id	sid	tid	token	lemma	pos
ijassa-135	1	1	advances	advance	NOUN
ijassa-135	1	2	in	in	ADP
ijassa-135	1	3	systems	system	NOUN
ijassa-135	1	4	science	science	NOUN
ijassa-135	1	5	and	and	CCONJ
ijassa-135	1	6	applications	application	NOUN
ijassa-135	1	7	(	(	PUNCT
ijassa-135	1	8	2013	2013	NUM
ijassa-135	1	9	)	)	PUNCT
ijassa-135	1	10	vol.13	vol.13	NOUN
ijassa-135	1	11	no.3	no.3	VERB
ijassa-135	1	12	233	233	NUM
ijassa-135	1	13	-	-	SYM
ijassa-135	1	14	248	248	NUM
ijassa-135	1	15	ways	way	NOUN
ijassa-135	1	16	of	of	ADP
ijassa-135	1	17	fusing	fuse	VERB
ijassa-135	1	18	different	different	ADJ
ijassa-135	1	19	types	type	NOUN
ijassa-135	1	20	of	of	ADP
ijassa-135	1	21	information	information	NOUN
ijassa-135	1	22	and	and	CCONJ
ijassa-135	1	23	how	how	SCONJ
ijassa-135	1	24	systemic	systemic	ADJ
ijassa-135	1	25	yoyo	yoyo	PROPN
ijassa-135	1	26	model	model	NOUN
ijassa-135	1	27	is	be	AUX
ijassa-135	1	28	applied	apply	VERB
ijassa-135	1	29	in	in	ADP
ijassa-135	1	30	complex	complex	ADJ
ijassa-135	1	31	systems	system	NOUN
ijassa-135	1	32	evaluation	evaluation	NOUN
ijassa-135	1	33	and	and	CCONJ
ijassa-135	1	34	estimation	estimation	NOUN
ijassa-135	1	35	xiaojun	xiaojun	PROPN
ijassa-135	1	36	duan1	duan1	PROPN
ijassa-135	1	37	and	and	CCONJ
ijassa-135	1	38	yi	yi	PROPN
ijassa-135	1	39	lin2	lin2	PROPN
ijassa-135	1	40	1department	1department	NUM
ijassa-135	1	41	of	of	ADP
ijassa-135	1	42	mathematics	mathematic	NOUN
ijassa-135	1	43	and	and	CCONJ
ijassa-135	1	44	systems	system	NOUN
ijassa-135	1	45	science	science	PROPN
ijassa-135	1	46	national	national	PROPN
ijassa-135	1	47	university	university	PROPN
ijassa-135	1	48	of	of	ADP
ijassa-135	1	49	defense	defense	PROPN
ijassa-135	1	50	technology	technology	PROPN
ijassa-135	1	51	changsha	changsha	PROPN
ijassa-135	1	52	410073	410073	NUM
ijassa-135	1	53	,	,	PUNCT
ijassa-135	1	54	pr	pr	ADP
ijassa-135	1	55	china	china	PROPN
ijassa-135	2	1	2department	2department	NUM
ijassa-135	2	2	of	of	ADP
ijassa-135	2	3	mathematics	mathematics	PROPN
ijassa-135	2	4	slippery	slippery	PROPN
ijassa-135	2	5	rock	rock	PROPN
ijassa-135	2	6	university	university	PROPN
ijassa-135	2	7	slippery	slippery	ADJ
ijassa-135	2	8	rock	rock	NOUN
ijassa-135	2	9	,	,	PUNCT
ijassa-135	2	10	pa	pa	PROPN
ijassa-135	2	11	16057	16057	NUM
ijassa-135	2	12	usa	usa	PROPN
ijassa-135	2	13	abstract	abstract	PROPN
ijassa-135	2	14	continuing	continue	VERB
ijassa-135	2	15	the	the	DET
ijassa-135	2	16	works	work	NOUN
ijassa-135	2	17	in	in	ADP
ijassa-135	2	18	literature[1	literature[1	PROPN
ijassa-135	2	19	]	]	PUNCT
ijassa-135	2	20	,	,	PUNCT
ijassa-135	2	21	we	we	PRON
ijassa-135	2	22	show	show	VERB
ijassa-135	2	23	in	in	ADP
ijassa-135	2	24	this	this	DET
ijassa-135	2	25	paper	paper	NOUN
ijassa-135	2	26	how	how	SCONJ
ijassa-135	2	27	different	different	ADJ
ijassa-135	2	28	types	type	NOUN
ijassa-135	2	29	of	of	ADP
ijassa-135	2	30	information	information	NOUN
ijassa-135	2	31	can	can	AUX
ijassa-135	2	32	be	be	AUX
ijassa-135	2	33	fused	fuse	VERB
ijassa-135	2	34	together	together	ADV
ijassa-135	2	35	consistently	consistently	ADV
ijassa-135	2	36	in	in	ADP
ijassa-135	2	37	order	order	NOUN
ijassa-135	2	38	to	to	PART
ijassa-135	2	39	produce	produce	VERB
ijassa-135	2	40	accurate	accurate	ADJ
ijassa-135	2	41	evaluations	evaluation	NOUN
ijassa-135	2	42	and	and	CCONJ
ijassa-135	2	43	estimations	estimation	NOUN
ijassa-135	2	44	for	for	ADP
