39	region	region	NOUN
hjic-1083	55	40	of	of	ADP
hjic-1083	55	41	the	the	DET
hjic-1083	55	42	local	local	ADJ
hjic-1083	55	43	linear	linear	NOUN
hjic-1083	55	44	models	model	NOUN
hjic-1083	55	45	are	be	AUX
hjic-1083	55	46	defined	define	VERB
hjic-1083	55	47	by	by	ADP
hjic-1083	55	48	the	the	DET
hjic-1083	55	49	normalized	normalize	VERB
hjic-1083	55	50	rule	rule	NOUN
hjic-1083	55	51	fulfillments	fulfillment	NOUN
hjic-1083	55	52	:	:	PUNCT
hjic-1083	55	53	w	w	X
hjic-1083	55	54	;	;	PUNCT
hjic-1083	55	55	{	{	PUNCT
hjic-1083	55	56	3i(xk	3i(xk	NUM
hjic-1083	55	57	)	)	PUNCT
hjic-1083	55	58	r	r	NOUN
hjic-1083	55	59	(	(	PUNCT
hjic-1083	55	60	8)	8)	NUM
hjic-1083	55	61	l	l	NOUN
hjic-1083	55	62	:	:	PUNCT
hjic-1083	55	63	wi	wi	PROPN
hjic-1083	55	64	/3;(xa	/3;(xa	PUNCT
hjic-1083	55	65	)	)	PUNCT
hjic-1083	55	66	i	i	PROPN
hjic-1083	56	1	=	=	NOUN
hjic-1083	56	2	l	l	NOUN
hjic-1083	56	3	to	to	PART
hjic-1083	56	4	represent	represent	VERB
hjic-1083	56	5	the	the	DET
hjic-1083	56	6	ai.i(xu	ai.i(xu	ADJ
hjic-1083	56	7	)	)	PUNCT
hjic-1083	56	8	fuzzy	fuzzy	ADJ
hjic-1083	56	9	set	set	NOUN
hjic-1083	56	10	,	,	PUNCT
hjic-1083	56	11	in	in	ADP
hjic-1083	56	12	this	this	DET
hjic-1083	56	13	paper	paper	NOUN
hjic-1083	56	14	gaussian	gaussian	NOUN
hjic-1083	56	15	membership	membership	NOUN
hjic-1083	56	16	function	function	NOUN
hjic-1083	56	17	is	be	AUX
hjic-1083	56	18	used	use	VERB
hjic-1083	56	19	(	(	PUNCT
hjic-1083	56	20	9	9	NUM
hjic-1083	56	21	)	)	PUNCT
hjic-1083	56	22	where	where	SCONJ
hjic-1083	56	23	v	v	NOUN
hjic-1083	56	24	,	,	PUNCT
hjic-1083	56	25	.	.	PUNCT
hjic-1083	56	26	.	.	PUNCT
hjic-1083	57	1	represents	represent	VERB
hjic-1083	57	2	the	the	DET
hjic-1083	57	3	center	center	NOUN
hjic-1083	57	4	and	and	CCONJ
hjic-1083	57	5	a,~	a,~	NOUN
hjic-1083	57	6	.	.	PUNCT
hjic-1083	58	1	the	the	DET
hjic-1083	58	2	.	.	PUNCT
hjic-1083	58	3	variance	variance	NOUN
hjic-1083	58	4	of	of	ADP
hjic-1083	58	5	,	,	PUNCT
hjic-1083	58	6	j	j	PROPN
hjic-1083	58	7	,	,	PUNCT
hjic-1083	58	8	)	)	PUNCT
hjic-1083	58	9	the	the	DET
hjic-1083	58	10	gaussian	gaussian	ADJ
hjic-1083	58	11	function	function	NOUN
hjic-1083	58	12	.	.	PUNCT
hjic-1083	59	1	the	the	DET
hjic-1083	59	2	use	use	NOUN
hjic-1083	59	3	of	of	ADP
hjic-1083	59	4	gaussian	gaussian	ADJ
hjic-1083	59	5	membership	membership	NOUN
hjic-1083	59	6	functions	function	NOUN
hjic-1083	59	7	allows	allow	VERB
hjic-1083	59	8	the	the	DET
hjic-1083	59	9	compact	compact	ADJ
hjic-1083	59	10	formulation	formulation	NOUN
hjic-1083	59	11	of	of	ADP
hjic-1083	59	12	eq.(6	eq.(6	NOUN
hjic-1083	59	13	):	):	PUNCT
hjic-1083	59	14	,	,	PUNCT
hjic-1083	59	15	b;(x	b;(x	NOUN
hjic-1083	59	16	,	,	PUNCT
hjic-1083	59	17	)	)	PUNCT
hjic-1083	59	18	~	~	PUNCT
hjic-1083	60	1	a;(x	a;(x	NOUN
hjic-1083	60	2	,	,	PUNCT
hjic-1083	60	3	)	)	PUNCT
hjic-1083	60	4	~exp	~exp	PROPN
hjic-1083	60	5	(	(	PUNCT
hjic-1083	60	6	-~(x,-v;l	-~(x,-v;l	PROPN
hjic-1083	60	7	(	(	PUNCT
hjic-1083	60	8	f;'t	f;'t	NOUN
hjic-1083	60	9	'	'	PUNCT
hjic-1083	60	10	(	(	PUNCT
hjic-1083	60	11	x	x	NOUN
hjic-1083	60	12	,	,	PUNCT
hjic-1083	60	13	vj	vj	PROPN
hjic-1083	60	14	)	)	PUNCT
hjic-1083	60	15	)	)	PUNCT
hjic-1083	60	16	(	(	PUNCT
hjic-1083	60	17	10	10	NUM
hjic-1083	60	18	)	)	PUNCT
hjic-1083	61	1	where	where	SCONJ
hjic-1083	61	2	v~	v~	NOUN
hjic-1083	61	3	=	=	PUNCT
hjic-1083	61	4	[	[	PUNCT
hjic-1083	61	5	v1,j	v1,j	PROPN
hjic-1083	61	6	'	'	PUNCT
hjic-1083	61	7	...	...	PUNCT
hjic-1083	61	8	,	,	PUNCT
hjic-1083	61	9	v	v	NOUN
hjic-1083	61	10	n	n	CCONJ
hjic-1083	61	11	)	)	PUNCT
hjic-1083	61	12	represents	represent	VERB
hjic-1083	61	13	the	the	DET
hjic-1083	61	14	center	center	NOUN
hjic-1083	61	15	of	of	ADP
hjic-1083	61	16	the	the	DET
hjic-1083	61	17	i	i	PROPN
hjic-1083	61	18	th	th	X
hjic-1083	61	19	multivariate	multivariate	NOUN
hjic-1083	61	20	gaussian	gaussian	NOUN
hjic-1083	61	21	and	and	CCONJ
hjic-1083	61	22	(	(	PUNCT
hjic-1083	61	23	f	f	X
hjic-1083	61	24	:	:	PUNCT
hjic-1083	61	25	xf1	xf1	INTJ
hjic-1083	61	26	stands	stand	VERB
hjic-1083	61	27	for	for	ADP
hjic-1083	61	28	the	the	DET
hjic-1083	61	29	inverse	inverse	NOUN
hjic-1083	61	30	of	of	ADP
hjic-1083	61	31	a	a	DET
hjic-1083	61	32	diagonal	diagonal	ADJ
hjic-1083	61	33	matrix	matrix	NOUN
hjic-1083	61	34	that	that	PRON
hjic-1083	61	35	contains	contain	VERB
hjic-1083	61	36	the	the	DET
hjic-1083	61	37	variances	variance	NOUN
hjic-1083	61	38	:	:	PUNCT
hjic-1083	62	1	[	[	X
hjic-1083	62	2	a~	a~	PROPN
hjic-1083	62	3	;	;	PUNCT
hjic-1083	62	4	0	0	NUM
hjic-1083	62	5	xx	xx	NUM
hjic-1083	62	6	0	0	NUM
hjic-1083	62	7	2	2	NUM
hjic-1083	62	8	fi	fi	NOUN
hjic-1083	62	9	=	=	NOUN
hjic-1083	62	10	:	:	PUNCT
hjic-1083	62	11	(	(	PUNCT
hjic-1083	62	12	j2,i	j2,i	NOUN
hjic-1083	62	13	0	0	NUM
hjic-1083	62	14	0	0	NUM
hjic-1083	62	15	1	1	NUM
hjic-1083	62	16	]	]	PUNCT
hjic-1083	62	17	(	(	PUNCT
hjic-1083	62	18	11	11	NUM
hjic-1083	62	19	)	)	PUNCT
hjic-1083	62	20	this	this	DET
hjic-1083	62	21	compact	compact	ADJ
hjic-1083	62	22	formulation	formulation	NOUN
hjic-1083	62	23	of	of	ADP
hjic-1083	62	24	the	the	DET
hjic-1083	62	25	operating	operate	VERB
hjic-1083	62	26	regime	regime	NOUN
hjic-1083	62	27	based	base	VERB
hjic-1083	62	28	model	model	NOUN
hjic-1083	62	29	suggests	suggest	VERB
hjic-1083	62	30	that	that	SCONJ
hjic-1083	62	31	the	the	DET
hjic-1083	62	32	model	model	NOUN
hjic-1083	62	33	is	be	AUX
hjic-1083	62	34	not	not	PART
hjic-1083	62	35	only	only	ADV
hjic-1083	62	36	equivalent	equivalent	ADJ
hjic-1083	62	37	to	to	ADP
hjic-1083	62	38	a	a	DET
hjic-1083	62	39	ts	ts	X
hjic-1083	62	40	fuzzy	fuzzy	ADJ
hjic-1083	62	41	model	model	NOUN
hjic-1083	62	42	but	but	CCONJ
hjic-1083	62	43	it	it	PRON
hjic-1083	62	44	is	be	AUX
hjic-1083	62	45	functionally	functionally	ADV
hjic-1083	62	46	identical	identical	ADJ
hjic-1083	62	47	to	to	ADP
hjic-1083	62	48	generalized	generalized	ADJ
hjic-1083	62	49	radial	radial	ADJ
hjic-1083	62	50	basis	basis	NOUN
hjic-1083	62	51	function	function	NOUN
hjic-1083	62	52	network	network	NOUN
hjic-1083	62	53	(	(	PUNCT
hjic-1083	62	54	gbfn	gbfn	NOUN
hjic-1083	62	55	)	)	PUNCT
hjic-1083	63	1	[	[	X
hjic-1083	63	2	8	8	NUM
hjic-1083	63	3	]	]	PUNCT
hjic-1083	63	4	.	.	PUNCT
hjic-1083	64	1	when	when	SCONJ
hjic-1083	64	2	there	there	PRON
hjic-1083	64	3	is	be	VERB
hjic-1083	64	4	a	a	DET
hjic-1083	64	5	correlation	correlation	NOUN
hjic-1083	64	6	among	among	ADP
hjic-1083	64	7	input	input	NOUN
hjic-1083	64	8	variables	variable	NOUN
hjic-1083	64	9	of	of	ADP
hjic-1083	64	10	the	the	DET
hjic-1083	64	11	model	model	NOUN
hjic-1083	64	12	,	,	PUNCT
hjic-1083	64	13	f;xx	f;xx	PROPN
hjic-1083	64	14	is	be	AUX
hjic-1083	64	15	not	not	PART
hjic-1083	64	16	a	a	DET
hjic-1083	64	17	diagonal	diagonal	ADJ
hjic-1083	64	18	matrix	matrix	NOUN
hjic-1083	64	19	as	as	SCONJ
hjic-1083	64	20	it	it	PRON
hjic-1083	64	21	was	be	AUX
hjic-1083	64	22	shown	show	VERB
hjic-1083	64	23	in	in	ADP
hjic-1083	64	24	eq.(ll	eq.(ll	ADJ
hjic-1083	64	25	)	)	PUNCT
hjic-1083	64	26	.	.	PUNCT
hjic-1083	65	1	in	in	ADP
hjic-1083	65	2	this	this	DET
hjic-1083	65	3	case	case	NOUN
hjic-1083	65	4	the	the	DET
hjic-1083	65	5	decomposition	decomposition	NOUN
hjic-1083	65	6	of	of	ADP
hjic-1083	65	7	ai(xk	ai(xk	PROPN
hjic-1083	65	8	)	)	PUNCT
hjic-1083	65	9	to	to	ADP
hjic-1083	65	10	~./xj	~./xj	NUM
hjic-1083	65	11	,	,	PUNCT
hjic-1083	65	12	k	k	NOUN
hjic-1083	65	13	)	)	PUNCT
hjic-1083	65	14	fuzzy	fuzzy	ADJ
hjic-1083	65	15	sets	set	NOUN
hjic-1083	65	16	by	by	ADP
hjic-1083	65	17	a	a	DET
hjic-1083	65	18	(	(	PUNCT
hjic-1083	65	19	ii	ii	NOUN
hjic-1083	65	20	n	n	PROPN
hjic-1083	65	21	(	(	PUNCT
hjic-1083	65	22	)	)	PUNCT
hjic-1083	65	23	iin	iin	NOUN
hjic-1083	65	24	(	(	PUNCT
hjic-1083	65	25	1	1	NUM
hjic-1083	65	26	(	(	PUNCT
hjic-1083	65	27	xj	xj	PROPN
hjic-1083	65	28	,	,	PUNCT
hjic-1083	65	29	k	k	PROPN
hjic-1083	65	30	-zvi	-zvi	PROPN
hjic-1083	65	31	,	,	PUNCT
hjic-1083	65	32	jl	jl	NOUN
hjic-1083	65	33	)	)	PUNCT
hjic-1083	65	34	(	(	PUNCT
hjic-1083	65	35	12	12	NUM
hjic-1083	65	36	)	)	PUNCT
hjic-1083	65	37	i	i	PRON
hjic-1083	65	38	xk	xk	ADJ
hjic-1083	65	39	)	)	PUNCT
hjic-1083	66	1	=	=	PUNCT
hjic-1083	67	1	i	i	NOUN
hjic-1083	67	2	=	=	VERB
hjic-1083	67	3	l	l	X
hjic-1083	67	4	~.i	~.i	PUNCT
hjic-1083	67	5	xi	xi	PROPN
hjic-1083	67	6	,	,	PUNCT
hjic-1083	67	7	k	k	PROPN
hjic-1083	68	1	=	=	PUNCT
hjic-1083	68	2	i	i	PROPN
hjic-1083	68	3	=	=	NOUN
hjic-1083	68	4	l	l	NOUN
hjic-1083	68	5	exp	exp	NOUN
hjic-1083	68	6	2	2	NUM
hjic-1083	68	7	ai	ai	NOUN
hjic-1083	68	8	,	,	PUNCT
hjic-1083	68	9	j	j	PROPN
hjic-1083	68	10	is	be	AUX
hjic-1083	68	11	not	not	PART
hjic-1083	68	12	possible	possible	ADJ
hjic-1083	68	13	directly	directly	ADV
hjic-1083	68	14	.	.	PUNCT
hjic-1083	69	1	the	the	DET
hjic-1083	69	2	proposed	propose	VERB
hjic-1083	69	3	method	method	NOUN
hjic-1083	69	4	to	to	PART
hjic-1083	69	5	solve	solve	VERB
hjic-1083	69	6	this	this	DET
hjic-1083	69	7	problem	problem	NOUN
hjic-1083	69	8	is	be	AUX
hjic-1083	69	9	based	base	VERB
hjic-1083	69	10	on	on	ADP
hjic-1083	69	11	the	the	DET
hjic-1083	69	12	eigenvector	eigenvector	NOUN
hjic-1083	69	13	projection	projection	NOUN
hjic-1083	69	14	[	[	X
hjic-1083	69	15	9	9	NUM
hjic-1083	69	16	]	]	PUNCT
hjic-1083	69	17	or	or	CCONJ
hjic-1083	69	18	transformed	transform	VERB
hjic-1083	69	19	input	input	NOUN
hjic-1083	69	20	-	-	PUNCT
hjic-1083	69	21	domain	domain	NOUN
hjic-1083	69	22	approach	approach	NOUN
hjic-1083	69	23	[	[	X
hjic-1083	69	24	10	10	NUM
hjic-1083	69	25	]	]	PUNCT
hjic-1083	69	26	.	.	PUNCT
hjic-1083	70	1	the	the	DET
hjic-1083	70	2	approach	approach	NOUN
hjic-1083	70	3	is	be	AUX
hjic-1083	70	4	based	base	VERB
hjic-1083	70	5	on	on	ADP
hjic-1083	70	6	the	the	DET
hjic-1083	70	7	calculation	calculation	NOUN
hjic-1083	70	8	of	of	ADP
hjic-1083	70	9	the	the	DET
hjic-1083	70	10	eigenvalues	eigenvalues	PROPN
hjic-1083	70	11	ali	ali	PROPN
hjic-1083	70	12	and	and	CCONJ
hjic-1083	70	13	the	the	DET
hjic-1083	70	14	eigenvectors	eigenvector	NOUN
hjic-1083	70	15	t~	t~	PROPN
hjic-1083	70	16	,	,	PUNCT
hjic-1083	70	17	of	of	ADP
hjic-1083	70	18	the	the	DET
hjic-1083	70	19	~xx	~xx	ADJ
hjic-1083	70	20	matrix	matrix	NOUN
hjic-1083	70	21	,	,	PUNCT
hjic-1083	70	22	where	where	SCONJ
hjic-1083	70	23	j	j	PROPN
hjic-1083	70	24	=	=	SYM
hjic-1083	70	25	l	l	PROPN
hjic-1083	70	26	,	,	PUNCT
hjic-1083	70	27	...	...	PUNCT
hjic-1083	70	28	,	,	PUNCT
hjic-1083	70	29	n.	n.	NOUN
hjic-1083	70	30	using	use	VERB
hjic-1083	70	31	the	the	DET
hjic-1083	70	32	eigenvalues	eigenvalue	NOUN
hjic-1083	70	33	and	and	CCONJ
hjic-1083	70	34	the	the	DET
hjic-1083	70	35	eigenvectors	eigenvector	NOUN
hjic-1083	70	36	the	the	DET
hjic-1083	70	37	following	follow	VERB
hjic-1083	70	38	fuzzy	fuzzy	ADJ
hjic-1083	70	39	model	model	NOUN
hjic-1083	70	40	that	that	PRON
hjic-1083	70	41	has	have	VERB
hjic-1083	70	42	no	no	DET
hjic-1083	70	43	correlation	correlation	NOUN
hjic-1083	70	44	in	in	ADP
hjic-1083	70	45	its	its	PRON
hjic-1083	70	46	transformed	transform	VERB
hjic-1083	70	47	input	input	NOUN
hjic-1083	70	48	space	space	NOUN
hjic-1083	70	49	can	can	AUX
hjic-1083	70	50	be	be	AUX
hjic-1083	70	51	obtained	obtain	VERB
hjic-1083	70	52	:	:	PUNCT
hjic-1083	70	53	r	r	X
hjic-1083	70	54	;	;	PUNCT
hjic-1083	70	55	:	:	PUNCT
hjic-1083	70	56	if	if	SCONJ
hjic-1083	70	57	(	(	PUNCT
hjic-1083	70	58	t~)t	t~)t	PROPN
hjic-1083	70	59	xk	xk	PROPN
hjic-1083	70	60	is	be	AUX
hjic-1083	70	61	a;,1	a;,1	NOUN
hjic-1083	70	62	and	and	CCONJ
hjic-1083	70	63	...	...	PUNCT
hjic-1083	70	64	and	and	CCONJ
hjic-1083	70	65	(	(	PUNCT
hjic-1083	70	66	t~)r	t~)r	PROPN
hjic-1083	70	67	xk	xk	PROPN
hjic-1083	70	68	is	be	AUX
hjic-1083	70	69	a;,n	a;,n	ADJ
hjic-1083	70	70	(	(	PUNCT
hjic-1083	70	71	13	13	NUM
hjic-1083	70	72	)	)	PUNCT