ijassa-135	2	45	complex	complex	ADJ
ijassa-135	2	46	systems	system	NOUN
ijassa-135	2	47	.	.	PUNCT
ijassa-135	3	1	the	the	DET
ijassa-135	3	2	theoretical	theoretical	ADJ
ijassa-135	3	3	part	part	NOUN
ijassa-135	3	4	of	of	ADP
ijassa-135	3	5	this	this	DET
ijassa-135	3	6	presentation	presentation	NOUN
ijassa-135	3	7	is	be	AUX
ijassa-135	3	8	based	base	VERB
ijassa-135	3	9	on	on	ADP
ijassa-135	3	10	the	the	DET
ijassa-135	3	11	standard	standard	ADJ
ijassa-135	3	12	statistical	statistical	ADJ
ijassa-135	3	13	reasoning	reasoning	NOUN
ijassa-135	3	14	,	,	PUNCT
ijassa-135	3	15	while	while	SCONJ
ijassa-135	3	16	the	the	DET
ijassa-135	3	17	ending	end	VERB
ijassa-135	3	18	part	part	NOUN
ijassa-135	3	19	constructs	construct	VERB
ijassa-135	3	20	three	three	NUM
ijassa-135	3	21	case	case	NOUN
ijassa-135	3	22	studies	study	NOUN
ijassa-135	3	23	in	in	ADP
ijassa-135	3	24	order	order	NOUN
ijassa-135	3	25	to	to	PART
ijassa-135	3	26	validate	validate	VERB
ijassa-135	3	27	the	the	DET
ijassa-135	3	28	main	main	ADJ
ijassa-135	3	29	thinking	thinking	NOUN
ijassa-135	3	30	logic	logic	NOUN
ijassa-135	3	31	and	and	CCONJ
ijassa-135	3	32	results	result	NOUN
ijassa-135	3	33	obtained	obtain	VERB
ijassa-135	3	34	in	in	ADP
ijassa-135	3	35	literature[1	literature[1	PROPN
ijassa-135	3	36	]	]	PUNCT
ijassa-135	3	37	and	and	CCONJ
ijassa-135	3	38	in	in	ADP
ijassa-135	3	39	this	this	DET
ijassa-135	3	40	paper	paper	NOUN
ijassa-135	3	41	.	.	PUNCT
ijassa-135	4	1	it	it	PRON
ijassa-135	4	2	is	be	AUX
ijassa-135	4	3	shown	show	VERB
ijassa-135	4	4	that	that	SCONJ
ijassa-135	4	5	(	(	PUNCT
ijassa-135	4	6	1	1	X
ijassa-135	4	7	)	)	PUNCT
ijassa-135	4	8	for	for	ADP
ijassa-135	4	9	linear	linear	NOUN
ijassa-135	4	10	systems	system	NOUN
ijassa-135	4	11	,	,	PUNCT
ijassa-135	4	12	when	when	SCONJ
ijassa-135	4	13	fusing	fuse	VERB
ijassa-135	4	14	data	datum	NOUN
ijassa-135	4	15	of	of	ADP
ijassa-135	4	16	different	different	ADJ
ijassa-135	4	17	types	type	NOUN
ijassa-135	4	18	,	,	PUNCT
ijassa-135	4	19	the	the	DET
ijassa-135	4	20	weights	weight	NOUN
ijassa-135	4	21	placed	place	VERB
ijassa-135	4	22	on	on	ADP
ijassa-135	4	23	the	the	DET
ijassa-135	4	24	data	datum	NOUN
ijassa-135	4	25	have	have	VERB
ijassa-135	4	26	profound	profound	ADJ
ijassa-135	4	27	effects	effect	NOUN
ijassa-135	4	28	on	on	ADP
ijassa-135	4	29	the	the	DET
ijassa-135	4	30	outcomes	outcome	NOUN
ijassa-135	4	31	and	and	CCONJ
ijassa-135	4	32	the	the	DET
ijassa-135	4	33	achieved	achieve	VERB
ijassa-135	4	34	precisions	precision	NOUN
ijassa-135	4	35	,	,	PUNCT
ijassa-135	4	36	meaning	mean	VERB
ijassa-135	4	37	that	that	SCONJ
ijassa-135	4	38	in	in	ADP
ijassa-135	4	39	this	this	DET
ijassa-135	4	40	case	case	NOUN
ijassa-135	4	41	,	,	PUNCT
ijassa-135	4	42	the	the	DET
ijassa-135	4	43	unique	unique	ADJ
ijassa-135	4	44	optimal	optimal	ADJ
ijassa-135	4	45	weight	weight	NOUN
ijassa-135	4	46	matrix	matrix	NOUN
ijassa-135	4	47	is	be	AUX
ijassa-135	4	48	determined	determine	VERB
ijassa-135	4	49	by	by	ADP
ijassa-135	4	50	the	the	DET
ijassa-135	4	51	precisions	precision	NOUN
ijassa-135	4	52	of	of	ADP
ijassa-135	4	53	the	the	DET
ijassa-135	4	54	data	datum	NOUN
ijassa-135	4	55	(	(	PUNCT
ijassa-135	4	56	gauss	gauss	ADJ
ijassa-135	4	57	-	-	PUNCT
ijassa-135	4	58	markov	markov	NOUN
ijassa-135	4	59	theorem	theorem	NOUN
ijassa-135	4	60	of	of	ADP
ijassa-135	4	61	linear	linear	PROPN
ijassa-135	4	62	models	model	NOUN