hjic-1083	71	1	then	then	ADV
hjic-1083	71	2	yk	yk	PROPN
hjic-1083	71	3	=	=	PROPN
hjic-1083	71	4	a	a	PROPN
hjic-1083	71	5	;	;	PUNCT
hjic-1083	71	6	xk	xk	PROPN
hjic-1083	71	7	+	+	CCONJ
hjic-1083	71	8	b1	b1	NOUN
hjic-1083	71	9	where	where	SCONJ
hjic-1083	71	10	the	the	DET
hjic-1083	71	11	gaussian	gaussian	ADJ
hjic-1083	71	12	membership	membership	NOUN
hjic-1083	71	13	functions	function	NOUN
hjic-1083	71	14	are	be	AUX
hjic-1083	71	15	defined	define	VERB
hjic-1083	71	16	as	as	ADP
hjic-1083	71	17	h	h	NOUN
hjic-1083	71	18	_	_	PUNCT
hjic-1083	71	19	(	(	PUNCT
hjic-1083	71	20	i	i	NOUN
hjic-1083	71	21	)	)	PUNCT
hjic-1083	71	22	t	t	NOUN
hjic-1083	72	1	_	_	PUNCT
hjic-1083	73	1	(	(	PUNCT
hjic-1083	73	2	i	i	PRON
hjic-1083	73	3	t	t	X
hjic-1083	73	4	x	x	PUNCT
hjic-1083	74	1	d	d	NOUN
hjic-1083	74	2	-2	-2	NOUN
hjic-1083	75	1	_	_	PUNCT
hjic-1083	75	2	(	(	PUNCT
hjic-1083	75	3	11	11	NUM
hjic-1083	75	4	)	)	SYM
hjic-1083	75	5	2	2	NUM
hjic-1083	75	6	were	be	AUX
hjic-1083	75	7	x	x	X
hjic-1083	75	8	...	...	PUNCT
hjic-1083	76	1	t.	t.	NOUN
hjic-1083	76	2	x	x	PUNCT
hjic-1083	76	3	..	..	PUNCT
hjic-1083	76	4	,	,	PUNCT
hjic-1083	76	5	v.	v.	ADP
hjic-1083	76	6	,t	,t	PUNCT
hjic-1083	76	7	.	.	PUNCT
hjic-1083	76	8	)	)	PUNCT
hjic-1083	77	1	v.	v.	ADP
hjic-1083	77	2	an	an	DET
hjic-1083	77	3	0	0	NUM
hjic-1083	77	4	'	'	PUNCT
hjic-1083	77	5	;	;	PUNCT
hjic-1083	77	6	1	1	X
hjic-1083	77	7	·	·	PUNCT
hjic-1083	77	8	a	a	DET
hjic-1083	77	9	1	1	NUM
hjic-1083	77	10	·	·	PUNCT
hjic-1083	77	11	}	}	PUNCT
hjic-1083	77	12	.	.	PUNCT
hjic-1083	77	13	"	"	PUNCT
hjic-1083	78	1	j	j	PROPN
hjic-1083	78	2	"	"	PUNCT
hjic-1083	78	3	l	l	PROPN
hjic-1083	78	4	,	,	PUNCT
hjic-1083	78	5	j	j	PROPN
hjic-1083	78	6	j	j	PROPN
hjic-1083	78	7	l	l	PROPN
hjic-1083	78	8	,	,	PUNCT
hjic-1083	78	9	denote	denote	VERB
hjic-1083	78	10	the	the	DET
hjic-1083	78	11	transformed	transform	VERB
hjic-1083	78	12	input	input	NOUN
hjic-1083	78	13	variable	variable	NOUN
hjic-1083	78	14	,	,	PUNCT
hjic-1083	78	15	the	the	DET
hjic-1083	78	16	cluster	cluster	NOUN
hjic-1083	78	17	center	center	NOUN
hjic-1083	78	18	and	and	CCONJ
hjic-1083	78	19	variance	variance	NOUN
hjic-1083	78	20	,	,	PUNCT
hjic-1083	78	21	respectively	respectively	ADV
hjic-1083	78	22	.	.	PUNCT
hjic-1083	79	1	the	the	DET
hjic-1083	79	2	aim	aim	NOUN
hjic-1083	79	3	of	of	ADP
hjic-1083	79	4	the	the	DET
hjic-1083	79	5	remaining	remain	VERB
hjic-1083	79	6	part	part	NOUN
hjic-1083	79	7	of	of	ADP
hjic-1083	79	8	the	the	DET
hjic-1083	79	9	paper	paper	NOUN
hjic-1083	79	10	is	be	AUX
hjic-1083	79	11	to	to	PART
hjic-1083	79	12	propose	propose	VERB
hjic-1083	79	13	a	a	DET
hjic-1083	79	14	new	new	ADJ
hjic-1083	79	15	identification	identification	NOUN
hjic-1083	79	16	technique	technique	NOUN
hjic-1083	79	17	for	for	ADP
hjic-1083	79	18	the	the	DET
hjic-1083	79	19	identification	identification	NOUN
hjic-1083	79	20	of	of	ADP
hjic-1083	79	21	the	the	DET
hjic-1083	79	22	model	model	NOUN
hjic-1083	79	23	presented	present	VERB
hjic-1083	79	24	above	above	ADV
hjic-1083	79	25	.	.	PUNCT
hjic-1083	80	1	131	131	NUM
hjic-1083	80	2	em	em	PRON
hjic-1083	80	3	algorithm	algorithm	NOUN
hjic-1083	80	4	for	for	ADP
hjic-1083	80	5	identification	identification	NOUN
hjic-1083	80	6	of	of	ADP
hjic-1083	80	7	mixture	mixture	NOUN
hjic-1083	80	8	of	of	ADP
hjic-1083	80	9	gaussians	gaussian	NOUN
hjic-1083	80	10	model	model	VERB
hjic-1083	80	11	the	the	DET
hjic-1083	80	12	expectation	expectation	NOUN
hjic-1083	80	13	maximization	maximization	NOUN
hjic-1083	80	14	(	(	PUNCT
hjic-1083	80	15	em	em	PRON
hjic-1083	80	16	)	)	PUNCT
hjic-1083	80	17	algorithm	algorithm	NOUN
hjic-1083	80	18	is	be	AUX
hjic-1083	80	19	an	an	DET
hjic-1083	80	20	iterative	iterative	NOUN
hjic-1083	80	21	algorithm	algorithm	NOUN
hjic-1083	80	22	for	for	ADP
hjic-1083	80	23	the	the	DET
hjic-1083	80	24	computation	computation	NOUN
hjic-1083	80	25	of	of	ADP
hjic-1083	80	26	maximum	maximum	ADJ
hjic-1083	80	27	likelihood	likelihood	NOUN
hjic-1083	80	28	parameter	parameter	NOUN
hjic-1083	80	29	estimates	estimate	NOUN
hjic-1083	80	30	when	when	SCONJ
hjic-1083	80	31	the	the	DET
hjic-1083	80	32	observations	observation	NOUN
hjic-1083	80	33	can	can	AUX
hjic-1083	80	34	be	be	AUX
hjic-1083	80	35	viewed	view	VERB
hjic-1083	80	36	as	as	ADP
hjic-1083	80	37	incomplete	incomplete	ADJ
hjic-1083	80	38	data	datum	NOUN
hjic-1083	80	39	.	.	PUNCT
hjic-1083	81	1	the	the	DET
hjic-1083	81	2	em	em	PROPN
hjic-1083	81	3	algorithm	algorithm	NOUN
hjic-1083	81	4	is	be	AUX
hjic-1083	81	5	widely	widely	ADV
hjic-1083	81	6	used	use	VERB
hjic-1083	81	7	for	for	ADP
hjic-1083	81	8	parameter	parameter	NOUN
hjic-1083	81	9	estimation	estimation	NOUN
hjic-1083	81	10	of	of	ADP
hjic-1083	81	11	the	the	DET
hjic-1083	81	12	mixture	mixture	NOUN
hjic-1083	81	13	of	of	ADP
hjic-1083	81	14	models	model	NOUN
hjic-1083	81	15	,	,	PUNCT
hjic-1083	81	16	in	in	ADP
hjic-1083	81	17	particular	particular	ADJ
hjic-1083	81	18	the	the	DET
hjic-1083	81	19	mixture	mixture	NOUN
hjic-1083	81	20	of	of	ADP
hjic-1083	81	21	gaussians	gaussians	PROPN
hjic-1083	81	22	model	model	NOUN
hjic-1083	81	23	[	[	X
hjic-1083	81	24	11	11	NUM
hjic-1083	81	25	]	]	PUNCT
hjic-1083	81	26	.	.	PUNCT
hjic-1083	82	1	the	the	DET
hjic-1083	82	2	basics	basic	NOUN
hjic-1083	82	3	of	of	ADP
hjic-1083	82	4	em	em	PRON
hjic-1083	82	5	are	be	AUX
hjic-1083	82	6	the	the	DET
hjic-1083	82	7	following	following	NOUN
hjic-1083	82	8	.	.	PUNCT
hjic-1083	83	1	suppose	suppose	VERB
hjic-1083	83	2	we	we	PRON
hjic-1083	83	3	know	know	VERB
hjic-1083	83	4	the	the	DET
hjic-1083	83	5	observed	observed	ADJ
hjic-1083	83	6	values	value	NOUN
hjic-1083	83	7	of	of	ADP
hjic-1083	83	8	a	a	DET
hjic-1083	83	9	random	random	ADJ
hjic-1083	83	10	variable	variable	NOUN
hjic-1083	83	11	z	z	NOUN
hjic-1083	83	12	and	and	CCONJ
hjic-1083	83	13	we	we	PRON
hjic-1083	83	14	wish	wish	VERB
hjic-1083	83	15	to	to	PART
hjic-1083	83	16	model	model	VERB
hjic-1083	83	17	the	the	DET
hjic-1083	83	18	density	density	NOUN
hjic-1083	83	19	of	of	ADP
hjic-1083	83	20	z	z	NOUN
hjic-1083	83	21	using	use	VERB
hjic-1083	83	22	a	a	DET
hjic-1083	83	23	model	model	NOUN
hjic-1083	83	24	parameterized	parameterize	VERB
hjic-1083	83	25	by	by	ADP
hjic-1083	83	26	rj	rj	PROPN
hjic-1083	83	27	.	.	PUNCT
hjic-1083	84	1	each	each	DET
hjic-1083	84	2	observation	observation	NOUN
hjic-1083	84	3	consists	consist	VERB
hjic-1083	84	4	of	of	ADP
hjic-1083	84	5	n	n	PROPN
hjic-1083	84	6	+	+	CCONJ
hjic-1083	84	7	1	1	NUM
hjic-1083	84	8	measured	measured	ADJ
hjic-1083	84	9	variables	variable	NOUN
hjic-1083	84	10	,	,	PUNCT
hjic-1083	84	11	grouped	group	VERB
hjic-1083	84	12	into	into	ADP
hjic-1083	84	13	an	an	DET
hjic-1083	84	14	n	n	PRON
hjic-1083	84	15	+	+	ADJ
hjic-1083	84	16	!	!	PUNCT
hjic-1083	84	17	-dimensional	-dimensional	ADJ
hjic-1083	84	18	column	column	NOUN
hjic-1083	84	19	vector	vector	NOUN
hjic-1083	85	1	z	z	NOUN
hjic-1083	85	2	k	k	PROPN
hjic-1083	86	1	=	=	PUNCT
hjic-1083	87	1	[	[	X
hjic-1083	87	2	zl	zl	X
hjic-1083	87	3	,	,	PUNCT
hjic-1083	87	4	k	k	NOUN
hjic-1083	87	5	'	'	PUNCT
hjic-1083	87	6	...	...	PUNCT
hjic-1083	87	7	'	'	PUNCT
hjic-1083	87	8	zn+l	zn+l	NOUN
hjic-1083	87	9	,	,	PUNCT
hjic-1083	87	10	k	k	NOUN
hjic-1083	87	11	r	r	NOUN
hjic-1083	87	12	.	.	PUNCT
hjic-1083	88	1	a	a	DET
hjic-1083	88	2	set	set	NOUN
hjic-1083	88	3	of	of	ADP
hjic-1083	88	4	n	n	PRON
hjic-1083	88	5	observations	observation	NOUN
hjic-1083	88	6	is	be	AUX
hjic-1083	88	7	denoted	denote	VERB
hjic-1083	88	8	by	by	ADP
hjic-1083	88	9	z	z	PROPN
hjic-1083	88	10	and	and	CCONJ
hjic-1083	88	11	represented	represent	VERB
hjic-1083	88	12	as	as	ADP
hjic-1083	88	13	a	a	DET
hjic-1083	88	14	matrix	matrix	NOUN
hjic-1083	88	15	:	:	PUNCT
hjic-1083	88	16	[	[	PUNCT
hjic-1083	88	17	z	z	NOUN
hjic-1083	88	18	,	,	PUNCT
hjic-1083	88	19	,	,	PUNCT
hjic-1083	88	20	,	,	PUNCT
hjic-1083	88	21	zr	zr	PROPN
hjic-1083	88	22	,	,	PUNCT
hjic-1083	88	23	z	z	NOUN
hjic-1083	88	24	z,,n	z,,n	NUM
hjic-1083	88	25	l	l	NOUN
hjic-1083	88	26	z	z	NOUN
hjic-1083	88	27	=	=	SYM
hjic-1083	88	28	zz	zz	PROPN
hjic-1083	88	29	,	,	PUNCT
hjic-1083	88	30	l	l	PROPN
hjic-1083	88	31	zz	zz	PROPN
hjic-1083	88	32	,	,	PUNCT
hjic-1083	88	33	z	z	PROPN
hjic-1083	88	34	zz	zz	PROPN
hjic-1083	88	35	,	,	PUNCT
hjic-1083	88	36	n	n	PROPN
hjic-1083	88	37	(	(	PUNCT
hjic-1083	88	38	15	15	NUM
hjic-1083	88	39	)	)	PUNCT
hjic-1083	88	40	zn	zn	NOUN
hjic-1083	88	41	:	:	PUNCT
hjic-1083	88	42	i	i	PRON
hjic-1083	88	43	,	,	PUNCT
hjic-1083	88	44	l	l	PROPN
hjic-1083	88	45	zn+l,2	zn+l,2	PROPN
hjic-1083	89	1	zn:!.n	zn:!.n	NUM
hjic-1083	89	2	as	as	SCONJ
hjic-1083	89	3	the	the	DET
hjic-1083	89	4	identification	identification	NOUN
hjic-1083	89	5	is	be	AUX
hjic-1083	89	6	performed	perform	VERB
hjic-1083	89	7	on	on	ADP
hjic-1083	89	8	the	the	DET
hjic-1083	89	9	available	available	ADJ
hjic-1083	89	10	identification	identification	NOUN
hjic-1083	89	11	data	datum	NOUN
hjic-1083	89	12	,	,	PUNCT
hjic-1083	89	13	z	z	PROPN
hjic-1083	89	14	is	be	AUX
hjic-1083	89	15	divided	divide	VERB
hjic-1083	89	16	into	into	ADP
hjic-1083	89	17	a	a	DET
hjic-1083	89	18	regression	regression	NOUN
hjic-1083	89	19	data	data	NOUN
hjic-1083	89	20	matrix	matrix	NOUN
hjic-1083	89	21	x	x	PUNCT
hjic-1083	89	22	and	and	CCONJ
hjic-1083	89	23	a	a	DET
hjic-1083	89	24	regression	regression	NOUN
hjic-1083	89	25	vector	vector	NOUN
hjic-1083	89	26	y	y	PROPN
hjic-1083	89	27	(	(	PUNCT
hjic-1083	89	28	16	16	NUM
hjic-1083	89	29	)	)	PUNCT
hjic-1083	89	30	(	(	PUNCT
hjic-1083	89	31	17	17	NUM
hjic-1083	89	32	)	)	PUNCT
hjic-1083	89	33	in	in	ADP
hjic-1083	89	34	the	the	DET
hjic-1083	89	35	pattern	pattern	NOUN
hjic-1083	89	36	recognition	recognition	NOUN
hjic-1083	89	37	terminology	terminology	NOUN
hjic-1083	89	38	,	,	PUNCT
hjic-1083	89	39	the	the	DET
hjic-1083	89	40	columns	column	NOUN
hjic-1083	89	41	of	of	ADP
hjic-1083	89	42	z	z	PROPN
hjic-1083	89	43	called	call	VERB
hjic-1083	89	44	patterns	pattern	NOUN
hjic-1083	89	45	or	or	CCONJ
hjic-1083	89	46	objects	object	NOUN
hjic-1083	89	47	,	,	PUNCT
hjic-1083	89	48	the	the	DET
hjic-1083	89	49	rows	row	NOUN
hjic-1083	89	50	are	be	AUX
hjic-1083	89	51	called	call	VERB
hjic-1083	89	52	the	the	DET
hjic-1083	89	53	features	feature	NOUN
hjic-1083	89	54	or	or	CCONJ
hjic-1083	89	55	attributes	attribute	NOUN
hjic-1083	89	56	,	,	PUNCT
hjic-1083	89	57	and	and	CCONJ
hjic-1083	89	58	z	z	NOUN
hjic-1083	89	59	is	be	AUX
hjic-1083	89	60	called	call	VERB
hjic-1083	89	61	the	the	DET
hjic-1083	89	62	pattern	pattern	NOUN
hjic-1083	89	63	matrix	matrix	NOUN
hjic-1083	89	64	.	.	PUNCT
hjic-1083	90	1	em	em	PRON
hjic-1083	90	2	obtains	obtain	VERB
hjic-1083	90	3	parameter	parameter	NOUN
hjic-1083	90	4	estimates	estimate	NOUN
hjic-1083	90	5	fj	fj	X
hjic-1083	90	6	which	which	PRON
hjic-1083	90	7	maximize	maximize	VERB
hjic-1083	90	8	the	the	DET
hjic-1083	90	9	likelihood	likelihood	NOUN
hjic-1083	90	10	l(rj	l(rj	NOUN
hjic-1083	90	11	)	)	PUNCT
hjic-1083	91	1	=	=	SYM
hjic-1083	91	2	p(z~	p(z~	PROPN
hjic-1083	91	3	)	)	PUNCT
hjic-1083	91	4	of	of	ADP
hjic-1083	91	5	the	the	DET
hjic-1083	91	6	data	datum	NOUN
hjic-1083	91	7	.	.	PUNCT
hjic-1083	92	1	the	the	DET
hjic-1083	92	2	em	em	PRON
hjic-1083	92	3	assumes	assume	VERB
hjic-1083	92	4	that	that	SCONJ
hjic-1083	92	5	this	this	DET
hjic-1083	92	6	estimation	estimation	NOUN
hjic-1083	92	7	is	be	AUX
hjic-1083	92	8	intractable	intractable	ADJ
hjic-1083	92	9	and	and	CCONJ
hjic-1083	92	10	the	the	DET
hjic-1083	92	11	values	value	NOUN
hjic-1083	92	12	of	of	ADP
hjic-1083	92	13	a	a	DET
hjic-1083	92	14	missing	missing	ADJ
hjic-1083	92	15	or	or	CCONJ
hjic-1083	92	16	hidden	hide	VERB
hjic-1083	92	17	random	random	ADJ
hjic-1083	92	18	variable	variable	ADJ
hjic-1083	92	19	h	h	NOUN
hjic-1083	92	20	would	would	AUX
hjic-1083	92	21	make	make	VERB
hjic-1083	92	22	the	the	DET
hjic-1083	92	23	problem	problem	NOUN
hjic-1083	92	24	more	more	ADV
hjic-1083	92	25	tractable	tractable	ADJ
hjic-1083	92	26	.	.	PUNCT
hjic-1083	93	1	let	let	AUX
hjic-1083	93	2	p(z	p(z	VERB
hjic-1083	93	3	,	,	PUNCT
hjic-1083	93	4	h~	h~	PROPN
hjic-1083	93	5	)	)	PUNCT
hjic-1083	93	6	denote	denote	VERB
hjic-1083	93	7	the	the	DET
hjic-1083	93	8	joint	joint	ADJ
hjic-1083	93	9	probability	probability	NOUN
hjic-1083	93	10	of	of	ADP
hjic-1083	93	11	z	z	NOUN
hjic-1083	93	12	and	and	CCONJ
hjic-1083	93	13	h	h	PROPN
hjic-1083	93	14	parameterized	parameterized	ADJ
hjic-1083	93	15	by	by	ADP
hjic-1083	93	16	11	11	NUM
hjic-1083	93	17	•	•	NOUN
hjic-1083	93	18	it	it	PRON
hjic-1083	93	19	is	be	AUX
hjic-1083	93	20	assumed	assume	VERB
hjic-1083	93	21	that	that	SCONJ
hjic-1083	93	22	z	z	PROPN
hjic-1083	93	23	and	and	CCONJ
hjic-1083	93	24	h	h	NOUN
hjic-1083	93	25	are	be	AUX
hjic-1083	93	26	such	such	ADJ
hjic-1083	93	27	that	that	SCONJ
hjic-1083	93	28	maximizing	maximize	VERB
hjic-1083	93	29	the	the	DET
hjic-1083	93	30	complete	complete	ADJ
hjic-1083	93	31	data	datum	NOUN
hjic-1083	93	32	likelihood	likelihood	NOUN
hjic-1083	93	33	lr(rj	lr(rj	NOUN
hjic-1083	93	34	)	)	PUNCT
hjic-1083	94	1	=	=	SYM
hjic-1083	94	2	p(z	p(z	NOUN
hjic-1083	94	3	,	,	PUNCT
hjic-1083	94	4	hjr	hjr	NOUN
hjic-1083	94	5	]	]	PUNCT
hjic-1083	94	6	)	)	PUNCT
hjic-1083	94	7	is	be	AUX
hjic-1083	94	8	more	more	ADV
hjic-1083	94	9	tractable	tractable	ADJ
hjic-1083	94	10	than	than	ADP
hjic-1083	94	11	maximizing	maximize	VERB
hjic-1083	94	12	l(q	l(q	PROPN
hjic-1083	94	13	)	)	PUNCT
hjic-1083	94	14	.	.	PUNCT
hjic-1083	95	1	however	however	ADV
hjic-1083	95	2	,	,	PUNCT
hjic-1083	95	3	the	the	DET
hjic-1083	95	4	values	value	NOUN
hjic-1083	95	5	of	of	ADP
hjic-1083	95	6	h	h	NOUN
hjic-1083	95	7	are	be	AUX
hjic-1083	95	8	not	not	PART
hjic-1083	95	9	known	know	VERB
hjic-1083	95	10	.	.	PUNCT
hjic-1083	96	1	the	the	DET
hjic-1083	96	2	em	em	PROPN
hjic-1083	96	3	algorithm	algorithm	NOUN
hjic-1083	96	4	tackles	tackle	NOUN
hjic-1083	96	5	this	this	DET
hjic-1083	96	6	problem	problem	NOUN
hjic-1083	96	7	by	by	ADP
hjic-1083	96	8	iteratively	iteratively	ADV
hjic-1083	96	9	generating	generate	VERB
hjic-1083	96	10	a	a	DET
hjic-1083	96	11	probability	probability	NOUN
hjic-1083	96	12	over	over	ADP
hjic-1083	96	13	~he	~he	NOUN
hjic-1083	96	14	values	value	NOUN
hjic-1083	96	15	h	h	NOUN
hjic-1083	96	16	and	and	CCONJ
hjic-1083	96	17	estimating	estimate	VERB
hjic-1083	96	18	the	the	DET
hjic-1083	96	19	parameters	parameter	NOUN
hjic-1083	96	20	whtch	whtch	VERB
hjic-1083	96	21	maximize	maximize	VERB
hjic-1083	96	22	the	the	DET
hjic-1083	96	23	expected	expect	VERB
hjic-1083	96	24	value	value	NOUN
hjic-1083	96	25	of	of	ADP
hjic-1083	96	26	l	l	NOUN
hjic-1083	96	27	<	<	X
hjic-1083	96	28	vj	vj	PROPN
hjic-1083	96	29	)	)	PUNCT
hjic-1083	96	30	with	with	ADP
hjic-1083	96	31	respect	respect	NOUN
hjic-1083	96	32	to	to	AUX
hjic-1083	96	33	b.	b.	VERB
hjic-1083	96	34	the	the	DET
hjic-1083	96	35	mixture	mixture	NOUN
hjic-1083	96	36	of	of	ADP
hjic-1083	96	37	gaussians	gaussians	PROPN
hjic-1083	96	38	model	model	NOUN
hjic-1083	96	39	represents	represent	VERB
hjic-1083	96	40	the	the	DET
hjic-1083	96	41	p(z~	p(z~	PROPN
hjic-1083	96	42	)	)	PUNCT
hjic-1083	96	43	probability	probability	NOUN
hjic-1083	96	44	density	density	NOUN
hjic-1083	96	45	function	function	VERB
hjic-1083	97	1	that	that	SCONJ
hjic-1083	97	2	b	b	X
hjic-1083	97	3	e\panded	e\pande	VERB
hjic-1083	97	4	in	in	ADP
hjic-1083	97	5	a	a	DET
hjic-1083	97	6	sum	sum	NOUN
hjic-1083	97	7	over	over	ADP
hjic-1083	97	8	the	the	DET
hjic-1083	97	9	c	c	PROPN
hjic-1083	97	10	clusters	cluster	NOUN
hjic-1083	97	11	132	132	NUM
hjic-1083	97	12	c	c	NOUN
hjic-1083	97	13	c	c	NOUN
hjic-1083	97	14	p(z~	p(z~	PROPN
hjic-1083	97	15	)	)	PUNCT
hjic-1083	97	16	=	=	SYM
hjic-1083	97	17	l	l	NOUN
hjic-1083	97	18	p(z,1ji	p(z,1ji	PROPN
hjic-1083	97	19	)	)	PUNCT
hjic-1083	97	20	=	=	PUNCT
hjic-1083	97	21	lp	lp	ADP
hjic-1083	97	22	<	<	X
hjic-1083	97	23	zl1]j)p(1ji	zl1]j)p(1ji	NOUN
hjic-1083	97	24	)	)	PUNCT
hjic-1083	98	1	next	next	ADV
hjic-1083	98	2	we	we	PRON
hjic-1083	98	3	compute	compute	VERB
hjic-1083	98	4	the	the	DET
hjic-1083	98	5	remaining	remain	VERB
hjic-1083	98	6	parameters	parameter	NOUN
hjic-1083	98	7	of	of	ADP
hjic-1083	98	8	the	the	DET
hjic-1083	98	9	(	(	PUNCT
hjic-1083	98	10	18	18	NUM
hjic-1083	98	11	)	)	PUNCT
hjic-1083	98	12	cluster	cluster	NOUN
hjic-1083	98	13	,	,	PUNCT
hjic-1083	98	14	the	the	DET
hjic-1083	98	15	mean	mean	NOUN
hjic-1083	98	16	i	i	NOUN
hjic-1083	99	1	=	=	NOUN
hjic-1083	99	2	l	l	NOUN
hjic-1083	99	3	i	i	NOUN
hjic-1083	99	4	=	=	NOUN
hjic-1083	99	5	l	l	NOUN
hjic-1083	99	6	where	where	SCONJ
hjic-1083	99	7	1j	1j	NUM
hjic-1083	99	8	is	be	AUX
hjic-1083	99	9	the	the	DET
hjic-1083	99	10	set	set	NOUN
hjic-1083	99	11	of	of	ADP
hjic-1083	99	12	the	the	DET
hjic-1083	99	13	parameters	parameter	NOUN
hjic-1083	99	14	1j	1j	NUM
hjic-1083	99	15	=	=	SYM
hjic-1083	99	16	{	{	PUNCT
hjic-1083	99	17	1j;ii	1j;ii	NUM
hjic-1083	99	18	=	=	SYM
hjic-1083	99	19	l	l	PROPN
hjic-1083	99	20	,	,	PUNCT
hjic-1083	99	21	...	...	PUNCT
hjic-1083	99	22	,	,	PUNCT
hjic-1083	99	23	c	c	X
hjic-1083	99	24	}	}	PUNCT
hjic-1083	99	25	of	of	ADP
hjic-1083	99	26	the	the	DET
hjic-1083	99	27	model	model	NOUN
hjic-1083	99	28	and	and	CCONJ
hjic-1083	99	29	p(1j	p(1j	PRON
hjic-1083	99	30	;)	;)	NUM
hjic-1083	99	31	denotes	denote	VERB
hjic-1083	99	32	the	the	DET
hjic-1083	99	33	unconditioned	unconditioned	ADJ
hjic-1083	99	34	cluster	cluster	NOUN
hjic-1083	99	35	probabilities	probability	NOUN
hjic-1083	99	36	normalized	normalize	VERB
hjic-1083	99	37	to	to	PART
hjic-1083	99	38	satisfy	satisfy	VERB
hjic-1083	99	39	:	:	PUNCT
hjic-1083	99	40	l;=l	l;=l	PROPN
hjic-1083	99	41	p(1j	p(1j	NOUN
hjic-1083	99	42	;)	;)	PUNCT
hjic-1083	99	43	;	;	PUNCT
hjic-1083	99	44	:	:	PUNCT
hjic-1083	99	45	:	:	PUNCT
hjic-1083	99	46	:	:	PUNCT
hjic-1083	99	47	:	:	PUNCT
hjic-1083	99	48	1	1	X
hjic-1083	99	49	.	.	X
hjic-1083	99	50	the	the	DET
hjic-1083	99	51	p(zj1ji	p(zj1ji	NOUN
hjic-1083	99	52	)	)	PUNCT
hjic-1083	99	53	distribution	distribution	NOUN
hjic-1083	99	54	generated	generate	VERB
hjic-1083	99	55	by	by	ADP
hjic-1083	99	56	the	the	DET
hjic-1083	99	57	i	i	PROPN
hjic-1083	99	58	-th	-th	NOUN
hjic-1083	99	59	cluster	cluster	NOUN
hjic-1083	99	60	is	be	AUX
hjic-1083	99	61	represented	represent	VERB
hjic-1083	99	62	by	by	ADP
hjic-1083	99	63	gaussian	gaussian	NOUN
hjic-1083	99	64	like	like	ADP
hjic-1083	99	65	p(z~-	p(z~-	NUM
hjic-1083	99	66	)	)	PUNCT
hjic-1083	99	67	1	1	NUM
hjic-1083	99	68	exp(-.!.(z	exp(-.!.(z	PROPN
hjic-1083	99	69	-	-	PUNCT
hjic-1083	99	70	v.l	v.l	PROPN
hjic-1083	99	71	(	(	PUNCT
hjic-1083	99	72	f.f1	f.f1	ADJ
hjic-1083	99	73	(	(	PUNCT
hjic-1083	99	74	z	z	NOUN
hjic-1083	99	75	-	-	PUNCT
hjic-1083	99	76	v.	v.	NOUN
hjic-1083	99	77	)	)	PUNCT
hjic-1083	99	78	)	)	PUNCT
hjic-1083	100	1	(	(	PUNCT
hjic-1083	100	2	19	19	NUM
hjic-1083	100	3	)	)	PUNCT
hjic-1083	100	4	i	i	PRON
hjic-1083	100	5	(	(	PUNCT
hjic-1083	100	6	27c	27c	NUM
hjic-1083	100	7	ff	ff	NUM
hjic-1083	100	8	.jifj	.jifj	NOUN
hjic-1083	100	9	2	2	NUM
hjic-1083	100	10	l	l	NOUN
hjic-1083	101	1	i	i	NOUN
hjic-1083	101	2	l	l	NOUN
hjic-1083	101	3	where	where	SCONJ
hjic-1083	101	4	1j	1j	NUM
hjic-1083	101	5	;	;	PUNCT
hjic-1083	101	6	represents	represent	VERB
hjic-1083	101	7	the	the	DET
hjic-1083	101	8	parameters	parameter	NOUN
hjic-1083	101	9	of	of	ADP
hjic-1083	101	10	the	the	DET
hjic-1083	101	11	i	i	PROPN
hjic-1083	101	12	-th	-th	NOUN
hjic-1083	101	13	cluster	cluster	NOUN
hjic-1083	101	14	,	,	PUNCT
hjic-1083	101	15	1	1	NUM
hjic-1083	101	16	]	]	PUNCT
hjic-1083	101	17	;	;	PUNCT
hjic-1083	101	18	=	=	X
hjic-1083	101	19	{	{	PUNCT
hjic-1083	101	20	v;,fzli	v;,fzli	NOUN
hjic-1083	101	21	=	=	NOUN
hjic-1083	101	22	l	l	NOUN
hjic-1083	101	23	,	,	PUNCT
hjic-1083	101	24	...	...	PUNCT
hjic-1083	101	25	,	,	PUNCT
hjic-1083	101	26	c	c	X
hjic-1083	101	27	}	}	PUNCT
hjic-1083	101	28	.	.	PUNCT
hjic-1083	102	1	as	as	SCONJ
hjic-1083	102	2	each	each	DET
hjic-1083	102	3	data	data	NOUN
hjic-1083	102	4	point	point	NOUN
hjic-1083	102	5	zk	zk	PROPN
hjic-1083	102	6	is	be	AUX
hjic-1083	102	7	generated	generate	VERB
hjic-1083	102	8	by	by	ADP
hjic-1083	102	9	one	one	NUM
hjic-1083	102	10	and	and	CCONJ
hjic-1083	102	11	only	only	ADV
hjic-1083	102	12	one	one	NUM
hjic-1083	102	13	of	of	ADP
hjic-1083	102	14	the	the	DET
hjic-1083	102	15	component	component	NOUN
hjic-1083	102	16	gaussians	gaussian	NOUN
hjic-1083	102	17	,	,	PUNCT
hjic-1083	102	18	the	the	DET
hjic-1083	102	19	hidden	hide	VERB
hjic-1083	102	20	random	random	ADJ
hjic-1083	102	21	variable	variable	NOUN
hjic-1083	102	22	hk	hk	PROPN
hjic-1083	102	23	for	for	ADP
hjic-1083	102	24	the	the	DET
hjic-1083	102	25	em	em	PROPN
hjic-1083	102	26	algorithm	algorithm	NOUN
hjic-1083	102	27	it	it	PRON
hjic-1083	102	28	is	be	AUX
hjic-1083	102	29	the	the	DET
hjic-1083	102	30	label	label	NOUN
hjic-1083	102	31	of	of	ADP
hjic-1083	102	32	the	the	DET
hjic-1083	102	33	component	component	NOUN
hjic-1083	102	34	gaussian	gaussian	NOUN
hjic-1083	102	35	to	to	ADP
hjic-1083	102	36	which	which	PRON
hjic-1083	102	37	z	z	NOUN
hjic-1083	102	38	k	k	NOUN
hjic-1083	102	39	belongs	belong	VERB
hjic-1083	102	40	.	.	PUNCT
hjic-1083	103	1	based	base	VERB
hjic-1083	103	2	on	on	ADP
hjic-1083	103	3	this	this	DET
hjic-1083	103	4	assumption	assumption	NOUN
hjic-1083	103	5	,	,	PUNCT
hjic-1083	103	6	the	the	DET
hjic-1083	103	7	em	em	PROPN
hjic-1083	103	8	algorithm	algorithm	NOUN
hjic-1083	103	9	for	for	ADP
hjic-1083	103	10	maximum	maximum	ADJ
hjic-1083	103	11	likelihood	likelihood	NOUN
hjic-1083	103	12	parameter	parameter	NOUN
hjic-1083	103	13	estimation	estimation	NOUN
hjic-1083	103	14	is	be	AUX
hjic-1083	103	15	the	the	DET
hjic-1083	103	16	following	following	NOUN
hjic-1083	103	17	.	.	PUNCT
hjic-1083	104	1	the	the	DET
hjic-1083	104	2	algorithm	algorithm	NOUN
hjic-1083	104	3	starts	start	VERB
hjic-1083	104	4	with	with	ADP
hjic-1083	104	5	an	an	DET
hjic-1083	104	6	initial	initial	ADJ
hjic-1083	104	7	guess	guess	NOUN
hjic-1083	104	8	11'0	11'0	NOUN
hjic-1083	104	9	'	'	PUNCT
hjic-1083	104	10	of	of	ADP
hjic-1083	104	11	the	the	DET
hjic-1083	104	12	parameters	parameter	NOUN
hjic-1083	104	13	and	and	CCONJ
hjic-1083	104	14	repeatedly	repeatedly	ADV
hjic-1083	104	15	applies	apply	VERB
hjic-1083	104	16	the	the	DET
hjic-1083	104	17	following	follow	VERB
hjic-1083	104	18	two	two	NUM
hjic-1083	104	19	steps	step	NOUN
hjic-1083	104	20	to	to	PART
hjic-1083	104	21	generate	generate	VERB
hjic-1083	104	22	successively	successively	ADV
hjic-1083	104	23	better	well	ADJ
hjic-1083	104	24	parameter	parameter	NOUN
hjic-1083	104	25	estimates	estimate	NOUN
hjic-1083	104	26	:	:	PUNCT
hjic-1083	104	27	initialization	initialization	NOUN
hjic-1083	104	28	:	:	PUNCT
hjic-1083	104	29	initialize	initialize	VERB
hjic-1083	104	30	the	the	DET
hjic-1083	104	31	means	mean	NOUN
hjic-1083	104	32	v	v	NOUN
hjic-1083	104	33	;	;	PUNCT
hjic-1083	104	34	to	to	PART
hjic-1083	104	35	randomly	randomly	ADV
hjic-1083	104	36	picked	pick	VERB
hjic-1083	104	37	data	datum	NOUN
hjic-1083	104	38	points	point	NOUN
hjic-1083	104	39	from	from	ADP
hjic-1083	104	40	z	z	PROPN
hjic-1083	104	41	and	and	CCONJ
hjic-1083	104	42	the	the	DET
hjic-1083	104	43	covariance	covariance	NOUN
hjic-1083	104	44	matrices	matrice	VERB
hjic-1083	104	45	fj	fj	PROPN
hjic-1083	104	46	to	to	ADP
hjic-1083	104	47	unit	unit	NOUN
hjic-1083	104	48	matrices	matrix	NOUN
hjic-1083	104	49	.	.	PUNCT
hjic-1083	104	50	'	'	PUNCT