ijassa-135	4	63	)	)	PUNCT
ijassa-135	4	64	;	;	PUNCT
ijassa-135	4	65	(	(	PUNCT
ijassa-135	4	66	2	2	X
ijassa-135	4	67	)	)	PUNCT
ijassa-135	4	68	for	for	ADP
ijassa-135	4	69	nonlinear	nonlinear	ADJ
ijassa-135	4	70	models	model	NOUN
ijassa-135	4	71	,	,	PUNCT
ijassa-135	4	72	when	when	SCONJ
ijassa-135	4	73	fusing	fuse	VERB
ijassa-135	4	74	heterogeneous	heterogeneous	ADJ
ijassa-135	4	75	sets	set	NOUN
ijassa-135	4	76	of	of	ADP
ijassa-135	4	77	data	datum	NOUN
ijassa-135	4	78	with	with	ADP
ijassa-135	4	79	varied	varied	ADJ
ijassa-135	4	80	scales	scale	NOUN
ijassa-135	4	81	of	of	ADP
ijassa-135	4	82	precision	precision	NOUN
ijassa-135	4	83	,	,	PUNCT
ijassa-135	4	84	the	the	DET
ijassa-135	4	85	structure	structure	NOUN
ijassa-135	4	86	of	of	ADP
ijassa-135	4	87	the	the	DET
ijassa-135	4	88	weight	weight	NOUN
ijassa-135	4	89	matrix	matrix	NOUN
ijassa-135	4	90	is	be	AUX
ijassa-135	4	91	no	no	ADV
ijassa-135	4	92	longer	long	ADV
ijassa-135	4	93	uniquely	uniquely	ADV
ijassa-135	4	94	determined	determine	VERB
ijassa-135	4	95	by	by	ADP
ijassa-135	4	96	the	the	DET
ijassa-135	4	97	precisionsbut	precisionsbut	NOUN
ijassa-135	4	98	also	also	ADV
ijassa-135	4	99	related	relate	VERB
ijassa-135	4	100	to	to	ADP
ijassa-135	4	101	the	the	DET
ijassa-135	4	102	degree	degree	NOUN
ijassa-135	4	103	of	of	ADP
ijassa-135	4	104	model	model	NOUN
ijassa-135	4	105	nonlinearity	nonlinearity	NOUN
ijassa-135	4	106	,	,	PUNCT
ijassa-135	4	107	indicating	indicate	VERB
ijassa-135	4	108	that	that	SCONJ
ijassa-135	4	109	the	the	DET
ijassa-135	4	110	classical	classical	ADJ
ijassa-135	4	111	gauss	gauss	ADJ
ijassa-135	4	112	-	-	PUNCT
ijassa-135	4	113	markov	markov	NOUN
ijassa-135	4	114	theorem	theorem	NOUN
ijassa-135	4	115	of	of	ADP
ijassa-135	4	116	linear	linear	PROPN
ijassa-135	4	117	models	model	NOUN
ijassa-135	4	118	no	no	ADV
ijassa-135	4	119	longer	long	ADV
ijassa-135	4	120	holds	hold	VERB
ijassa-135	4	121	true	true	ADJ
ijassa-135	4	122	.	.	PUNCT
ijassa-135	5	1	at	at	ADP
ijassa-135	5	2	the	the	DET
ijassa-135	5	3	same	same	ADJ
ijassa-135	5	4	time	time	NOUN
ijassa-135	5	5	,	,	PUNCT
ijassa-135	5	6	a	a	DET
ijassa-135	5	7	specific	specific	ADJ
ijassa-135	5	8	method	method	NOUN
ijassa-135	5	9	of	of	ADP
ijassa-135	5	10	determining	determine	VERB
ijassa-135	5	11	the	the	DET
ijassa-135	5	12	optimal	optimal	ADJ
ijassa-135	5	13	weighting	weighting	NOUN
ijassa-135	5	14	factor	factor	NOUN
ijassa-135	5	15	and	and	CCONJ
ijassa-135	5	16	the	the	DET
ijassa-135	5	17	relevant	relevant	ADJ
ijassa-135	5	18	computational	computational	ADJ
ijassa-135	5	19	method	method	NOUN
ijassa-135	5	20	for	for	ADP
ijassa-135	5	21	estimating	estimate	VERB
ijassa-135	5	22	the	the	DET
ijassa-135	5	23	parameters	parameter	NOUN
ijassa-135	5	24	are	be	AUX
ijassa-135	5	25	established	establish	VERB
ijassa-135	5	26	.	.	PUNCT
ijassa-135	6	1	combined	combine	VERB
ijassa-135	6	2	with	with	ADP
ijassa-135	6	3	the	the	DET
ijassa-135	6	4	process	process	NOUN
ijassa-135	6	5	of	of	ADP
ijassa-135	6	6	conserved	conserved	ADJ
ijassa-135	6	7	information	information	NOUN
ijassa-135	6	8	applied	apply	VERB
ijassa-135	6	9	in	in	ADP
ijassa-135	6	10	systems	system	NOUN
ijassa-135	6	11	evaluation	evaluation	NOUN
ijassa-135	6	12	,	,	PUNCT
ijassa-135	6	13	we	we	PRON
ijassa-135	6	14	provide	provide	VERB
ijassa-135	6	15	three	three	NUM
ijassa-135	6	16	case	case	NOUN
ijassa-135	6	17	studies	study	NOUN
ijassa-135	6	18	,	,	PUNCT
ijassa-135	6	19	including	include	VERB
ijassa-135	6	20	(	(	PUNCT
ijassa-135	6	21	1	1	X
ijassa-135	6	22	)	)	PUNCT
ijassa-135	6	23	how	how	SCONJ
ijassa-135	6	24	to	to	PART
ijassa-135	6	25	quantitatively	quantitatively	ADV
ijassa-135	6	26	measure	measure	VERB
ijassa-135	6	27	prior	prior	ADJ
ijassa-135	6	28	knowledge	knowledge	NOUN
ijassa-135	6	29	and	and	CCONJ
ijassa-135	6	30	observational	observational	ADJ
ijassa-135	6	31	data	datum	NOUN
ijassa-135	6	32	so	so	SCONJ
ijassa-135	6	33	that	that	SCONJ
ijassa-135	6	34	prior	prior	ADJ
ijassa-135	6	35	knowledge	knowledge	NOUN
ijassa-135	6	36	can	can	AUX
ijassa-135	6	37	be	be	AUX
ijassa-135	6	38	considered	consider	VERB
ijassa-135	6	39	in	in	ADP
ijassa-135	6	40	obtaining	obtain	VERB
ijassa-135	6	41	much	much	ADJ
ijassa-135	6	42	improved	improve	VERB
ijassa-135	6	43	optimal	optimal	ADJ
ijassa-135	6	44	systems	system	NOUN
ijassa-135	6	45	evaluations	evaluation	NOUN
ijassa-135	6	46	;	;	PUNCT
ijassa-135	6	47	(	(	PUNCT
ijassa-135	6	48	2	2	X
ijassa-135	6	49	)	)	PUNCT
ijassa-135	6	50	how	how	SCONJ
ijassa-135	6	51	to	to	PART
ijassa-135	6	52	excavate	excavate	VERB
ijassa-135	6	53	new	new	ADJ
ijassa-135	6	54	sources	source	NOUN
ijassa-135	6	55	of	of	ADP
ijassa-135	6	56	observational	observational	ADJ
ijassa-135	6	57	data	datum	NOUN
ijassa-135	6	58	of	of	ADP
ijassa-135	6	59	processes	process	NOUN
ijassa-135	6	60	so	so	SCONJ
ijassa-135	6	61	that	that	SCONJ
ijassa-135	6	62	the	the	DET
ijassa-135	6	63	established	establish	VERB
ijassa-135	6	64	models	model	NOUN
ijassa-135	6	65	can	can	AUX
ijassa-135	6	66	be	be	AUX
ijassa-135	6	67	validated	validate	VERB
ijassa-135	6	68	jointly	jointly	ADV
ijassa-135	6	69	using	use	VERB
ijassa-135	6	70	process	process	NOUN
ijassa-135	6	71	data	datum	NOUN
ijassa-135	6	72	collected	collect	VERB
ijassa-135	6	73	under	under	ADP
ijassa-135	6	74	different	different	ADJ
ijassa-135	6	75	test	test	NOUN
ijassa-135	6	76	environments	environment	NOUN
ijassa-135	6	77	and	and	CCONJ
ijassa-135	6	78	the	the	DET
ijassa-135	6	79	directly	directly	ADV
ijassa-135	6	80	measured	measure	VERB
ijassa-135	6	81	information	information	NOUN
ijassa-135	6	82	of	of	ADP
ijassa-135	6	83	the	the	DET
ijassa-135	6	84	specific	specific	ADJ
ijassa-135	6	85	indices	index	NOUN
ijassa-135	6	86	of	of	ADP
ijassa-135	6	87	concern	concern	NOUN
ijassa-135	6	88	in	in	ADP
ijassa-135	6	89	order	order	NOUN
ijassa-135	6	90	to	to	PART
ijassa-135	6	91	improve	improve	VERB
ijassa-135	6	92	the	the	DET
ijassa-135	6	93	quality	quality	NOUN
ijassa-135	6	94	of	of	ADP
ijassa-135	6	95	systems	system	NOUN
ijassa-135	6	96	evaluation	evaluation	NOUN
ijassa-135	6	97	and	and	CCONJ
ijassa-135	6	98	estimation	estimation	NOUN
ijassa-135	6	99	and	and	CCONJ
ijassa-135	6	100	to	to	PART
ijassa-135	6	101	obtain	obtain	VERB
ijassa-135	6	102	model	model	NOUN
ijassa-135	6	103	validation	validation	NOUN
ijassa-135	6	104	results	result	NOUN
ijassa-135	6	105	of	of	ADP
ijassa-135	6	106	better	well	ADJ
ijassa-135	6	107	accuracy	accuracy	NOUN
ijassa-135	6	108	;	;	PUNCT
ijassa-135	6	109	and	and	CCONJ
ijassa-135	6	110	(	(	PUNCT
ijassa-135	6	111	3	3	X
ijassa-135	6	112	)	)	PUNCT
ijassa-135	6	113	how	how	SCONJ
ijassa-135	6	114	to	to	PART
ijassa-135	6	115	more	more	ADV
ijassa-135	6	116	effectively	effectively	ADV
ijassa-135	6	117	fuse	fuse	VERB
ijassa-135	6	118	prior	prior	ADJ
ijassa-135	6	119	knowledge	knowledge	NOUN