hjic-1083	105	1	set	set	VERB
hjic-1083	105	2	p(1ji	p(1ji	ADJ
hjic-1083	105	3	)	)	PUNCT
hjic-1083	105	4	=	=	SYM
hjic-1083	105	5	1/	1/	NUM
hjic-1083	105	6	c	c	NOUN
hjic-1083	105	7	for	for	ADP
hjic-1083	105	8	all	all	DET
hjic-1083	105	9	i.	i.	NOUN
hjic-1083	105	10	expectation	expectation	NOUN
hjic-1083	105	11	(	(	PUNCT
hjic-1083	105	12	e	e	NOUN
hjic-1083	105	13	)	)	PUNCT
hjic-1083	105	14	step	step	NOUN
hjic-1083	105	15	:	:	PUNCT
hjic-1083	105	16	in	in	ADP
hjic-1083	105	17	the	the	DET
hjic-1083	105	18	e	e	NOUN
hjic-1083	105	19	-	-	NOUN
hjic-1083	105	20	step	step	NOUN
hjic-1083	105	21	we	we	PRON
hjic-1083	105	22	assume	assume	VERB
hjic-1083	105	23	the	the	DET
hjic-1083	105	24	current	current	ADJ
hjic-1083	105	25	cluster	cluster	NOUN
hjic-1083	105	26	parameter	parameter	NOUN
hjic-1083	105	27	to	to	PART
hjic-1083	105	28	be	be	AUX
hjic-1083	105	29	correct	correct	ADJ
hjic-1083	105	30	and	and	CCONJ
hjic-1083	105	31	evaluate	evaluate	VERB
hjic-1083	105	32	the	the	DET
hjic-1083	105	33	posterior	posterior	ADJ
hjic-1083	105	34	probabilities	probability	NOUN
hjic-1083	105	35	that	that	PRON
hjic-1083	105	36	relate	relate	VERB
hjic-1083	105	37	each	each	DET
hjic-1083	105	38	data	data	NOUN
hjic-1083	105	39	point	point	NOUN
hjic-1083	105	40	in	in	ADP
hjic-1083	105	41	the	the	DET
hjic-1083	105	42	conditional	conditional	ADJ
hjic-1083	105	43	probability	probability	NOUN
hjic-1083	105	44	p	p	X
hjic-1083	105	45	(	(	PUNCT
hjic-1083	105	46	rjtjz	rjtjz	PROPN
hjic-1083	105	47	)	)	PUNCT
hjic-1083	105	48	.	.	PUNCT
hjic-1083	106	1	these	these	DET
hjic-1083	106	2	posterior	posterior	ADJ
hjic-1083	106	3	probabilities	probability	NOUN
hjic-1083	106	4	can	can	AUX
hjic-1083	106	5	be	be	AUX
hjic-1083	106	6	interpreted	interpret	VERB
hjic-1083	106	7	as	as	ADP
hjic-1083	106	8	the	the	DET
hjic-1083	106	9	probability	probability	NOUN
hjic-1083	106	10	that	that	SCONJ
hjic-1083	106	11	a	a	DET
hjic-1083	106	12	particular	particular	ADJ
hjic-1083	106	13	piece	piece	NOUN
hjic-1083	106	14	of	of	ADP
hjic-1083	106	15	data	datum	NOUN
hjic-1083	106	16	was	be	AUX
hjic-1083	106	17	generated	generate	VERB
hjic-1083	106	18	by	by	ADP
hjic-1083	106	19	a	a	DET
hjic-1083	106	20	particular	particular	ADJ
hjic-1083	106	21	cluster	cluster	NOUN
hjic-1083	106	22	.	.	PUNCT
hjic-1083	107	1	by	by	ADP
hjic-1083	107	2	using	use	VERB
hjic-1083	107	3	bayes	bayes	PROPN
hjic-1083	107	4	theorem	theorem	VERB
hjic-1083	107	5	,	,	PUNCT
hjic-1083	107	6	(	(	PUNCT
hjic-1083	107	7	.	.	PUNCT
hjic-1083	107	8	·	·	PUNCT
hjic-1083	107	9	lz>=	lz>=	VERB
hjic-1083	107	10	p(zj1j	p(zj1j	NOUN
hjic-1083	107	11	;)	;)	PUNCT
hjic-1083	107	12	p(1j	p(1j	ADP
hjic-1083	107	13	;)	;)	PUNCT
hjic-1083	107	14	p	p	NOUN
hjic-1083	107	15	y/	y/	NOUN
hjic-1083	107	16	,	,	PUNCT
hjic-1083	107	17	'	'	PUNCT
hjic-1083	107	18	(	(	PUNCT
hjic-1083	107	19	)	)	PUNCT
hjic-1083	107	20	p	p	NOUN
hjic-1083	107	21	z	z	NOUN
hjic-1083	107	22	{	{	PUNCT
hjic-1083	107	23	21	21	NUM
hjic-1083	107	24	)	)	PUNCT
hjic-1083	107	25	maximization	maximization	NOUN
hjic-1083	107	26	(	(	PUNCT
hjic-1083	107	27	m	m	NOUN
hjic-1083	107	28	)	)	PUNCT
hjic-1083	107	29	step	step	NOUN
hjic-1083	107	30	:	:	PUNCT
hjic-1083	107	31	in	in	ADP
hjic-1083	107	32	the	the	DET
hjic-1083	107	33	m	m	NOUN
hjic-1083	107	34	-	-	NOUN
hjic-1083	107	35	step	step	NOUN
hjic-1083	107	36	we	we	PRON
hjic-1083	107	37	assume	assume	VERB
hjic-1083	107	38	the	the	DET
hjic-1083	107	39	current	current	ADJ
hjic-1083	107	40	data	data	NOUN
hjic-1083	107	41	distribution	distribution	NOUN
hjic-1083	107	42	to	to	PART
hjic-1083	107	43	be	be	AUX
hjic-1083	107	44	correct	correct	ADJ
hjic-1083	107	45	and	and	CCONJ
hjic-1083	107	46	find	find	VERB
hjic-1083	107	47	the	the	DET
hjic-1083	107	48	parameters	parameter	NOUN
hjic-1083	107	49	of	of	ADP
hjic-1083	107	50	the	the	DET
hjic-1083	107	51	clusters	cluster	NOUN
hjic-1083	107	52	that	that	PRON
hjic-1083	107	53	maximize	maximize	VERB
hjic-1083	107	54	the	the	DET
hjic-1083	107	55	likelihood	likelihood	NOUN
hjic-1083	107	56	of	of	ADP
hjic-1083	107	57	the	the	DET
hjic-1083	107	58	data	datum	NOUN
hjic-1083	107	59	.	.	PUNCT
hjic-1083	108	1	according	accord	VERB
hjic-1083	108	2	to	to	ADP
hjic-1083	108	3	this~	this~	PROPN
hjic-1083	108	4	the	the	DET
hjic-1083	108	5	unconditional	unconditional	ADJ
hjic-1083	108	6	probabilities	probability	NOUN
hjic-1083	108	7	are	be	AUX
hjic-1083	108	8	calculated	calculate	VERB
hjic-1083	108	9	as	as	ADP
hjic-1083	108	10	f	f	PROPN
hjic-1083	108	11	f	f	PROPN
hjic-1083	108	12	p	p	X
hjic-1083	108	13	(	(	PUNCT
hjic-1083	108	14	1jijz	1jijz	NUM
hjic-1083	108	15	)	)	PUNCT
hjic-1083	108	16	v.	v.	NOUN
hjic-1083	109	1	=	=	PUNCT
hjic-1083	109	2	zp(z~-)dz=	zp(z~-)dz=	PROPN
hjic-1083	109	3	z	z	PROPN
hjic-1083	109	4	--	--	PUNCT
hjic-1083	109	5	p(z)dz	p(z)dz	ADP
hjic-1083	109	6	i	i	PRON
hjic-1083	109	7	i	i	PRON
hjic-1083	109	8	p(1ji	p(1ji	ADV
hjic-1083	109	9	)	)	PUNCT
hjic-1083	109	10	(	(	PUNCT
hjic-1083	109	11	23	23	NUM
hjic-1083	109	12	)	)	PUNCT
hjic-1083	109	13	and	and	CCONJ
hjic-1083	109	14	in	in	ADP
hjic-1083	109	15	a	a	DET
hjic-1083	109	16	similar	similar	ADJ
hjic-1083	109	17	way	way	NOUN
hjic-1083	109	18	the	the	DET
hjic-1083	109	19	cluster	cluster	NOUN
hjic-1083	109	20	weighted	weight	VERB
hjic-1083	109	21	covariance	covariance	NOUN
hjic-1083	109	22	matrices	matrix	NOUN
hjic-1083	109	23	n	n	PRON
hjic-1083	109	24	l(zk	l(zk	PROPN
hjic-1083	109	25	-v)(zk	-v)(zk	PROPN
hjic-1083	109	26	-v;l	-v;l	PROPN
hjic-1083	109	27	p(1jijzk	p(1jijzk	NOUN
hjic-1083	109	28	)	)	PUNCT
hjic-1083	110	1	k	k	X
hjic-1083	110	2	=	=	NOUN
hjic-1083	110	3	l	l	X
hjic-1083	110	4	(	(	PUNCT
hjic-1083	110	5	24	24	NUM
hjic-1083	110	6	)	)	PUNCT
hjic-1083	110	7	in	in	ADP
hjic-1083	110	8	the	the	DET
hjic-1083	110	9	above	above	ADJ
hjic-1083	110	10	it	it	PRON
hjic-1083	110	11	has	have	AUX
hjic-1083	110	12	been	be	AUX
hjic-1083	110	13	shown	show	VERB
hjic-1083	110	14	that	that	SCONJ
hjic-1083	110	15	the	the	DET
hjic-1083	110	16	gaussian	gaussian	ADJ
hjic-1083	110	17	mixture	mixture	NOUN
hjic-1083	110	18	model	model	NOUN
hjic-1083	110	19	models	model	NOUN
hjic-1083	110	20	the	the	DET
hjic-1083	110	21	p(z	p(z	NOUN
hjic-1083	110	22	)	)	PUNCT
hjic-1083	110	23	=	=	SYM
hjic-1083	110	24	p(x	p(x	PROPN
hjic-1083	110	25	,	,	PUNCT
hjic-1083	110	26	y	y	NOUN
hjic-1083	110	27	)	)	PUNCT
hjic-1083	110	28	joint	joint	ADJ
hjic-1083	110	29	density	density	NOUN
hjic-1083	110	30	of	of	ADP
hjic-1083	110	31	the	the	DET
hjic-1083	110	32	response	response	NOUN
hjic-1083	110	33	variable	variable	PROPN
hjic-1083	110	34	yk	yk	PROPN
hjic-1083	110	35	and	and	CCONJ
hjic-1083	110	36	the	the	DET
hjic-1083	110	37	regressors	regressor	NOUN
hjic-1083	110	38	xk	xk	PROPN
hjic-1083	110	39	as	as	ADP
hjic-1083	110	40	a	a	DET
hjic-1083	110	41	mixture	mixture	NOUN
hjic-1083	110	42	of	of	ADP
hjic-1083	110	43	c	c	NOUN
hjic-1083	110	44	multivariate	multivariate	NOUN
hjic-1083	110	45	n	n	PROPN
hjic-1083	110	46	+	+	CCONJ
hjic-1083	110	47	1	1	NUM
hjic-1083	110	48	dimensional	dimensional	ADJ
hjic-1083	110	49	gaussian	gaussian	ADJ
hjic-1083	110	50	functions	function	NOUN
hjic-1083	110	51	.	.	PUNCT
hjic-1083	111	1	the	the	DET
hjic-1083	111	2	conditional	conditional	ADJ
hjic-1083	111	3	density	density	NOUN
hjic-1083	111	4	p(yjx	p(yjx	PROPN
hjic-1083	111	5	)	)	PUNCT
hjic-1083	111	6	is	be	AUX
hjic-1083	111	7	also	also	ADV
hjic-1083	111	8	a	a	DET
hjic-1083	111	9	mixture	mixture	NOUN
hjic-1083	111	10	of	of	ADP
hjic-1083	111	11	gaussians	gaussian	NOUN
hjic-1083	111	12	model	model	NOUN
hjic-1083	111	13	and	and	CCONJ
hjic-1083	111	14	the	the	DET
hjic-1083	111	15	regression	regression	NOUN
hjic-1083	111	16	e[yjx	e[yjx	NOUN
hjic-1083	111	17	]	]	PUNCT
hjic-1083	111	18	is	be	AUX
hjic-1083	111	19	i	i	PRON
hjic-1083	111	20	j	j	PROPN
hjic-1083	112	1	i	i	PRON
hjic-1083	112	2	j	j	PROPN
hjic-1083	112	3	y	y	PROPN
hjic-1083	112	4	p(y	p(y	PROPN
hjic-1083	112	5	,	,	PUNCT
hjic-1083	112	6	x)dy	x)dy	PROPN
hjic-1083	112	7	j	j	PROPN
hjic-1083	112	8	y	y	PROPN
hjic-1083	112	9	p(y	p(y	PROPN
hjic-1083	112	10	,	,	PUNCT
hjic-1083	112	11	x)dy	x)dy	PROPN
hjic-1083	112	12	e[yx]=	e[yx]=	PROPN
hjic-1083	112	13	y	y	PROPN
hjic-1083	112	14	p(yx)dy	p(yx)dy	NOUN
hjic-1083	112	15	p(x	p(x	PROPN
hjic-1083	112	16	)	)	PUNCT
hjic-1083	112	17	j	j	PROPN
hjic-1083	112	18	p(x	p(x	PROPN
hjic-1083	112	19	,	,	PUNCT
hjic-1083	112	20	y)dy	y)dy	PROPN
hjic-1083	112	21	(	(	PUNCT
hjic-1083	112	22	25	25	NUM
hjic-1083	112	23	)	)	PUNCT
hjic-1083	112	24	=	=	SYM
hjic-1083	113	1	i.	i.	NOUN
hjic-1083	114	1	[	[	X
hjic-1083	114	2	xr	xr	PROPN
hjic-1083	114	3	1]8	1]8	NUM
hjic-1083	114	4	;	;	PUNCT
hjic-1083	114	5	]	]	PUNCT
hjic-1083	114	6	p(~1j	p(~1j	NOUN
hjic-1083	114	7	;)	;)	PUNCT
hjic-1083	114	8	p(1j	p(1j	ADP
hjic-1083	114	9	;)	;)	PUNCT
hjic-1083	114	10	i.	i.	NOUN
hjic-1083	114	11	p	p	PROPN
hjic-1083	114	12	(	(	PUNCT
hjic-1083	114	13	1j;ix	1j;ix	NUM
hjic-1083	114	14	)	)	PUNCT
hjic-1083	115	1	[	[	X
hjic-1083	115	2	xr	xr	PROPN
hjic-1083	115	3	1]8	1]8	NUM
hjic-1083	115	4	;	;	PUNCT
hjic-1083	115	5	]	]	PUNCT
hjic-1083	116	1	i	i	PRON
hjic-1083	116	2	=	=	NOUN
hjic-1083	116	3	l	l	NOUN
hjic-1083	116	4	p(x	p(x	NOUN
hjic-1083	116	5	)	)	PUNCT
hjic-1083	116	6	i	i	PROPN
hjic-1083	116	7	=	=	NOUN
hjic-1083	116	8	l	l	NOUN
hjic-1083	116	9	where	where	SCONJ
hjic-1083	116	10	ei	ei	NOUN
hjic-1083	116	11	denotes	denote	VERB
hjic-1083	116	12	the	the	DET
hjic-1083	116	13	parameter	parameter	PROPN
hjic-1083	116	14	vector	vector	NOUN
hjic-1083	116	15	of	of	ADP
hjic-1083	116	16	the	the	DET
hjic-1083	116	17	local	local	ADJ
hjic-1083	116	18	model	model	NOUN
hjic-1083	116	19	and	and	CCONJ
hjic-1083	116	20	p(1j;jx	p(1j;jx	PROPN
hjic-1083	116	21	)	)	PUNCT
hjic-1083	116	22	denotes	denote	VERB
hjic-1083	116	23	the	the	DET
hjic-1083	116	24	probability	probability	NOUN
hjic-1083	116	25	that	that	SCONJ
hjic-1083	116	26	the	the	DET
hjic-1083	116	27	i	i	PROPN
hjic-1083	116	28	-th	-th	NOUN
hjic-1083	116	29	gaussian	gaussian	NOUN
hjic-1083	116	30	component	component	NOUN
hjic-1083	116	31	generated	generate	VERB
hjic-1083	116	32	the	the	DET
hjic-1083	116	33	regression	regression	NOUN
hjic-1083	116	34	vector	vector	NOUN
hjic-1083	116	35	x	x	X
hjic-1083	116	36	:	:	PUNCT
hjic-1083	116	37	p	p	X
hjic-1083	116	38	(	(	PUNCT
hjic-1083	116	39	tl	tl	PROPN
hjic-1083	116	40	;)	;)	X
hjic-1083	116	41	exp(-.!(xv':)t	exp(-.!(xv':)t	NOUN
hjic-1083	116	42	(	(	PUNCT
hjic-1083	116	43	f:"t1	f:"t1	NOUN
hjic-1083	116	44	(	(	PUNCT
hjic-1083	116	45	x	x	NOUN
hjic-1083	116	46	-·v	-·v	PROPN
hjic-1083	116	47	'	'	PUNCT
hjic-1083	116	48	:)	:)	ADJ
hjic-1083	116	49	l	l	NOUN
hjic-1083	116	50	(	(	PUNCT
hjic-1083	116	51	21r	21r	NOUN
hjic-1083	116	52	)	)	PUNCT
hjic-1083	116	53	'	'	NUM
hjic-1083	116	54	2	2	NUM
hjic-1083	116	55	.jiif4	.jiif4	SYM
hjic-1083	116	56	2	2	NUM
hjic-1083	116	57	'	'	PUNCT
hjic-1083	116	58	'	'	PUNCT
hjic-1083	116	59	'	'	PUNCT
hjic-1083	116	60	j	j	PROPN
hjic-1083	116	61	(	(	PUNCT
hjic-1083	116	62	26	26	NUM
hjic-1083	116	63	)	)	PUNCT
hjic-1083	116	64	:	:	PUNCT
hjic-1083	116	65	t	t	PROPN
hjic-1083	116	66	p(ij	p(ij	PROPN
hjic-1083	116	67	;)	;)	PUNCT
hjic-1083	116	68	exp(-.!(x	exp(-.!(x	PROPN
hjic-1083	116	69	-	-	PUNCT
hjic-1083	116	70	v':l	v':l	PROPN
hjic-1083	116	71	(	(	PUNCT
hjic-1083	116	72	f.	f.	PROPN
hjic-1083	116	73	""'f1	""'f1	PROPN
hjic-1083	117	1	(	(	PUNCT
hjic-1083	117	2	x	x	X
hjic-1083	117	3	-	-	NOUN
hjic-1083	117	4	v':)l	v':)l	ADJ
hjic-1083	117	5	i	i	NOUN
hjic-1083	117	6	=	=	NOUN
hjic-1083	117	7	l	l	X
hjic-1083	117	8	(	(	PUNCT
hjic-1083	117	9	21r	21r	NOUN
hjic-1083	117	10	)	)	PUNCT
hjic-1083	117	11	'	'	NUM
hjic-1083	117	12	2	2	NUM
hjic-1083	117	13	.jiif4	.jiif4	SYM