ijassa-135	6	120	and	and	CCONJ
ijassa-135	6	121	heterogeneous	heterogeneous	ADJ
ijassa-135	6	122	sets	set	NOUN
ijassa-135	6	123	of	of	ADP
ijassa-135	6	124	data	datum	NOUN
ijassa-135	6	125	.	.	PUNCT
ijassa-135	7	1	all	all	PRON
ijassa-135	7	2	of	of	ADP
ijassa-135	7	3	these	these	DET
ijassa-135	7	4	case	case	NOUN
ijassa-135	7	5	studies	study	NOUN
ijassa-135	7	6	further	far	ADV
ijassa-135	7	7	witness	witness	VERB
ijassa-135	7	8	the	the	DET
ijassa-135	7	9	epistemological	epistemological	ADJ
ijassa-135	7	10	validity	validity	NOUN
ijassa-135	7	11	of	of	ADP
ijassa-135	7	12	the	the	DET
ijassa-135	7	13	information	information	NOUN
ijassa-135	7	14	conservation	conservation	NOUN
ijassa-135	7	15	existing	exist	VERB
ijassa-135	7	16	in	in	ADP
ijassa-135	7	17	the	the	DET
ijassa-135	7	18	systemic	systemic	ADJ
ijassa-135	7	19	recognition	recognition	NOUN
ijassa-135	7	20	process	process	NOUN
ijassa-135	7	21	beneath	beneath	ADP
ijassa-135	7	22	the	the	DET
ijassa-135	7	23	systems	system	NOUN
ijassa-135	7	24	model	model	NOUN
ijassa-135	7	25	description	description	NOUN
ijassa-135	7	26	,	,	PUNCT
ijassa-135	7	27	prior	prior	ADJ
ijassa-135	7	28	knowledge	knowledge	NOUN
ijassa-135	7	29	,	,	PUNCT
ijassa-135	7	30	and	and	CCONJ
ijassa-135	7	31	observational	observational	ADJ
ijassa-135	7	32	data	datum	NOUN
ijassa-135	7	33	,	,	PUNCT
ijassa-135	7	34	and	and	CCONJ
ijassa-135	7	35	their	their	PRON
ijassa-135	7	36	transformational	transformational	ADJ
ijassa-135	7	37	relationship	relationship	NOUN
ijassa-135	7	38	,	,	PUNCT
ijassa-135	7	39	as	as	SCONJ
ijassa-135	7	40	obtained	obtain	VERB
ijassa-135	7	41	in	in	ADP
ijassa-135	7	42	literature[1	literature[1	PROPN
ijassa-135	7	43	]	]	PUNCT
ijassa-135	7	44	.	.	PUNCT
ijassa-135	8	1	xiaojun	xiaojun	PROPN
ijassa-135	8	2	duan	duan	PROPN
ijassa-135	8	3	,	,	PUNCT
ijassa-135	8	4	yi	yi	PROPN
ijassa-135	8	5	lin	lin	PROPN
ijassa-135	8	6	:	:	PUNCT
ijassa-135	8	7	ways	way	NOUN
ijassa-135	8	8	of	of	ADP
ijassa-135	8	9	fusing	fuse	VERB
ijassa-135	8	10	different	different	ADJ
ijassa-135	8	11	types	type	NOUN
ijassa-135	8	12	of	of	ADP
ijassa-135	8	13	information	information	NOUN
ijassa-135	8	14	and	and	CCONJ
ijassa-135	8	15	how	how	SCONJ
ijassa-135	8	16	systemic	systemic	ADJ
ijassa-135	8	17	...	...	PUNCT
ijassa-135	8	18	234	234	NUM
ijassa-135	8	19	because	because	SCONJ
ijassa-135	8	20	other	other	ADJ
ijassa-135	8	21	than	than	ADP
ijassa-135	8	22	establishing	establish	VERB
ijassa-135	8	23	the	the	DET
ijassa-135	8	24	theory	theory	NOUN
ijassa-135	8	25	,	,	PUNCT
ijassa-135	8	26	particular	particular	ADJ
ijassa-135	8	27	procedures	procedure	NOUN
ijassa-135	8	28	are	be	AUX
ijassa-135	8	29	provided	provide	VERB
ijassa-135	8	30	,	,	PUNCT
ijassa-135	8	31	conclusions	conclusion	NOUN
ijassa-135	8	32	of	of	ADP
ijassa-135	8	33	this	this	DET
ijassa-135	8	34	work	work	NOUN
ijassa-135	8	35	can	can	AUX
ijassa-135	8	36	be	be	AUX
ijassa-135	8	37	directly	directly	ADV
ijassa-135	8	38	employed	employ	VERB
ijassa-135	8	39	in	in	ADP
ijassa-135	8	40	system	system	NOUN
ijassa-135	8	41	evaluations	evaluation	NOUN
ijassa-135	8	42	and	and	CCONJ
ijassa-135	8	43	estimations	estimation	NOUN
ijassa-135	8	44	and	and	CCONJ
ijassa-135	8	45	related	related	ADJ
ijassa-135	8	46	works	work	NOUN
ijassa-135	8	47	.	.	PUNCT
ijassa-135	9	1	this	this	DET
ijassa-135	9	2	work	work	NOUN
ijassa-135	9	3	shows	show	VERB