hjic-1083	117	14	2	2	NUM
hjic-1083	117	15	'	'	PART
hjic-1083	117	16	l	l	NOUN
hjic-1083	117	17	'	'	PUNCT
hjic-1083	117	18	j	j	NOUN
hjic-1083	117	19	where	where	SCONJ
hjic-1083	117	20	the	the	DET
hjic-1083	117	21	~xx	~xx	PROPN
hjic-1083	117	22	is	be	AUX
hjic-1083	117	23	obtained	obtain	VERB
hjic-1083	117	24	by	by	ADP
hjic-1083	117	25	the	the	DET
hjic-1083	117	26	partitioning	partitioning	NOUN
hjic-1083	117	27	of	of	ADP
hjic-1083	117	28	the	the	DET
hjic-1083	117	29	f	f	PROPN
hjic-1083	117	30	;	;	PUNCT
hjic-1083	117	31	covariance	covariance	NOUN
hjic-1083	117	32	matrix	matrix	NOUN
hjic-1083	117	33	f	f	PROPN
hjic-1083	117	34	-	-	PUNCT
hjic-1083	117	35	[	[	X
hjic-1083	117	36	·	·	PUNCT
hjic-1083	117	37	ft	ft	PROPN
hjic-1083	117	38	fty	fty	PROPN
hjic-1083	117	39	]	]	PUNCT
hjic-1083	117	40	i~]x	i~]x	PROPN
hjic-1083	117	41	f	f	X
hjic-1083	117	42	/	/	SYM
hjic-1083	117	43	y	y	PROPN
hjic-1083	117	44	(	(	PUNCT
hjic-1083	117	45	27	27	NUM
hjic-1083	117	46	)	)	PUNCT
hjic-1083	117	47	the	the	DET
hjic-1083	117	48	optimal	optimal	ADJ
hjic-1083	117	49	ei	ei	NOUN
hjic-1083	117	50	parameter	parameter	NOUN
hjic-1083	117	51	vector	vector	NOUN
hjic-1083	117	52	of	of	ADP
hjic-1083	117	53	the	the	DET
hjic-1083	117	54	local	local	ADJ
hjic-1083	117	55	models	model	NOUN
hjic-1083	117	56	can	can	AUX
hjic-1083	117	57	be	be	AUX
hjic-1083	117	58	obtained	obtain	VERB
hjic-1083	117	59	as	as	ADP
hjic-1083	117	60	:	:	PUNCT
hjic-1083	117	61	a1	a1	NOUN
hjic-1083	117	62	=	=	SYM
hjic-1083	117	63	{	{	PUNCT
hjic-1083	117	64	fjxx	fjxx	NOUN
hjic-1083	117	65	t	t	PROPN
hjic-1083	117	66	f;xy	f;xy	NOUN
hjic-1083	117	67	b	b	NOUN
hjic-1083	117	68	;	;	PUNCT
hjic-1083	117	69	=	=	SYM
hjic-1083	117	70	v	v	NOUN
hjic-1083	117	71	(	(	PUNCT
hjic-1083	117	72	-afv	-afv	NOUN
hjic-1083	117	73	:	:	PUNCT
hjic-1083	117	74	or	or	CCONJ
hjic-1083	117	75	in	in	ADP
hjic-1083	117	76	a	a	DET
hjic-1083	117	77	more	more	ADV
hjic-1083	117	78	compact	compact	ADJ
hjic-1083	117	79	form	form	NOUN
hjic-1083	117	80	:	:	PUNCT
hjic-1083	117	81	(	(	PUNCT
hjic-1083	117	82	j	j	X
hjic-1083	117	83	=	=	X
hjic-1083	117	84	l.!"~lf.t.t	l.!"~lf.t.t	X
hjic-1083	117	85	\-1	\-1	X
hjic-1083	117	86	,	,	PUNCT
hjic-1083	117	87	y	y	PROPN
hjic-1083	117	88	-f'j'x{fxx	-f'j'x{fxx	PROPN
hjic-1083	117	89	\-1	\-1	PROPN
hjic-1083	117	90	xj	xj	PROPN
hjic-1083	117	91	t	t	PROPN
hjic-1083	117	92	l.i'i	l.i'i	X
hjic-1083	117	93	\	\	PROPN
hjic-1083	118	1	i	i	PRON
hjic-1083	118	2	}	}	PUNCT
hjic-1083	118	3	~	~	PUNCT
hjic-1083	118	4	li	li	PROPN
hjic-1083	119	1	i	i	PRON
hjic-1083	119	2	\	\	PROPN
hjic-1083	120	1	i	i	PRON
hjic-1083	120	2	j	j	PROPN
hjic-1083	120	3	v	v	NOUN
hjic-1083	120	4	;	;	PUNCT
hjic-1083	120	5	(	(	PUNCT
hjic-1083	120	6	28	28	NUM
hjic-1083	120	7	)	)	PUNCT
hjic-1083	120	8	(	(	PUNCT
hjic-1083	120	9	29	29	NUM
hjic-1083	120	10	)	)	PUNCT
hjic-1083	120	11	ph	ph	NOUN
hjic-1083	120	12	fig.2	fig.2	NOUN
hjic-1083	120	13	the	the	DET
hjic-1083	120	14	considered	consider	VERB
hjic-1083	120	15	continuous	continuous	ADJ
hjic-1083	120	16	stirred	stir	VERB
hjic-1083	120	17	tank	tank	NOUN
hjic-1083	120	18	reactor	reactor	NOUN
hjic-1083	120	19	.	.	PUNCT
hjic-1083	121	1	526	526	NUM
hjic-1083	121	2	524	524	NUM
hjic-1083	121	3	522	522	NUM
hjic-1083	121	4	520	520	NUM
hjic-1083	121	5	j518	j518	NUM
hjic-1083	121	6	516	516	NUM
hjic-1083	121	7	514	514	NUM
hjic-1083	121	8	512	512	NUM
hjic-1083	121	9	6.5	6.5	NUM
hjic-1083	121	10	7.5	7.5	NUM
hjic-1083	121	11	8.5	8.5	NUM
hjic-1083	121	12	9	9	NUM
hjic-1083	121	13	9.5	9.5	NUM
hjic-1083	121	14	10	10	NUM
hjic-1083	121	15	10.5	10.5	NUM
hjic-1083	121	16	11	11	NUM
hjic-1083	121	17	ph(k	ph(k	NOUN
hjic-1083	121	18	)	)	PUNCT
hjic-1083	122	1	fig.3	fig.3	PROPN
hjic-1083	122	2	orientation	orientation	NOUN
hjic-1083	122	3	of	of	ADP
hjic-1083	122	4	the	the	DET
hjic-1083	122	5	identified	identify	VERB
hjic-1083	122	6	clusters	cluster	NOUN
hjic-1083	122	7	.	.	PUNCT
hjic-1083	123	1	this	this	PRON
hjic-1083	123	2	is	be	AUX
hjic-1083	123	3	identical	identical	ADJ
hjic-1083	123	4	to	to	ADP
hjic-1083	123	5	the	the	DET
hjic-1083	123	6	weighted	weighted	NOUN
hjic-1083	123	7	,	,	PUNCT
hjic-1083	123	8	also	also	ADV
hjic-1083	123	9	called	call	VERB
hjic-1083	123	10	local	local	ADJ
hjic-1083	123	11	,	,	PUNCT
hjic-1083	123	12	parameter	parameter	NOUN
hjic-1083	123	13	estimation	estimation	NOUN
hjic-1083	123	14	approach	approach	NOUN
hjic-1083	123	15	that	that	PRON
hjic-1083	123	16	does	do	AUX
hjic-1083	123	17	not	not	PART
hjic-1083	123	18	estimate	estimate	VERB
hjic-1083	123	19	all	all	DET
hjic-1083	123	20	parameters	parameter	NOUN
hjic-1083	123	21	simultaneously	simultaneously	ADV
hjic-1083	123	22	,	,	PUNCT
hjic-1083	123	23	because	because	SCONJ
hjic-1083	123	24	the	the	DET
hjic-1083	123	25	parameters	parameter	NOUN
hjic-1083	123	26	of	of	ADP
hjic-1083	123	27	the	the	DET
hjic-1083	123	28	local	local	ADJ
hjic-1083	123	29	models	model	NOUN
hjic-1083	123	30	are	be	AUX
hjic-1083	123	31	estimated	estimate	VERB
hjic-1083	123	32	separately	separately	ADV
hjic-1083	123	33	using	use	VERB
hjic-1083	123	34	a	a	DET
hjic-1083	123	35	set	set	NOUN
hjic-1083	123	36	of	of	ADP
hjic-1083	123	37	local	local	ADJ
hjic-1083	123	38	estimation	estimation	NOUN
hjic-1083	123	39	criteria	criterion	NOUN
hjic-1083	123	40	where	where	SCONJ
hjic-1083	123	41	xe	xe	PROPN
hjic-1083	123	42	denotes	denote	VERB
hjic-1083	123	43	the	the	DET
hjic-1083	123	44	extended	extended	ADJ
hjic-1083	123	45	regression	regression	NOUN
hjic-1083	123	46	matrix	matrix	NOUN
hjic-1083	123	47	obtained	obtain	VERB
hjic-1083	123	48	by	by	ADP
hjic-1083	123	49	adding	add	VERB
hjic-1083	123	50	a	a	DET
hjic-1083	123	51	unitary	unitary	ADJ
hjic-1083	123	52	column	column	NOUN
hjic-1083	123	53	to	to	ADP
hjic-1083	123	54	x	x	PROPN
hjic-1083	123	55	,	,	PUNCT
hjic-1083	123	56	xe	xe	PROPN
hjic-1083	123	57	=	=	PUNCT
hjic-1083	124	1	[	[	X
hjic-1083	124	2	x	x	X
hjic-1083	124	3	1	1	NUM
hjic-1083	124	4	]	]	PUNCT
hjic-1083	124	5	,	,	PUNCT
hjic-1083	124	6	and	and	CCONJ
hjic-1083	124	7	<	<	X
hjic-1083	124	8	pi	pi	NOUN
hjic-1083	124	9	denote	denote	VERB
hjic-1083	124	10	a	a	DET
hjic-1083	124	11	diagonal	diagonal	ADJ
hjic-1083	124	12	matrix	matrix	NOUN
hjic-1083	124	13	having	have	VERB
hjic-1083	124	14	membership	membership	NOUN
hjic-1083	124	15	degrees	degree	NOUN
hjic-1083	124	16	in	in	ADP
hjic-1083	124	17	its	its	PRON
hjic-1083	124	18	diagonal	diagonal	ADJ
hjic-1083	124	19	elements	element	NOUN
hjic-1083	124	20	.	.	PUNCT
hjic-1083	125	1	[	[	PUNCT
hjic-1083	125	2	f.li	f.li	NOUN
hjic-1083	125	3	,	,	PUNCT
hjic-1083	125	4	l	l	PROPN
hjic-1083	125	5	0	0	PUNCT
hjic-1083	125	6	(	(	PUNCT
hjic-1083	125	7	(	(	PUNCT
hjic-1083	125	8	)	)	PUNCT
hjic-1083	125	9	.	.	PUNCT
hjic-1083	126	1	=	=	PUNCT
hjic-1083	126	2	0	0	NUM
hjic-1083	126	3	j.li,2	j.li,2	PROPN
hjic-1083	126	4	l	l	NOUN
hjic-1083	126	5	:	:	PUNCT
hjic-1083	126	6	:	:	PUNCT
hjic-1083	126	7	0	0	NUM
hjic-1083	126	8	0	0	NUM
hjic-1083	126	9	(	(	PUNCT
hjic-1083	126	10	31	31	NUM
hjic-1083	126	11	)	)	PUNCT
hjic-1083	126	12	the	the	DET
hjic-1083	126	13	weighted	weight	VERB
hjic-1083	126	14	least	least	ADJ
hjic-1083	126	15	-	-	PUNCT
hjic-1083	126	16	squares	square	NOUN
hjic-1083	126	17	estimate	estimate	NOUN
hjic-1083	126	18	of	of	ADP
hjic-1083	126	19	the	the	DET
hjic-1083	126	20	consequent	consequent	ADJ
hjic-1083	126	21	rule	rule	NOUN
hjic-1083	126	22	parameters	parameter	NOUN
hjic-1083	126	23	is	be	AUX
hjic-1083	126	24	given	give	VERB
hjic-1083	126	25	by	by	ADP
hjic-1083	126	26	(	(	PUNCT
hjic-1083	126	27	32	32	NUM
hjic-1083	126	28	)	)	PUNCT
hjic-1083	126	29	note	note	NOUN
hjic-1083	126	30	that	that	SCONJ
hjic-1083	126	31	the	the	DET
hjic-1083	126	32	resulted	resulted	ADJ
hjic-1083	126	33	gaussian	gaussian	ADJ
hjic-1083	126	34	mixture	mixture	NOUN
hjic-1083	126	35	of	of	ADP
hjic-1083	126	36	local	local	ADJ
hjic-1083	126	37	models	model	NOUN
hjic-1083	126	38	defined	define	VERB
hjic-1083	126	39	by	by	ADP
hjic-1083	126	40	eq.(25	eq.(25	NOUN
hjic-1083	126	41	)	)	PUNCT
hjic-1083	126	42	is	be	AUX
hjic-1083	126	43	identical	identical	ADJ
hjic-1083	126	44	to	to	ADP
hjic-1083	126	45	the	the	DET
hjic-1083	126	46	operating	operate	VERB
hjic-1083	126	47	regime	regime	NOUN
hjic-1083	126	48	based	base	VERB
hjic-1083	126	49	model	model	NOUN
hjic-1083	126	50	given	give	VERB
hjic-1083	126	51	by	by	ADP
hjic-1083	126	52	eq.(3	eq.(3	NOUN
hjic-1083	126	53	)	)	PUNCT
hjic-1083	126	54	when	when	SCONJ
hjic-1083	126	55	the	the	DET
hjic-1083	126	56	133	133	NUM
hjic-1083	126	57	6.5	6.5	NUM
hjic-1083	126	58	"	"	PUNCT
hjic-1083	126	59	o	o	NOUN
hjic-1083	126	60	200	200	NUM
hjic-1083	126	61	400	400	NUM
hjic-1083	126	62	600	600	NUM
hjic-1083	126	63	800	800	NUM
hjic-1083	126	64	~000	~000	NUM
hjic-1083	126	65	time	time	NOUN
hjic-1083	126	66	[	[	X
hjic-1083	126	67	time	time	NOUN
hjic-1083	126	68	-	-	PUNCT
hjic-1083	126	69	step=0.2	step=0.2	NOUN
hjic-1083	126	70	min	min	NOUN
hjic-1083	126	71	]	]	X
hjic-1083	126	72	fig.4	fig.4	ADJ
hjic-1083	126	73	free	free	ADJ
hjic-1083	126	74	-	-	PUNCT
hjic-1083	126	75	run	run	NOUN
hjic-1083	126	76	test	test	NOUN
hjic-1083	126	77	of	of	ADP
hjic-1083	126	78	the	the	DET
hjic-1083	126	79	model	model	NOUN
hjic-1083	126	80	on	on	ADP
hjic-1083	126	81	the	the	DET
hjic-1083	126	82	validation	validation	NOUN
hjic-1083	126	83	data	datum	NOUN
hjic-1083	126	84	.	.	PUNCT
hjic-1083	127	1	weighting	weight	VERB
hjic-1083	127	2	function	function	NOUN
hjic-1083	127	3	is	be	AUX
hjic-1083	127	4	chosen	choose	VERB
hjic-1083	127	5	as	as	ADP
hjic-1083	127	6	¢i(x	¢i(x	NUM
hjic-1083	127	7	)	)	PUNCT
hjic-1083	127	8	=	=	SYM
hjic-1083	127	9	p(1j;jx	p(1j;jx	PROPN
hjic-1083	127	10	)	)	PUNCT
hjic-1083	127	11	.	.	PUNCT
hjic-1083	128	1	furthermore	furthermore	ADV
hjic-1083	128	2	,	,	PUNCT
hjic-1083	128	3	the	the	DET
hjic-1083	128	4	model	model	NOUN
hjic-1083	128	5	is	be	AUX
hjic-1083	128	6	also	also	ADV
hjic-1083	128	7	identical	identical	ADJ
hjic-1083	128	8	to	to	ADP
hjic-1083	128	9	ts	ts	ADP
hjic-1083	128	10	fuzzy	fuzzy	ADJ
hjic-1083	128	11	models	model	NOUN
hjic-1083	128	12	,	,	PUNCT
hjic-1083	128	13	when	when	SCONJ
hjic-1083	128	14	the	the	DET
hjic-1083	128	15	membership	membership	NOUN
hjic-1083	128	16	functions	function	NOUN
hjic-1083	128	17	are	be	AUX
hjic-1083	128	18	identified	identify	VERB
hjic-1083	128	19	as	as	SCONJ
hjic-1083	128	20	it	it	PRON
hjic-1083	128	21	was	be	AUX
hjic-1083	128	22	shown	show	VERB
hjic-1083	128	23	in	in	ADP
hjic-1083	128	24	section	section	NOUN
hjic-1083	128	25	2	2	NUM
hjic-1083	128	26	.	.	PUNCT
hjic-1083	128	27	application	application	NOUN
hjic-1083	128	28	to	to	ADP
hjic-1083	128	29	the	the	DET
hjic-1083	128	30	identification	identification	NOUN
hjic-1083	128	31	of	of	ADP
hjic-1083	128	32	a	a	DET
hjic-1083	128	33	ph	ph	ADJ
hjic-1083	128	34	process	process	NOUN
hjic-1083	128	35	the	the	DET
hjic-1083	128	36	identification	identification	NOUN
hjic-1083	128	37	of	of	ADP
hjic-1083	128	38	the	the	DET
hjic-1083	128	39	ph	ph	NOUN
hjic-1083	128	40	(	(	PUNCT
hjic-1083	128	41	the	the	DET
hjic-1083	128	42	concentration	concentration	NOUN
hjic-1083	128	43	of	of	ADP
hjic-1083	128	44	hydrogen	hydrogen	NOUN
hjic-1083	128	45	ions	ion	NOUN
hjic-1083	128	46	)	)	PUNCT
hjic-1083	128	47	in	in	ADP
hjic-1083	128	48	a	a	DET
hjic-1083	128	49	continuous	continuous	ADJ
hjic-1083	128	50	stirred	stir	VERB
hjic-1083	128	51	tank	tank	NOUN
hjic-1083	128	52	reactor	reactor	NOUN
hjic-1083	128	53	(	(	PUNCT
hjic-1083	128	54	cstr	cstr	NOUN
hjic-1083	128	55	)	)	PUNCT
hjic-1083	128	56	is	be	AUX
hjic-1083	128	57	a	a	DET
hjic-1083	128	58	well	well	ADV
hjic-1083	128	59	-	-	PUNCT
hjic-1083	128	60	known	know	VERB