ijassa-135	9	4	how	how	SCONJ
ijassa-135	9	5	systemic	systemic	ADJ
ijassa-135	9	6	thinking	thinking	NOUN
ijassa-135	9	7	can	can	AUX
ijassa-135	9	8	be	be	AUX
ijassa-135	9	9	practically	practically	ADV
ijassa-135	9	10	applied	apply	VERB
ijassa-135	9	11	to	to	PART
ijassa-135	9	12	benefit	benefit	VERB
ijassa-135	9	13	the	the	DET
ijassa-135	9	14	efforts	effort	NOUN
ijassa-135	9	15	of	of	ADP
ijassa-135	9	16	system	system	NOUN
ijassa-135	9	17	evaluation	evaluation	NOUN
ijassa-135	9	18	and	and	CCONJ
ijassa-135	9	19	model	model	NOUN
ijassa-135	9	20	estimations	estimation	NOUN
ijassa-135	9	21	involved	involve	VERB
ijassa-135	9	22	in	in	ADP
ijassa-135	9	23	various	various	ADJ
ijassa-135	9	24	engineering	engineering	NOUN
ijassa-135	9	25	projects	project	NOUN
ijassa-135	9	26	.	.	PUNCT
ijassa-135	10	1	keywords	keyword	VERB
ijassa-135	10	2	systemic	systemic	PROPN
ijassa-135	10	3	yoyo	yoyo	PROPN
ijassa-135	10	4	model	model	PROPN
ijassa-135	10	5	,	,	PUNCT
ijassa-135	10	6	data	datum	NOUN
ijassa-135	10	7	fusion	fusion	NOUN
ijassa-135	10	8	,	,	PUNCT
ijassa-135	10	9	linear	linear	ADJ
ijassa-135	10	10	/	/	SYM
ijassa-135	10	11	nonlinear	nonlinear	ADJ
ijassa-135	10	12	model	model	NOUN
ijassa-135	10	13	,	,	PUNCT
ijassa-135	10	14	parameter	parameter	NOUN
ijassa-135	10	15	estimation	estimation	NOUN
ijassa-135	10	16	,	,	PUNCT
ijassa-135	10	17	gauss	gauss	ADJ
ijassa-135	10	18	-	-	PUNCT
ijassa-135	10	19	markov	markov	NOUN
ijassa-135	10	20	theorem	theorem	VERB
ijassa-135	10	21	1	1	NUM
ijassa-135	10	22	introduction	introduction	NOUN
ijassa-135	10	23	in	in	ADP
ijassa-135	10	24	literature[1	literature[1	PROPN
ijassa-135	10	25	]	]	PUNCT
ijassa-135	10	26	,	,	PUNCT
ijassa-135	10	27	after	after	ADP
ijassa-135	10	28	clarifying	clarify	VERB
ijassa-135	10	29	the	the	DET
ijassa-135	10	30	relationship	relationship	NOUN
ijassa-135	10	31	between	between	ADP
ijassa-135	10	32	observational	observational	ADJ
ijassa-135	10	33	quantities	quantity	NOUN
ijassa-135	10	34	and	and	CCONJ
ijassa-135	10	35	the	the	DET
ijassa-135	10	36	target	target	NOUN
ijassa-135	10	37	indices	indice	VERB
ijassa-135	10	38	to	to	PART
ijassa-135	10	39	be	be	AUX
ijassa-135	10	40	measured	measure	VERB
ijassa-135	10	41	,	,	PUNCT
ijassa-135	10	42	the	the	DET
ijassa-135	10	43	systemic	systemic	ADJ
ijassa-135	10	44	yoyo	yoyo	PROPN
ijassa-135	10	45	model[2	model[2	NOUN
ijassa-135	10	46	]	]	PUNCT
ijassa-135	10	47	is	be	AUX
ijassa-135	10	48	established	establish	VERB
ijassa-135	10	49	for	for	ADP
ijassa-135	10	50	system	system	NOUN
ijassa-135	10	51	evaluations	evaluation	NOUN
ijassa-135	10	52	and	and	CCONJ
ijassa-135	10	53	estimations	estimation	NOUN
ijassa-135	10	54	(	(	PUNCT
ijassa-135	10	55	fig.1	fig.1	PROPN
ijassa-135	10	56	)	)	PUNCT
ijassa-135	10	57	,	,	PUNCT
ijassa-135	10	58	where	where	SCONJ
ijassa-135	10	59	the	the	DET
ijassa-135	10	60	form	form	NOUN
ijassa-135	10	61	of	of	ADP
ijassa-135	10	62	the	the	DET
ijassa-135	10	63	model	model	NOUN
ijassa-135	10	64	,	,	PUNCT
ijassa-135	10	65	observational	observational	ADJ
ijassa-135	10	66	data	datum	NOUN
ijassa-135	10	67	,	,	PUNCT
ijassa-135	10	68	and	and	CCONJ
ijassa-135	10	69	prior	prior	ADJ
ijassa-135	10	70	knowledge	knowledge	NOUN
ijassa-135	10	71	are	be	AUX
ijassa-135	10	72	the	the	DET
ijassa-135	10	73	main	main	ADJ
ijassa-135	10	74	sources	source	NOUN
ijassa-135	10	75	of	of	ADP
ijassa-135	10	76	information	information	NOUN
ijassa-135	10	77	useful	useful	ADJ
ijassa-135	10	78	for	for	ADP
ijassa-135	10	79	the	the	DET
ijassa-135	10	80	evaluation	evaluation	NOUN
ijassa-135	10	81	,	,	PUNCT
ijassa-135	10	82	estimation	estimation	NOUN
ijassa-135	10	83	,	,	PUNCT
ijassa-135	10	84	and	and	CCONJ
ijassa-135	10	85	prediction	prediction	NOUN
ijassa-135	10	86	of	of	ADP
ijassa-135	10	87	the	the	DET
ijassa-135	10	88	performance	performance	NOUN
ijassa-135	10	89	index	index	NOUN
ijassa-135	10	90	of	of	ADP
ijassa-135	10	91	the	the	DET
ijassa-135	10	92	system	system	NOUN
ijassa-135	10	93	to	to	PART
ijassa-135	10	94	be	be	AUX
ijassa-135	10	95	measured	measure	VERB
ijassa-135	10	96	.	.	PUNCT
ijassa-135	11	1	fig.1	fig.1	VERB
ijassa-135	11	2	the	the	DET
ijassa-135	11	3	systemic	systemic	ADJ
ijassa-135	11	4	yoyo	yoyo	PROPN
ijassa-135	11	5	model	model	NOUN
ijassa-135	11	6	for	for	ADP
ijassa-135	11	7	complex	complex	ADJ
ijassa-135	11	8	system	system	NOUN
ijassa-135	11	9	evaluation	evaluation	NOUN
ijassa-135	11	10	from	from	ADP
ijassa-135	11	11	analyzing	analyze	VERB
ijassa-135	11	12	the	the	DET
ijassa-135	11	13	characteristics	characteristic	NOUN
ijassa-135	11	14	of	of	ADP
ijassa-135	11	15	and	and	CCONJ
ijassa-135	11	16	connections	connection	NOUN
ijassa-135	11	17	between	between	ADP
ijassa-135	11	18	the	the	DET
ijassa-135	11	19	three	three	NUM
ijassa-135	11	20	main	main	ADJ
ijassa-135	11	21	sources	source	NOUN
ijassa-135	11	22	of	of	ADP
ijassa-135	11	23	information	information	NOUN
ijassa-135	11	24	,	,	PUNCT
ijassa-135	11	25	model	model	NOUN
ijassa-135	11	26	descriptions	description	NOUN
ijassa-135	11	27	,	,	PUNCT
ijassa-135	11	28	prior	prior	ADJ
ijassa-135	11	29	knowledge	knowledge	NOUN
ijassa-135	11	30	,	,	PUNCT
ijassa-135	11	31	and	and	CCONJ
ijassa-135	11	32	observational	observational	ADJ
ijassa-135	11	33	data	datum	NOUN
ijassa-135	11	34	,	,	PUNCT
ijassa-135	11	35	for	for	ADP
ijassa-135	11	36	system	system	NOUN
ijassa-135	11	37	evaluations	evaluation	NOUN
ijassa-135	11	38	and	and	CCONJ
ijassa-135	11	39	estimations	estimation	NOUN
ijassa-135	11	40	,	,	PUNCT
ijassa-135	11	41	the	the	DET
ijassa-135	11	42	following	follow	VERB
ijassa-135	11	43	conservation	conservation	NOUN
ijassa-135	11	44	law	law	NOUN
ijassa-135	11	45	of	of	ADP
ijassa-135	11	46	information	information	NOUN
ijassa-135	11	47	for	for	ADP
ijassa-135	11	48	system	system	NOUN
ijassa-135	11	49	analysis	analysis	NOUN
ijassa-135	11	50	is	be	AUX
ijassa-135	11	51	obtained	obtain	VERB
ijassa-135	11	52	.	.	PUNCT
ijassa-135	12	1	aeim	aeim	PROPN
ijassa-135	12	2	×beid	×beid	PROPN
ijassa-135	12	3	×	×	NOUN
ijassa-135	12	4	ceip	ceip	NOUN
ijassa-135	12	5	=	=	PUNCT
ijassa-135	13	1	a	a	DET
ijassa-135	13	2	(	(	PUNCT
ijassa-135	13	3	1	1	NUM
ijassa-135	13	4	)	)	PUNCT
ijassa-135	13	5	where	where	SCONJ
ijassa-135	13	6	a	a	DET
ijassa-135	13	7	,	,	PUNCT
ijassa-135	13	8	b	b	NOUN
ijassa-135	13	9	,	,	PUNCT
ijassa-135	13	10	and	and	CCONJ
ijassa-135	13	11	c	c	PROPN
ijassa-135	13	12	are	be	AUX
ijassa-135	13	13	constants	constant	NOUN
ijassa-135	13	14	,	,	PUNCT
ijassa-135	13	15	i	i	PRON
ijassa-135	13	16	m	m	VERB
ijassa-135	13	17	stands	stand	VERB
ijassa-135	13	18	for	for	ADP
ijassa-135	13	19	the	the	DET
ijassa-135	13	20	information	information	NOUN
ijassa-135	13	21	content	content	NOUN
ijassa-135	13	22	described	describe	VERB
ijassa-135	13	23	by	by	ADP
ijassa-135	13	24	the	the	DET