hjic-1083	128	61	benchmark	benchmark	NOUN
hjic-1083	128	62	problem	problem	NOUN
hjic-1083	128	63	.	.	PUNCT
hjic-1083	129	1	the	the	DET
hjic-1083	129	2	cstr	cstr	NOUN
hjic-1083	129	3	depicted	depict	VERB
hjic-1083	129	4	in	in	ADP
hjic-1083	129	5	fig.2	fig.2	PROPN
hjic-1083	129	6	.	.	PUNCT
hjic-1083	130	1	has	have	VERB
hjic-1083	130	2	two	two	NUM
hjic-1083	130	3	input	input	NOUN
hjic-1083	130	4	streams	stream	NOUN
hjic-1083	130	5	:	:	PUNCT
hjic-1083	130	6	sodium	sodium	NOUN
hjic-1083	130	7	hydroxide	hydroxide	NOUN
hjic-1083	130	8	and	and	CCONJ
hjic-1083	130	9	acetic	acetic	ADJ
hjic-1083	130	10	acid	acid	NOUN
hjic-1083	130	11	.	.	PUNCT
hjic-1083	131	1	the	the	DET
hjic-1083	131	2	dynamic	dynamic	ADJ
hjic-1083	131	3	model	model	NOUN
hjic-1083	131	4	for	for	ADP
hjic-1083	131	5	the	the	DET
hjic-1083	131	6	ph	ph	NOUN
hjic-1083	131	7	in	in	ADP
hjic-1083	131	8	the	the	DET
hjic-1083	131	9	tank	tank	NOUN
hjic-1083	131	10	is	be	AUX
hjic-1083	131	11	given	give	VERB
hjic-1083	131	12	in	in	ADP
hjic-1083	131	13	the	the	DET
hjic-1083	131	14	appendix	appendix	NOUN
hjic-1083	131	15	.	.	PUNCT
hjic-1083	132	1	po	po	NOUN
hjic-1083	132	2	,	,	PUNCT
hjic-1083	132	3	collection	collection	NOUN
hjic-1083	132	4	of	of	ADP
hjic-1083	132	5	the	the	DET
hjic-1083	132	6	data	datum	NOUN
hjic-1083	132	7	,	,	PUNCT
hjic-1083	132	8	a	a	DET
hjic-1083	132	9	sampling	sample	VERB
hjic-1083	132	10	interval	interval	NOUN
hjic-1083	132	11	of	of	ADP
hjic-1083	132	12	0.2	0.2	NUM
hjic-1083	132	13	min	min	NOUN
hjic-1083	132	14	was	be	AUX
hjic-1083	132	15	used	use	VERB
hjic-1083	132	16	.	.	PUNCT
hjic-1083	133	1	as	as	SCONJ
hjic-1083	133	2	the	the	DET
hjic-1083	133	3	process	process	NOUN
hjic-1083	133	4	can	can	AUX
hjic-1083	133	5	be	be	AUX
hjic-1083	133	6	modeled	model	VERB
hjic-1083	133	7	as	as	ADP
hjic-1083	133	8	a	a	DET
hjic-1083	133	9	first	first	ADJ
hjic-1083	133	10	!	!	PUNCT
hjic-1083	134	1	jrder	jrder	NOUN
hjic-1083	134	2	dynamic	dynamic	ADJ
hjic-1083	134	3	system	system	NOUN
hjic-1083	134	4	[	[	X
hjic-1083	134	5	12	12	NUM
hjic-1083	134	6	]	]	PUNCT
hjic-1083	134	7	,	,	PUNCT
hjic-1083	134	8	the	the	DET
hjic-1083	134	9	fuzzy	fuzzy	ADJ
hjic-1083	134	10	model	model	NOUN
hjic-1083	134	11	consisu	consisu	PROPN
hjic-1083	134	12	,	,	PUNCT
hjic-1083	134	13	uf	uf	PROPN
hjic-1083	134	14	the	the	DET
hjic-1083	134	15	following	follow	VERB
hjic-1083	134	16	rules	rule	NOUN
hjic-1083	134	17	:	:	PUNCT
hjic-1083	134	18	ri	ri	NOUN
hjic-1083	134	19	:	:	PUNCT
hjic-1083	134	20	if	if	SCONJ
hjic-1083	134	21	(	(	PUNCT
hjic-1083	134	22	ph(k	ph(k	X
hjic-1083	134	23	)	)	PUNCT
hjic-1083	134	24	,	,	PUNCT
hjic-1083	134	25	fnaoh	fnaoh	NOUN
hjic-1083	134	26	(	(	PUNCT
hjic-1083	134	27	k	k	NOUN
hjic-1083	134	28	)	)	PUNCT
hjic-1083	134	29	]	]	PUNCT
hjic-1083	134	30	is	be	AUX
hjic-1083	134	31	a	a	DET
hjic-1083	134	32	(	(	PUNCT
hjic-1083	134	33	33	33	NUM
hjic-1083	134	34	)	)	PUNCT
hjic-1083	134	35	then	then	ADV
hjic-1083	134	36	ph	ph	X
hjic-1083	134	37	(	(	PUNCT
hjic-1083	134	38	k	k	NOUN
hjic-1083	134	39	+	+	PROPN
hjic-1083	134	40	1	1	X
hjic-1083	134	41	)	)	PUNCT
hjic-1083	134	42	=	=	SYM
hjic-1083	134	43	a1,1	a1,1	NOUN
hjic-1083	134	44	·	·	PUNCT
hjic-1083	134	45	ph	ph	X
hjic-1083	134	46	(	(	PUNCT
hjic-1083	134	47	k	k	NOUN
hjic-1083	134	48	)	)	PUNCT
hjic-1083	135	1	+	+	NOUN
hjic-1083	135	2	a1•2	a1•2	PROPN
hjic-1083	135	3	•	•	ADJ
hjic-1083	135	4	f	f	PROPN
hjic-1083	135	5	nuoil	nuoil	NOUN
hjic-1083	135	6	{	{	PUNCT
hjic-1083	135	7	k	k	NOUN
hjic-1083	135	8	)	)	PUNCT
hjic-1083	135	9	+	+	SYM
hjic-1083	135	10	b	b	X
hjic-1083	135	11	,	,	PUNCT
hjic-1083	135	12	by	by	ADP
hjic-1083	135	13	using	use	VERB
hjic-1083	135	14	transformed	transform	VERB
hjic-1083	135	15	input	input	NOUN
hjic-1083	135	16	variables	variable	NOUN
hjic-1083	135	17	:	:	PUNCT
hjic-1083	135	18	ri	ri	X
hjic-1083	135	19	:	:	PUNCT
hjic-1083	135	20	if	if	SCONJ
hjic-1083	135	21	~:.1	~:.1	PRON
hjic-1083	135	22	•	•	NUM
hjic-1083	135	23	ph(k)+t{,2	ph(k)+t{,2	NOUN
hjic-1083	135	24	·	·	PUNCT
hjic-1083	135	25	fnaou(k)j	fnaou(k)j	X
hjic-1083	135	26	is	be	AUX
hjic-1083	135	27	as.t	as.t	NOUN
hjic-1083	135	28	and	and	CCONJ
hjic-1083	135	29	&	&	CCONJ
hjic-1083	135	30	~.1	~.1	PROPN
hjic-1083	135	31	•	•	NOUN
hjic-1083	135	32	ph(k)+t~.2	ph(k)+t~.2	NOUN
hjic-1083	135	33	•	•	NOUN
hjic-1083	135	34	fnuoil(k	fnuoil(k	NOUN
hjic-1083	135	35	)	)	PUNCT
hjic-1083	135	36	]	]	PUNCT
hjic-1083	136	1	is	be	AUX
hjic-1083	136	2	a1.z	a1.z	PROPN
hjic-1083	136	3	(	(	PUNCT
hjic-1083	136	4	34	34	NUM
hjic-1083	136	5	}	}	PUNCT
hjic-1083	136	6	then	then	ADV
hjic-1083	136	7	ph(k	ph(k	X
hjic-1083	136	8	+	+	CCONJ
hjic-1083	136	9	1	1	X
hjic-1083	136	10	)	)	PUNCT
hjic-1083	136	11	=	=	VERB
hjic-1083	136	12	ai	ai	PROPN
hjic-1083	136	13	,	,	PUNCT
hjic-1083	136	14	t	t	PROPN
hjic-1083	136	15	'	'	PUNCT
hjic-1083	136	16	ph(k)+a,,2	ph(k)+a,,2	ADJ
hjic-1083	136	17	•	•	NUM
hjic-1083	136	18	f,.a011	f,.a011	NOUN
hjic-1083	136	19	(	(	PUNCT
hjic-1083	136	20	k	k	NOUN
hjic-1083	136	21	)	)	PUNCT
hjic-1083	137	1	+	+	SYM
hjic-1083	137	2	b	b	X
hjic-1083	137	3	,	,	PUNCT
hjic-1083	137	4	four	four	NUM
hjic-1083	137	5	local	local	ADJ
hjic-1083	137	6	models	model	NOUN
hjic-1083	137	7	were	be	AUX
hjic-1083	137	8	identified	identify	VERB
hjic-1083	137	9	.	.	PUNCT
hjic-1083	138	1	the	the	DET
hjic-1083	138	2	number	number	NOUN
hjic-1083	138	3	of	of	ADP
hjic-1083	138	4	local	local	ADJ
hjic-1083	138	5	models	model	NOUN
hjic-1083	138	6	were	be	AUX
hjic-1083	138	7	determined	determine	VERB
hjic-1083	138	8	by	by	ADP
hjic-1083	138	9	cross	cross	NOUN
hjic-1083	138	10	-	-	NOUN
hjic-1083	138	11	validation	validation	NOUN
hjic-1083	138	12	.	.	PUNCT
hjic-1083	139	1	the	the	DET
hjic-1083	139	2	operating	operating	NOUN
hjic-1083	139	3	region	region	NOUN
hjic-1083	139	4	(	(	PUNCT
hjic-1083	139	5	the	the	DET
hjic-1083	139	6	orientation	orientation	NOUN
hjic-1083	139	7	of	of	ADP
hjic-1083	139	8	ft	ft	NOUN
hjic-1083	139	9	matrices	matrix	NOUN
hjic-1083	139	10	)	)	PUNCT
hjic-1083	139	11	of	of	ADP
hjic-1083	139	12	these	these	DET
hjic-1083	139	13	models	model	NOUN
hjic-1083	139	14	are	be	AUX
hjic-1083	139	15	shown	show	VERB
hjic-1083	139	16	in	in	ADP
hjic-1083	139	17	fig.3	fig.3	PROPN
hjic-1083	139	18	.	.	PUNCT
hjic-1083	140	1	the	the	DET
hjic-1083	140	2	identified	identify	VERB
hjic-1083	140	3	model	model	NOUN
hjic-1083	140	4	was	be	AUX
hjic-1083	140	5	tested	test	VERB
hjic-1083	140	6	with	with	ADP
hjic-1083	140	7	a	a	DET
hjic-1083	140	8	validation	validation	NOUN
hjic-1083	140	9	data	datum	NOUN
hjic-1083	140	10	set	set	VERB
hjic-1083	140	11	.	.	PUNCT
hjic-1083	141	1	the	the	DET
hjic-1083	141	2	model	model	NOUN
hjic-1083	141	3	was	be	AUX
hjic-1083	141	4	used	use	VERB
hjic-1083	141	5	for	for	ADP
hjic-1083	141	6	one	one	NUM
hjic-1083	141	7	-	-	PUNCT
hjic-1083	141	8	step	step	NOUN
hjic-1083	141	9	-	-	PUNCT
hjic-1083	141	10	ahead	ahead	NOUN
hjic-1083	141	11	and	and	CCONJ
hjic-1083	141	12	simulation	simulation	NOUN
hjic-1083	141	13	{	{	PUNCT
hjic-1083	141	14	infinite	infinite	NOUN
hjic-1083	141	15	-	-	PUNCT
hjic-1083	141	16	step	step	NOUN
hjic-1083	141	17	~	~	NOUN
hjic-1083	141	18	ahead	ahead	ADV
hjic-1083	141	19	)	)	PUNCT
hjic-1083	141	20	prediction	prediction	NOUN
hjic-1083	141	21	of	of	ADP
hjic-1083	141	22	the	the	DET
hjic-1083	141	23	ph	ph	PROPN
hjic-1083	141	24	.	.	PUNCT
hjic-1083	142	1	the	the	DET
hjic-1083	142	2	later	later	ADJ
hjic-1083	142	3	experiments	experiment	NOUN
hjic-1083	142	4	is	be	AUX
hjic-1083	142	5	depicted	depict	VERB
hjic-1083	142	6	in	in	ADP
hjic-1083	142	7	fig.4	fig.4	PROPN
hjic-1083	142	8	.	.	PUNCT
hjic-1083	143	1	the	the	DET
hjic-1083	143	2	results	result	NOUN
hjic-1083	143	3	were	be	AUX
hjic-1083	143	4	compared	compare	VERB
hjic-1083	143	5	with	with	ADP
hjic-1083	143	6	the	the	DET
hjic-1083	143	7	performance	performance	NOUN
hjic-1083	143	8	of	of	ADP
hjic-1083	143	9	models	model	NOUN
hjic-1083	143	10	obtained	obtain	VERB
hjic-1083	143	11	by	by	ADP
hjic-1083	143	12	using	use	VERB
hjic-1083	143	13	fuzzy	fuzzy	ADJ
hjic-1083	143	14	model	model	NOUN
hjic-1083	143	15	ldentl	ldentl	ADJ
hjic-1083	143	16	tkation	tkation	NOUN
hjic-1083	143	17	toolbox	toolbox	NOUN
hjic-1083	143	18	[	[	X
hjic-1083	143	19	9	9	NUM
hjic-1083	143	20	]	]	PUNCT
hjic-1083	143	21	.	.	PUNCT
hjic-1083	144	1	as	as	SCONJ
hjic-1083	144	2	table	table	NOUN
hjic-1083	144	3	1	1	NUM
hjic-1083	144	4	shows	show	NOUN
hjic-1083	144	5	,	,	PUNCT
hjic-1083	144	6	the	the	DET
hjic-1083	144	7	propo'\ed	propo'\ed	PROPN
hjic-1083	144	8	method	method	NOUN
hjic-1083	144	9	shows	show	VERB
hjic-1083	144	10	superior	superior	ADJ
hjic-1083	144	11	performance	performance	NOUN
hjic-1083	144	12	over	over	ADP
hjic-1083	144	13	this	this	PRON
hjic-1083	144	14	adv	adv	PROPN
hjic-1083	144	15	~	~	NOUN
hjic-1083	144	16	mced	mced	ADJ
hjic-1083	144	17	tool	tool	NOUN
hjic-1083	144	18	developed	develop	VERB
hjic-1083	144	19	for	for	ADP
hjic-1083	144	20	identification	identification	NOUN
hjic-1083	144	21	of	of	ADP
hjic-1083	144	22	nonline;1r	nonline;1r	NOUN
hjic-1083	144	23	dynamic	dynamic	ADJ
hjic-1083	144	24	systems	system	NOUN
hjic-1083	144	25	.	.	PUNCT
hjic-1083	145	1	134	134	NUM
hjic-1083	145	2	table	table	NOUN
hjic-1083	145	3	1	1	NUM
hjic-1083	145	4	comparison	comparison	NOUN
hjic-1083	145	5	of	of	ADP
hjic-1083	145	6	model	model	NOUN
hjic-1083	145	7	performances	performance	NOUN
hjic-1083	145	8	(	(	PUNCT
hjic-1083	145	9	mean	mean	ADJ
hjic-1083	145	10	squares	square	NOUN
hjic-1083	145	11	of	of	ADP
hjic-1083	145	12	prediction	prediction	NOUN
hjic-1083	145	13	errors	error	NOUN
hjic-1083	145	14	)	)	PUNCT
hjic-1083	145	15	.	.	PUNCT
hjic-1083	146	1	method	method	VERB
hjic-1083	146	2	one	one	NUM
hjic-1083	146	3	-	-	PUNCT
hjic-1083	146	4	ste	ste	PROPN
hjic-1083	146	5	simulation	simulation	NOUN
hjic-1083	146	6	fmid	fmid	PROPN
hjic-1083	147	1	[	[	X
hjic-1083	147	2	9	9	NUM
hjic-1083	147	3	]	]	PUNCT
hjic-1083	147	4	proposed	propose	VERB
hjic-1083	147	5	0.0241	0.0241	NUM
hjic-1083	147	6	0.009	0.009	NUM
hjic-1083	147	7	conclusions	conclusion	NOUN
hjic-1083	147	8	0.2835	0.2835	VERB
hjic-1083	147	9	0.0956	0.0956	NUM
hjic-1083	147	10	a	a	DET
hjic-1083	147	11	new	new	ADJ
hjic-1083	147	12	algorithm	algorithm	NOUN
hjic-1083	147	13	for	for	ADP
hjic-1083	147	14	the	the	DET
hjic-1083	147	15	identification	identification	NOUN
hjic-1083	147	16	of	of	ADP
hjic-1083	147	17	nonlinear	nonlinear	ADJ
hjic-1083	147	18	systems	system	NOUN
hjic-1083	147	19	is	be	AUX
hjic-1083	147	20	proposed	propose	VERB
hjic-1083	147	21	that	that	PRON
hjic-1083	147	22	is	be	AUX
hjic-1083	147	23	based	base	VERB
hjic-1083	147	24	on	on	ADP
hjic-1083	147	25	the	the	DET
hjic-1083	147	26	expectation	expectation	NOUN
hjic-1083	147	27	maximization	maximization	NOUN
hjic-1083	147	28	identification	identification	NOUN
hjic-1083	147	29	of	of	ADP
hjic-1083	147	30	gaussian	gaussian	ADJ
hjic-1083	147	31	mixtures	mixture	NOUN
hjic-1083	147	32	model	model	NOUN
hjic-1083	147	33	.	.	PUNCT
hjic-1083	148	1	a	a	DET
hjic-1083	148	2	method	method	NOUN
hjic-1083	148	3	to	to	PART
hjic-1083	148	4	extract	extract	VERB
hjic-1083	148	5	takagi	takagi	NOUN
hjic-1083	148	6	-	-	PUNCT
hjic-1083	148	7	sugeno	sugeno	NOUN
hjic-1083	148	8	fuzzy	fuzzy	ADJ
hjic-1083	148	9	models	model	NOUN
hjic-1083	148	10	from	from	ADP
hjic-1083	148	11	gaussian	gaussian	ADJ
hjic-1083	148	12	mixtures	mixture	NOUN
hjic-1083	148	13	model	model	NOUN
hjic-1083	148	14	is	be	AUX
hjic-1083	148	15	presented	present	VERB
hjic-1083	148	16	.	.	PUNCT
hjic-1083	149	1	the	the	DET
hjic-1083	149	2	resulted	resulted	ADJ
hjic-1083	149	3	fuzzy	fuzzy	ADJ
hjic-1083	149	4	models	model	NOUN
hjic-1083	149	5	are	be	AUX
hjic-1083	149	6	based	base	VERB
hjic-1083	149	7	on	on	ADP
hjic-1083	149	8	the	the	DET
hjic-1083	149	9	transformed	transform	VERB
hjic-1083	149	10	input	input	NOUN
hjic-1083	149	11	-	-	PUNCT
hjic-1083	149	12	domain	domain	NOUN
hjic-1083	149	13	approach	approach	NOUN
hjic-1083	149	14	,	,	PUNCT
hjic-1083	149	15	which	which	PRON
hjic-1083	149	16	allows	allow	VERB
hjic-1083	149	17	the	the	DET
hjic-1083	149	18	effective	effective	ADJ
hjic-1083	149	19	partition	partition	NOUN
hjic-1083	149	20	of	of	ADP
hjic-1083	149	21	the	the	DET
hjic-1083	149	22	input	input	NOUN
hjic-1083	149	23	space	space	NOUN
hjic-1083	149	24	and	and	CCONJ
hjic-1083	149	25	enables	enable	VERB
hjic-1083	149	26	the	the	DET
hjic-1083	149	27	interpretability	interpretability	NOUN
hjic-1083	149	28	of	of	ADP
hjic-1083	149	29	the	the	DET
hjic-1083	149	30	model	model	NOUN
hjic-1083	149	31	.	.	PUNCT
hjic-1083	150	1	the	the	DET
hjic-1083	150	2	performance	performance	NOUN
hjic-1083	150	3	of	of	ADP
hjic-1083	150	4	the	the	DET
hjic-1083	150	5	proposed	propose	VERB
hjic-1083	150	6	modeling	modeling	NOUN
hjic-1083	150	7	technique	technique	NOUN
hjic-1083	150	8	was	be	AUX
hjic-1083	150	9	demonstrated	demonstrate	VERB
hjic-1083	150	10	in	in	ADP
hjic-1083	150	11	the	the	DET
hjic-1083	150	12	identification	identification	NOUN
hjic-1083	150	13	of	of	ADP
hjic-1083	150	14	the	the	DET
hjic-1083	150	15	a	a	DET
hjic-1083	150	16	ph	ph	ADJ
hjic-1083	150	17	process	process	NOUN
hjic-1083	150	18	.	.	PUNCT
hjic-1083	151	1	acknowledgement	acknowledgement	NOUN
hjic-1083	151	2	the	the	DET
hjic-1083	151	3	financial	financial	ADJ
hjic-1083	151	4	support	support	NOUN
hjic-1083	151	5	of	of	ADP
hjic-1083	151	6	the	the	DET
hjic-1083	151	7	hungarian	hungarian	ADJ
hjic-1083	151	8	ministry	ministry	PROPN
hjic-1083	151	9	of	of	ADP
hjic-1083	151	10	culture	culture	NOUN
hjic-1083	151	11	and	and	CCONJ
hjic-1083	151	12	education	education	NOUN
hjic-1083	151	13	(	(	PUNCT
hjic-1083	151	14	fkfp-0023/2000	fkfp-0023/2000	PROPN
hjic-1083	151	15	,	,	PUNCT
hjic-1083	151	16	fkfp0073/200	fkfp0073/200	PROPN
hjic-1083	151	17	1	1	NUM
hjic-1083	151	18	)	)	PUNCT
hjic-1083	151	19	and	and	CCONJ
hjic-1083	151	20	the	the	DET
hjic-1083	151	21	hungarian	hungarian	ADJ
hjic-1083	151	22	science	science	PROPN
hjic-1083	151	23	foundation	foundation	PROPN
hjic-1083	151	24	(	(	PUNCT
hjic-1083	151	25	t023157	t023157	NOUN
hjic-1083	151	26	}	}	PUNCT
hjic-1083	151	27	is	be	AUX
hjic-1083	151	28	greatly	greatly	ADV
hjic-1083	151	29	acknowledged	acknowledge	VERB
hjic-1083	151	30	.	.	PUNCT
hjic-1083	152	1	janos	janos	PROPN
hjic-1083	152	2	abonyi	abonyi	PROPN
hjic-1083	152	3	is	be	AUX
hjic-1083	152	4	grateful	grateful	ADJ
hjic-1083	152	5	for	for	ADP
hjic-1083	152	6	the	the	DET
hjic-1083	152	7	financial	financial	ADJ
hjic-1083	152	8	support	support	NOUN
hjic-1083	152	9	of	of	ADP
hjic-1083	152	10	the	the	DET
hjic-1083	152	11	janos	janos	PROPN
hjic-1083	152	12	bolyai	bolyai	PROPN
hjic-1083	152	13	research	research	NOUN
hjic-1083	152	14	fellowship	fellowship	NOUN
hjic-1083	152	15	of	of	ADP
hjic-1083	152	16	the	the	DET
hjic-1083	152	17	hungarian	hungarian	ADJ
hjic-1083	152	18	academy	academy	PROPN
hjic-1083	152	19	of	of	ADP
hjic-1083	152	20	science	science	PROPN
hjic-1083	152	21	.	.	PUNCT
hjic-1083	153	1	tibor	tibor	PROPN
hjic-1083	153	2	chovan	chovan	PROPN
hjic-1083	153	3	is	be	AUX
hjic-1083	153	4	supported	support	VERB
hjic-1083	153	5	by	by	ADP
hjic-1083	153	6	the	the	DET
hjic-1083	153	7	hans	hans	PROPN
hjic-1083	153	8	pape	pape	PROPN
hjic-1083	153	9	foundation	foundation	PROPN
hjic-1083	153	10	.	.	PUNCT
hjic-1083	154	1	model	model	NOUN
hjic-1083	154	2	of	of	ADP
hjic-1083	154	3	the	the	DET
hjic-1083	154	4	ph	ph	ADJ
hjic-1083	154	5	process	process	NOUN
hjic-1083	154	6	a	a	DET
hjic-1083	154	7	dynamic	dynamic	ADJ
hjic-1083	154	8	model	model	NOUN
hjic-1083	154	9	of	of	ADP
hjic-1083	154	10	the	the	DET
hjic-1083	154	11	ph	ph	NOUN
hjic-1083	154	12	in	in	ADP
hjic-1083	154	13	a	a	DET
hjic-1083	154	14	tank	tank	NOUN
hjic-1083	154	15	can	can	AUX
hjic-1083	154	16	be	be	AUX
hjic-1083	154	17	obtained	obtain	VERB
hjic-1083	154	18	by	by	ADP
hjic-1083	154	19	considering	consider	VERB
hjic-1083	154	20	the	the	DET
hjic-1083	154	21	material	material	NOUN
hjic-1083	154	22	balances	balance	NOUN
hjic-1083	154	23	on	on	ADP
hjic-1083	154	24	[	[	X
hjic-1083	154	25	na+	na+	X
hjic-1083	154	26	]	]	X
hjic-1083	154	27	and	and	CCONJ
hjic-1083	154	28	the	the	DET
hjic-1083	154	29	total	total	ADJ
hjic-1083	154	30	acetate	acetate	NOUN
hjic-1083	155	1	[	[	X
hjic-1083	155	2	hac+	hac+	NOUN
hjic-1083	155	3	ac-	ac-	X
hjic-1083	155	4	]	]	PUNCT
hjic-1083	155	5	and	and	CCONJ
hjic-1083	155	6	assuming	assume	VERB
hjic-1083	155	7	that	that	SCONJ
hjic-1083	155	8	acid	acid	NOUN
hjic-1083	155	9	-	-	PUNCT
hjic-1083	155	10	base	base	NOUN
hjic-1083	155	11	equilibrium	equilibrium	NOUN
hjic-1083	155	12	and	and	CCONJ
hjic-1083	155	13	electroneutrality	electroneutrality	NOUN
hjic-1083	155	14	relationships	relationship	NOUN
hjic-1083	155	15	hold	hold	VERB
hjic-1083	155	16	[	[	X
hjic-1083	155	17	12	12	NUM
hjic-1083	155	18	]	]	PUNCT
hjic-1083	155	19	.	.	PUNCT
hjic-1083	156	1	f	f	PROPN
hjic-1083	156	2	e.~tc	e.~tc	PROPN
hjic-1083	156	3	•	•	NOUN
hjic-1083	157	1	[	[	X
hjic-1083	157	2	haclin	haclin	X
hjic-1083	157	3	(	(	PUNCT
hjic-1083	157	4	f	f	PROPN
hjic-1083	157	5	hac	hac	PROPN
hjic-1083	157	6	+	+	CCONJ
hjic-1083	157	7	fnuoh	fnuoh	NOUN
hjic-1083	157	8	)	)	PUNCT
hjic-1083	157	9	·	·	PUNCT
hjic-1083	158	1	[	[	X
hjic-1083	158	2	hac+	hac+	NOUN
hjic-1083	158	3	ac-	ac-	X
hjic-1083	158	4	]	]	X
hjic-1083	159	1	=	=	PUNCT
hjic-1083	160	1	=	=	NOUN
hjic-1083	160	2	vd[hac+ac-	vd[hac+ac-	NOUN
hjic-1083	160	3	]	]	X
hjic-1083	160	4	dt	dt	PUNCT
hjic-1083	160	5	sodium	sodium	NOUN
hjic-1083	160	6	ion	ion	NOUN
hjic-1083	160	7	balance	balance	NOUN
hjic-1083	160	8	:	:	PUNCT
hjic-1083	160	9	f,	f,	PROPN
hjic-1083	160	10	.	.	PUNCT
hjic-1083	160	11	,itoh	,itoh	PUNCT
hjic-1083	160	12	·	·	PUNCT
hjic-1083	161	1	[	[	X
hjic-1083	161	2	naoh},,-(fnm	naoh},,-(fnm	ADJ
hjic-1083	161	3	:	:	PUNCT
hjic-1083	161	4	+	+	NUM
hjic-1083	161	5	fl	fl	NOUN
hjic-1083	161	6	..	..	PUNCT
hjic-1083	161	7	,uoh	,uoh	PUNCT
hjic-1083	161	8	)	)	PUNCT
hjic-1083	161	9	·	·	PUNCT
hjic-1083	161	10	[	[	X
hjic-1083	161	11	na+]=	na+]=	NUM
hjic-1083	161	12	v	v	NUM
hjic-1083	161	13	d[~;+j	d[~;+j	X
hjic-1083	161	14	hac	hac	X
hjic-1083	161	15	equilibrium	equilibrium	NOUN
hjic-1083	161	16	:	:	PUNCT
hjic-1083	162	1	[	[	X
hjic-1083	162	2	ac"}·[h	ac"}·[h	X
hjic-1083	162	3	..	..	PUNCT
hjic-1083	162	4	]	]	PUNCT
hjic-1083	162	5	----=k	----=k	X
hjic-1083	162	6	{	{	PUNCT
hjic-1083	162	7	hac	hac	X
hjic-1083	162	8	]	]	X
hjic-1083	162	9	"	"	PUNCT
hjic-1083	162	10	water	water	NOUN
hjic-1083	162	11	equilibrium	equilibrium	NOUN
hjic-1083	162	12	:	:	PUNCT
hjic-1083	162	13	[	[	X
hjic-1083	162	14	h	h	X
hjic-1083	162	15	..	..	PUNCT
hjic-1083	162	16	l·[oh-1=	l·[oh-1=	PROPN
hjic-1083	162	17	k	k	X
hjic-1083	162	18	)	)	PUNCT
hjic-1083	162	19	!	!	PUNCT
hjic-1083	163	1	electroneutra1ity	electroneutra1ity	NOUN
hjic-1083	163	2	:	:	PUNCT
hjic-1083	163	3	{	{	PUNCT
hjic-1083	163	4	na	na	NOUN
hjic-1083	163	5	.	.	NOUN
hjic-1083	163	6	,.}+[h""j=[oh-}+[ac-1	,.}+[h""j=[oh-}+[ac-1	PUNCT
hjic-1083	163	7	the	the	DET
hjic-1083	163	8	ph	ph	NOUN
hjic-1083	163	9	can	can	AUX
hjic-1083	163	10	be	be	AUX
hjic-1083	163	11	calculated	calculate	VERB
hjic-1083	163	12	from	from	ADP
hjic-1083	163	13	the	the	DET
hjic-1083	163	14	previous	previous	ADJ
hjic-1083	163	15	equations	equation	NOUN
hjic-1083	163	16	as	as	ADP
hjic-1083	163	17	table	table	NOUN
hjic-1083	163	18	2	2	NUM
hjic-1083	163	19	parameters	parameter	NOUN
hjic-1083	163	20	used	use	VERB
hjic-1083	163	21	in	in	ADP
hjic-1083	163	22	the	the	DET
hjic-1083	163	23	simulations	simulation	NOUN
hjic-1083	163	24	.	.	PUNCT
hjic-1083	164	1	parameter	parameter	PROPN
hjic-1083	164	2	fnaoh	fnaoh	NOUN
hjic-1083	165	1	[	[	X
hjic-1083	165	2	naoh!n	naoh!n	PROPN
hjic-1083	165	3	[	[	X
hjic-1083	165	4	hacjn	hacjn	NOUN
hjic-1083	165	5	[	[	X
hjic-1083	165	6	na+	na+	X
hjic-1083	165	7	]	]	X
hjic-1083	165	8	description	description	NOUN
hjic-1083	165	9	volume	volume	NOUN
hjic-1083	165	10	of	of	ADP
hjic-1083	165	11	the	the	DET
hjic-1083	165	12	tank	tank	NOUN
hjic-1083	165	13	flow	flow	NOUN
hjic-1083	165	14	rate	rate	NOUN
hjic-1083	165	15	of	of	ADP
hjic-1083	165	16	acetic	acetic	ADJ
hjic-1083	165	17	acid	acid	NOUN
hjic-1083	165	18	flow	flow	NOUN
hjic-1083	165	19	rate	rate	NOUN
hjic-1083	165	20	of	of	ADP
hjic-1083	165	21	naoh	naoh	NOUN
hjic-1083	165	22	inlet	inlet	VERB
hjic-1083	165	23	concentration	concentration	NOUN
hjic-1083	165	24	of	of	ADP
hjic-1083	165	25	naoh	naoh	ADJ
hjic-1083	165	26	nominal	nominal	ADJ
hjic-1083	165	27	value	value	NOUN
hjic-1083	165	28	1000	1000	NUM
hjic-1083	166	1	[	[	X
hjic-1083	166	2	1	1	NUM
hjic-1083	166	3	]	]	SYM
hjic-1083	166	4	81	81	NUM
hjic-1083	166	5	[	[	SYM
hjic-1083	166	6	1	1	NUM
hjic-1083	166	7	/	/	SYM
hjic-1083	166	8	min	min	NOUN
hjic-1083	166	9	]	]	X
hjic-1083	166	10	515	515	NUM
hjic-1083	166	11	[	[	SYM
hjic-1083	166	12	1	1	NUM
hjic-1083	166	13	/	/	SYM
hjic-1083	166	14	min	min	NOUN
hjic-1083	166	15	]	]	X
hjic-1083	166	16	0.05	0.05	NUM
hjic-1083	166	17	[	[	X
hjic-1083	166	18	molll	molll	ADJ
hjic-1083	166	19	]	]	PUNCT
hjic-1083	166	20	inlet	inlet	VERB
hjic-1083	166	21	concentration	concentration	NOUN
hjic-1083	166	22	of	of	ADP
hjic-1083	166	23	acetic	acetic	ADJ
hjic-1083	166	24	0.32	0.32	NUM
hjic-1083	166	25	[	[	X
hjic-1083	166	26	mol/1	mol/1	X
hjic-1083	166	27	]	]	X
hjic-1083	166	28	acid	acid	NOUN
hjic-1083	166	29	initial	initial	ADJ
hjic-1083	166	30	concentration	concentration	NOUN
hjic-1083	166	31	of	of	ADP
hjic-1083	166	32	0.0432	0.0432	NUM
hjic-1083	167	1	[	[	X
hjic-1083	167	2	molll	molll	ADJ
hjic-1083	167	3	]	]	X
hjic-1083	167	4	sodium	sodium	NOUN
hjic-1083	167	5	in	in	ADP
hjic-1083	167	6	the	the	DET
hjic-1083	167	7	cstr	cstr	NOUN
hjic-1083	167	8	r	r	NOUN
hjic-1083	167	9	-	-	PUNCT
hjic-1083	167	10	]	]	X
hjic-1083	167	11	initial	initial	ADJ
hjic-1083	167	12	concentration	concentration	NOUN
hjic-1083	167	13	of	of	ADP
hjic-1083	167	14	acetate	acetate	NOUN
hjic-1083	167	15	0	0	NUM
hjic-1083	167	16	0432	0432	NUM
hjic-1083	168	1	[	[	X
hjic-1083	168	2	mol!l	mol!l	X
hjic-1083	168	3	]	]	X
hjic-1083	168	4	lhac	lhac	VERB
hjic-1083	169	1	+	+	CCONJ
hjic-1083	169	2	ac	ac	X
hjic-1083	169	3	in	in	ADP
hjic-1083	169	4	the	the	DET
hjic-1083	169	5	cstr	cstr	NOUN
hjic-1083	169	6	.	.	PUNCT
hjic-1083	170	1	ka	ka	PROPN
hjic-1083	170	2	acid	acid	PROPN
hjic-1083	170	3	equilibrium	equilibrium	PROPN
hjic-1083	170	4	constant	constant	ADJ
hjic-1083	170	5	1.753	1.753	NUM
hjic-1083	170	6	·	·	SYM
hjic-1083	170	7	10	10	NUM
hjic-1083	170	8	-	-	SYM
hjic-1083	170	9	5	5	NUM
hjic-1083	170	10	water	water	NOUN
hjic-1083	170	11	equilibrium	equilibrium	NOUN
hjic-1083	170	12	constant	constant	ADJ
hjic-1083	171	1	[	[	X
hjic-1083	171	2	h+]3	h+]3	X
hjic-1083	171	3	+	+	X
hjic-1083	171	4	[	[	X
hjic-1083	171	5	h+	h+	X
hjic-1083	171	6	]	]	X
hjic-1083	171	7	2	2	NUM
hjic-1083	171	8	(	(	PUNCT
hjic-1083	171	9	ka	ka	PROPN
hjic-1083	171	10	+	+	CCONJ
hjic-1083	172	1	[	[	X
hjic-1083	172	2	na+	na+	X
hjic-1083	172	3	]	]	X
hjic-1083	172	4	)	)	PUNCT
hjic-1083	173	1	+	+	CCONJ
hjic-1083	174	1	[	[	X
hjic-1083	174	2	h+]([na+]ka	h+]([na+]ka	ADJ
hjic-1083	174	3	-[hac+ac-]ka	-[hac+ac-]ka	ADJ
hjic-1083	174	4	-k	-k	INTJ
hjic-1083	174	5	.	.	PUNCT
hjic-1083	174	6	,.)-kwka	,.)-kwka	PUNCT
hjic-1083	175	1	=	=	SYM
hjic-1083	175	2	0	0	NUM
hjic-1083	175	3	ph==	ph==	ADJ
hjic-1083	175	4	log[h+	log[h+	PROPN
hjic-1083	175	5	]	]	X
hjic-1083	175	6	the	the	DET
hjic-1083	175	7	parameters	parameter	NOUN
hjic-1083	175	8	used	use	VERB
hjic-1083	175	9	in	in	ADP
hjic-1083	175	10	our	our	PRON
hjic-1083	175	11	simulations	simulation	NOUN
hjic-1083	175	12	are	be	AUX
hjic-1083	175	13	taken	take	VERB
hjic-1083	175	14	from	from	ADP
hjic-1083	175	15	[	[	X
hjic-1083	175	16	12	12	NUM
hjic-1083	175	17	]	]	PUNCT
hjic-1083	175	18	and	and	CCONJ
hjic-1083	175	19	are	be	AUX
hjic-1083	175	20	given	give	VERB
hjic-1083	175	21	in	in	ADP
hjic-1083	175	22	table	table	NOUN
hjic-1083	175	23	2	2	NUM
hjic-1083	175	24	.	.	PUNCT
hjic-1083	175	25	references	reference	NOUN
hjic-1083	175	26	1	1	NUM
hjic-1083	175	27	.	.	PUNCT
hjic-1083	175	28	leitch	leitch	PROPN
hjic-1083	175	29	r.	r.	PROPN
hjic-1083	175	30	:	:	PUNCT
hjic-1083	175	31	comput	comput	PROPN
hjic-1083	175	32	.	.	PUNCT
hjic-1083	176	1	control	control	PROPN
hjic-1083	176	2	eng	eng	PROPN
hjic-1083	176	3	.	.	PUNCT
hjic-1083	177	1	j.	j.	PROPN
hjic-1083	177	2	,	,	PUNCT
hjic-1083	177	3	1992	1992	NUM
hjic-1083	177	4	,	,	PUNCT
hjic-1083	177	5	july	july	PROPN
hjic-1083	177	6	,	,	PUNCT
hjic-1083	177	7	153	153	NUM
hjic-1083	177	8	-	-	SYM
hjic-1083	177	9	163	163	NUM
hjic-1083	177	10	2	2	NUM
hjic-1083	177	11	.	.	PUNCT
hjic-1083	177	12	coit	coit	PROPN
hjic-1083	177	13	b.	b.	PROPN
hjic-1083	177	14	j.	j.	PROPN
hjic-1083	177	15	,	,	PUNCT
hjic-1083	177	16	durham	durham	PROPN
hjic-1083	177	17	r.	r.	PROPN
hjic-1083	177	18	g.	g.	PROPN
hjic-1083	177	19	and	and	CCONJ
hjic-1083	177	20	sullivan	sullivan	PROPN
hjic-1083	177	21	g.	g.	PROPN
hjic-1083	177	22	r.	r.	PROPN
hjic-1083	177	23	:	:	PUNCT
hjic-1083	177	24	comput	comput	PROPN
hjic-1083	177	25	.	.	PUNCT
hjic-1083	178	1	chern	chern	PROPN
hjic-1083	178	2	.	.	PUNCT
hjic-1083	179	1	eng	eng	PROPN
hjic-1083	179	2	.	.	PROPN
hjic-1083	179	3	,	,	PUNCT
hjic-1083	179	4	1989	1989	NUM
hjic-1083	179	5	,	,	PUNCT
hjic-1083	179	6	13,973	13,973	NUM
hjic-1083	179	7	-	-	SYM
hjic-1083	179	8	984	984	NUM
hjic-1083	179	9	3	3	NUM
hjic-1083	179	10	.	.	PUNCT
hjic-1083	179	11	sjoberg	sjoberg	PROPN
hjic-1083	179	12	j.	j.	PROPN
hjic-1083	179	13	,	,	PUNCT
hjic-1083	179	14	zhang	zhang	PROPN
hjic-1083	179	15	q.	q.	PROPN
hjic-1083	179	16	,	,	PUNCT
hjic-1083	179	17	ljung	ljung	PROPN
hjic-1083	179	18	l.	l.	PROPN
hjic-1083	179	19	,	,	PUNCT
hjic-1083	179	20	benveniste	benveniste	PROPN
hjic-1083	179	21	a.	a.	NOUN
hjic-1083	179	22	,	,	PUNCT
hjic-1083	179	23	deywn	deywn	PROPN
hjic-1083	179	24	b.	b.	PROPN
hjic-1083	179	25	,	,	PUNCT
hjic-1083	179	26	gwrennec	gwrennec	NOUN
hjic-1083	179	27	p	p	PROPN
hjic-1083	179	28	-	-	PUNCT
hjic-1083	179	29	y.	y.	NOUN
hjic-1083	179	30	,	,	PUNCT
hjic-1083	179	31	hjalmarsson	hjalmarsson	NOUN
hjic-1083	179	32	h.	h.	PROPN
hjic-1083	179	33	and	and	CCONJ
hjic-1083	179	34	juditsky	juditsky	PROPN
hjic-1083	179	35	a.	a.	PROPN
hjic-1083	179	36	:	:	PUNCT
hjic-1083	179	37	automatica	automatica	PROPN
hjic-1083	179	38	,	,	PUNCT
hjic-1083	179	39	1995,31	1995,31	NUM
hjic-1083	179	40	,	,	PUNCT
hjic-1083	179	41	1691	1691	NUM
hjic-1083	179	42	-	-	SYM
hjic-1083	179	43	1724	1724	NUM
hjic-1083	179	44	4	4	NUM
hjic-1083	179	45	.	.	PUNCT
hjic-1083	179	46	murray	murray	PROPN
hjic-1083	179	47	-	-	PUNCT
hjic-1083	179	48	smith	smith	PROPN
hjic-1083	179	49	r.	r.	PROPN
hjic-1083	179	50	:	:	PUNCT
hjic-1083	179	51	a	a	DET
hjic-1083	179	52	local	local	ADJ
hjic-1083	179	53	model	model	NOUN
hjic-1083	179	54	network	network	NOUN
hjic-1083	179	55	approach	approach	NOUN
hjic-1083	179	56	to	to	ADP
hjic-1083	179	57	nonlinear	nonlinear	ADJ
hjic-1083	179	58	modelling	modelling	NOUN
hjic-1083	179	59	,	,	PUNCT
hjic-1083	179	60	phd	phd	NOUN
hjic-1083	179	61	thesis	thesis	NOUN
hjic-1083	179	62	,	,	PUNCT
hjic-1083	179	63	university	university	NOUN
hjic-1083	179	64	of	of	ADP
hjic-1083	179	65	strathclyde	strathclyde	PROPN
hjic-1083	179	66	,	,	PUNCT
hjic-1083	179	67	computer	computer	NOUN
hjic-1083	179	68	science	science	PROPN
hjic-1083	179	69	department	department	PROPN
hjic-1083	179	70	,	,	PUNCT
hjic-1083	179	71	1994	1994	NUM
hjic-1083	179	72	5	5	NUM
hjic-1083	179	73	.	.	PUNCT
hjic-1083	179	74	murray	murray	PROPN
hjic-1083	179	75	-	-	PUNCT
hjic-1083	179	76	smith	smith	PROPN
hjic-1083	179	77	r.	r.	PROPN
hjic-1083	179	78	and	and	CCONJ
hjic-1083	179	79	johansen	johansen	PROPN
hjic-1083	179	80	t.	t.	PROPN
hjic-1083	179	81	a.	a.	PROPN
hjic-1083	179	82	(	(	PUNCT
hjic-1083	179	83	ed	ed	NOUN
hjic-1083	179	84	):	):	PUNCT
hjic-1083	179	85	multiple	multiple	ADJ
hjic-1083	179	86	model	model	NOUN
hjic-1083	179	87	approaches	approach	NOUN
hjic-1083	179	88	to	to	PART
hjic-1083	179	89	nonlinear	nonlinear	ADJ
hjic-1083	179	90	modeling	modeling	NOUN
hjic-1083	179	91	and	and	CCONJ
hjic-1083	179	92	control	control	NOUN
hjic-1083	179	93	,	,	PUNCT
hjic-1083	179	94	taylor	taylor	PROPN
hjic-1083	179	95	&	&	CCONJ
hjic-1083	179	96	francis	francis	PROPN
hjic-1083	179	97	,	,	PUNCT
hjic-1083	179	98	london	london	PROPN
hjic-1083	179	99	,	,	PUNCT
hjic-1083	179	100	uk	uk	PROPN
hjic-1083	179	101	,	,	PUNCT
hjic-1083	179	102	1997	1997	NUM
hjic-1083	179	103	6	6	NUM
hjic-1083	179	104	.	.	PUNCT
hjic-1083	180	1	babuska	babuska	PROPN
hjic-1083	180	2	r.	r.	PROPN
hjic-1083	180	3	and	and	CCONJ
hjic-1083	180	4	verbruggen	verbruggen	PROPN
hjic-1083	180	5	h.	h.	PROPN
hjic-1083	180	6	b.	b.	PROPN
hjic-1083	180	7	:	:	PUNCT
hjic-1083	180	8	fuzzy	fuzzy	ADJ
hjic-1083	180	9	set	set	VERB
hjic-1083	180	10	methods	method	NOUN
hjic-1083	180	11	for	for	ADP
hjic-1083	180	12	local	local	ADJ
hjic-1083	180	13	modeling	modeling	NOUN
hjic-1083	180	14	and	and	CCONJ
hjic-1083	180	15	identification	identification	NOUN
hjic-1083	180	16	,	,	PUNCT
hjic-1083	180	17	in	in	ADP
hjic-1083	180	18	multiple	multiple	ADJ
hjic-1083	180	19	model	model	NOUN
hjic-1083	180	20	approaches	approach	NOUN
hjic-1083	180	21	to	to	PART
hjic-1083	180	22	nonlinear	nonlinear	ADJ
hjic-1083	180	23	modeling	modeling	NOUN
hjic-1083	180	24	and	and	CCONJ
hjic-1083	180	25	control	control	NOUN
hjic-1083	180	26	(	(	PUNCT
hjic-1083	180	27	ed	ed	NOUN
hjic-1083	180	28	.	.	PUNCT
hjic-1083	180	29	murray	murray	PROPN
hjic-1083	180	30	-	-	PUNCT
hjic-1083	180	31	smith	smith	PROPN
hjic-1083	180	32	r.	r.	PROPN
hjic-1083	180	33	,	,	PUNCT
hjic-1083	180	34	johansen	johansen	PROPN
hjic-1083	180	35	,	,	PUNCT
hjic-1083	180	36	t.	t.	PROPN
hjic-1083	180	37	a.	a.	PROPN
hjic-1083	180	38	)	)	PUNCT
hjic-1083	180	39	,	,	PUNCT
hjic-1083	180	40	taylor	taylor	PROPN
hjic-1083	180	41	&	&	CCONJ
hjic-1083	180	42	francis	francis	PROPN
hjic-1083	180	43	.	.	PROPN
hjic-1083	181	1	london	london	PROPN
hjic-1083	181	2	,	,	PUNCT
hjic-1083	181	3	uk	uk	PROPN
hjic-1083	181	4	,	,	PUNCT
hjic-1083	181	5	75	75	NUM
hjic-1083	181	6	-	-	SYM
hjic-1083	181	7	100	100	NUM
hjic-1083	181	8	,	,	PUNCT
hjic-1083	181	9	1997	1997	NUM
hjic-1083	181	10	7	7	NUM
hjic-1083	181	11	.	.	PUNCT
hjic-1083	181	12	takagi	takagi	PROPN
hjic-1083	181	13	t.	t.	PROPN
hjic-1083	181	14	and	and	CCONJ
hjic-1083	181	15	sugeno	sugeno	PROPN
hjic-1083	181	16	m.	m.	NOUN
hjic-1083	181	17	:	:	PUNCT
hjic-1083	181	18	ieee	ieee	PROPN
hjic-1083	181	19	trans	trans	PROPN
hjic-1083	181	20	.	.	PUNCT
hjic-1083	182	1	syst	syst	PROPN
hjic-1083	182	2	.	.	PUNCT
hjic-1083	183	1	man	man	PROPN
hjic-1083	183	2	cybem	cybem	PROPN
hjic-1083	183	3	.	.	PUNCT
hjic-1083	184	1	,l985	,l985	PROPN
hjic-1083	184	2	,	,	PUNCT
hjic-1083	184	3	15(1	15(1	NUM
hjic-1083	184	4	)	)	PUNCT
hjic-1083	184	5	,	,	PUNCT
hjic-1083	184	6	116	116	NUM
hjic-1083	184	7	-	-	SYM
hjic-1083	184	8	132	132	NUM
hjic-1083	184	9	8	8	NUM
hjic-1083	184	10	.	.	PUNCT
hjic-1083	185	1	hunt	hunt	PROPN
hjic-1083	185	2	k.j	k.j	PROPN
hjic-1083	185	3	.	.	PROPN
hjic-1083	185	4	,	,	PUNCT
hjic-1083	185	5	haas	haas	PROPN
hjic-1083	185	6	r.	r.	PROPN
hjic-1083	185	7	and	and	CCONJ
hjic-1083	185	8	murray	murray	PROPN
hjic-1083	185	9	-	-	PUNCT
hjic-1083	185	10	smith	smith	PROPN
hjic-1083	185	11	r.	r.	PROPN
hjic-1083	185	12	:	:	PUNCT
hjic-1083	185	13	ieee	ieee	PROPN
hjic-1083	185	14	trans	trans	PROPN
hjic-1083	185	15	.	.	PUNCT
hjic-1083	186	1	neural	neural	ADJ
hjic-1083	186	2	netw	netw	NOUN
hjic-1083	186	3	.	.	PUNCT
hjic-1083	186	4	,	,	PUNCT
hjic-1083	186	5	1996	1996	NUM
hjic-1083	186	6	,	,	PUNCT
hjic-1083	186	7	7(3	7(3	NUM
hjic-1083	186	8	)	)	PUNCT
hjic-1083	186	9	,	,	PUNCT
hjic-1083	186	10	776	776	NUM
hjic-1083	186	11	-	-	SYM
hjic-1083	186	12	781	781	NUM
hjic-1083	186	13	9	9	NUM
hjic-1083	186	14	.	.	PUNCT
hjic-1083	187	1	babuska	babuska	PROPN
hjic-1083	187	2	r.	r.	PROPN
hjic-1083	187	3	:	:	PUNCT
hjic-1083	187	4	fuzzy	fuzzy	ADJ
hjic-1083	187	5	modeling	modeling	NOUN
hjic-1083	187	6	for	for	ADP
hjic-1083	187	7	control	control	NOUN
hjic-1083	187	8	,	,	PUNCT
hjic-1083	187	9	kluwer	kluwer	NOUN
hjic-1083	187	10	academic	academic	ADJ
hjic-1083	187	11	publishers	publisher	NOUN
hjic-1083	187	12	,	,	PUNCT
hjic-1083	187	13	boston	boston	PROPN
hjic-1083	187	14	,	,	PUNCT
hjic-1083	187	15	ma	ma	PROPN
hjic-1083	187	16	,	,	PUNCT
hjic-1083	187	17	1998	1998	NUM
hjic-1083	187	18	10	10	NUM
hjic-1083	187	19	.	.	PUNCT
hjic-1083	188	1	kim	kim	PROPN
hjic-1083	188	2	e.	e.	PROPN
hjic-1083	188	3	,	,	PUNCT
hjic-1083	188	4	park	park	NOUN
hjic-1083	188	5	m.	m.	NOUN
hjic-1083	188	6	,	,	PUNCT
hjic-1083	188	7	kim	kim	PROPN
hjic-1083	188	8	s.	s.	PROPN
hjic-1083	188	9	and	and	CCONJ
hjic-1083	188	10	park	park	PROPN
hjic-1083	188	11	m.	m.	NOUN
hjic-1083	188	12	:	:	PUNCT
hjic-1083	188	13	ieee	ieee	NOUN
hjic-1083	188	14	trans	trans	PROPN
hjic-1083	188	15	.	.	PUNCT
hjic-1083	188	16	fuzzy	fuzzy	ADJ
hjic-1083	188	17	syst	syst	PROPN
hjic-1083	188	18	.	.	PUNCT
hjic-1083	188	19	,	,	PUNCT
hjic-1083	188	20	1998	1998	NUM
hjic-1083	188	21	,	,	PUNCT
hjic-1083	188	22	6	6	NUM
hjic-1083	188	23	,	,	PUNCT
hjic-1083	188	24	596	596	NUM
hjic-1083	188	25	-	-	SYM
hjic-1083	188	26	604	604	NUM
hjic-1083	188	27	11	11	NUM
hjic-1083	188	28	.	.	PUNCT
hjic-1083	189	1	schoner	schoner	PROPN
hjic-1083	189	2	b.	b.	PROPN
hjic-1083	189	3	:	:	PUNCT
hjic-1083	189	4	probabilistic	probabilistic	ADJ
hjic-1083	189	5	cheracterization	cheracterization	NOUN
hjic-1083	189	6	and	and	CCONJ
hjic-1083	189	7	synthesis	synthesis	NOUN
hjic-1083	189	8	of	of	ADP
hjic-1083	189	9	complex	complex	ADJ
hjic-1083	189	10	driven	drive	VERB
hjic-1083	189	11	systems	system	NOUN
hjic-1083	189	12	,	,	PUNCT
hjic-1083	189	13	ph.d	ph.d	PROPN
hjic-1083	189	14	.	.	PROPN
hjic-1083	190	1	thesis~	thesis~	PROPN
hjic-1083	190	2	massachusetts	massachusetts	PROPN
hjic-1083	190	3	institute	institute	PROPN
hjic-1083	190	4	of	of	ADP
hjic-1083	190	5	technology	technology	PROPN
hjic-1083	190	6	,	,	PUNCT
hjic-1083	190	7	2000	2000	NUM
hjic-1083	190	8	12	12	NUM
hjic-1083	190	9	.	.	PUNCT
hjic-1083	191	1	brat	brat	PROPN
hjic-1083	191	2	n.	n.	PROPN
hjic-1083	191	3	v.	v.	PROPN
hjic-1083	191	4	and	and	CCONJ
hjic-1083	191	5	mcavoy	mcavoy	PROPN
hjic-1083	191	6	t.	t.	PROPN
hjic-1083	191	7	j.	j.	PROPN
hjic-1083	191	8	:	:	PUNCT
hjic-1083	191	9	comput	comput	PROPN
hjic-1083	191	10	.	.	PUNCT
hjic-1083	192	1	chern	chern	PROPN
hjic-1083	192	2	.	.	PUNCT
hjic-1083	193	1	eng	eng	PROPN
hjic-1083	193	2	.	.	PROPN
hjic-1083	193	3	,	,	PUNCT
hjic-1083	193	4	1992	1992	NUM
hjic-1083	193	5	,	,	PUNCT
hjic-1083	193	6	16,271	16,271	NUM
hjic-1083	193	7	-	-	SYM
hjic-1083	193	8	281	281	NUM
hjic-1083	193	9	page	page	NOUN
hjic-1083	193	10	130	130	NUM
hjic-1083	193	11	page	page	NOUN
hjic-1083	193	12	131	131	NUM
hjic-1083	193	13	page	page	NOUN
hjic-1083	193	14	132	132	NUM
hjic-1083	193	15	page	page	NOUN
hjic-1083	193	16	133	133	NUM
hjic-1083	193	17	page	page	NOUN
hjic-1083	193	18	134	134	NUM
hjic-1083	193	19	page	page	NOUN
hjic-1083	193	20	135	135	NUM