ijassa-135	13	25	model	model	NOUN
ijassa-135	13	26	,	,	PUNCT
ijassa-135	13	27	i	i	PROPN
ijassa-135	13	28	d	d	PROPN
ijassa-135	13	29	the	the	DET
ijassa-135	13	30	information	information	NOUN
ijassa-135	13	31	content	content	NOUN
ijassa-135	13	32	of	of	ADP
ijassa-135	13	33	the	the	DET
ijassa-135	13	34	autoptic	autoptic	ADJ
ijassa-135	13	35	test	test	NOUN
ijassa-135	13	36	data	datum	NOUN
ijassa-135	13	37	,	,	PUNCT
ijassa-135	13	38	and	and	CCONJ
ijassa-135	13	39	ip	ip	VERB
ijassa-135	13	40	the	the	DET
ijassa-135	13	41	information	information	NOUN
ijassa-135	13	42	content	content	NOUN
ijassa-135	13	43	of	of	ADP
ijassa-135	13	44	the	the	DET
ijassa-135	13	45	prior	prior	ADJ
ijassa-135	13	46	knowledge	knowledge	NOUN
ijassa-135	13	47	.	.	PUNCT
ijassa-135	14	1	the	the	DET
ijassa-135	14	2	constant	constant	ADJ
ijassa-135	14	3	a	a	PRON
ijassa-135	14	4	should	should	AUX
ijassa-135	14	5	somehow	somehow	ADV
ijassa-135	14	6	depict	depict	VERB
ijassa-135	14	7	the	the	DET
ijassa-135	14	8	minimum	minimum	NOUN
ijassa-135	14	9	amount	amount	NOUN
ijassa-135	14	10	of	of	ADP
ijassa-135	14	11	information	information	NOUN
ijassa-135	14	12	required	require	VERB
ijassa-135	14	13	to	to	PART
ijassa-135	14	14	satisfy	satisfy	VERB
ijassa-135	14	15	the	the	DET
ijassa-135	14	16	given	give	VERB
ijassa-135	14	17	precision	precision	NOUN
ijassa-135	14	18	(	(	PUNCT
ijassa-135	14	19	in	in	ADP
ijassa-135	14	20	the	the	DET
ijassa-135	14	21	estimate	estimate	NOUN
ijassa-135	14	22	of	of	ADP
ijassa-135	14	23	the	the	DET
ijassa-135	14	24	model	model	NOUN
ijassa-135	14	25	or	or	CCONJ
ijassa-135	14	26	parameters	parameter	NOUN
ijassa-135	14	27	)	)	PUNCT
ijassa-135	14	28	,	,	PUNCT
ijassa-135	14	29	where	where	SCONJ
ijassa-135	14	30	the	the	DET
ijassa-135	14	31	precision	precision	NOUN
ijassa-135	14	32	is	be	AUX
ijassa-135	14	33	235	235	NUM
ijassa-135	14	34	advances	advance	NOUN
ijassa-135	14	35	in	in	ADP
ijassa-135	14	36	systems	system	NOUN
ijassa-135	14	37	science	science	NOUN
ijassa-135	14	38	and	and	CCONJ
ijassa-135	14	39	applications	application	NOUN
ijassa-135	14	40	(	(	PUNCT
ijassa-135	14	41	2013	2013	NUM
ijassa-135	14	42	)	)	PUNCT
ijassa-135	14	43	vol.13	vol.13	NOUN
ijassa-135	14	44	no.3	no.3	VERB
ijassa-135	14	45	given	give	VERB
ijassa-135	14	46	in	in	ADP
ijassa-135	14	47	terms	term	NOUN
ijassa-135	14	48	of	of	ADP
ijassa-135	14	49	the	the	DET
ijassa-135	14	50	model	model	NOUN
ijassa-135	14	51	accuracy	accuracy	NOUN
ijassa-135	14	52	and	and	CCONJ
ijassa-135	14	53	parameter	parameter	NOUN
ijassa-135	14	54	estimation	estimation	NOUN
ijassa-135	14	55	precision	precision	NOUN
ijassa-135	14	56	.	.	PUNCT
ijassa-135	15	1	for	for	ADP
ijassa-135	15	2	the	the	DET
ijassa-135	15	3	detailed	detailed	ADJ
ijassa-135	15	4	expressions	expression	NOUN
ijassa-135	15	5	of	of	ADP
ijassa-135	15	6	i	i	PRON
ijassa-135	15	7	m	m	PROPN
ijassa-135	15	8	,	,	PUNCT
ijassa-135	15	9	i	i	PROPN
ijassa-135	15	10	d	d	PROPN
ijassa-135	15	11	,	,	PUNCT
ijassa-135	15	12	and	and	CCONJ
ijassa-135	15	13	ip	ip	VERB
ijassa-135	15	14	,	,	PUNCT
ijassa-135	15	15	see	see	VERB
ijassa-135	15	16	[	[	X
ijassa-135	15	17	1	1	NUM
ijassa-135	15	18	]	]	PUNCT
ijassa-135	15	19	.	.	PUNCT
ijassa-135	16	1	with	with	SCONJ
ijassa-135	16	2	this	this	DET
ijassa-135	16	3	law	law	NOUN
ijassa-135	16	4	of	of	ADP
ijassa-135	16	5	conservation	conservation	NOUN
ijassa-135	16	6	is	be	AUX
ijassa-135	16	7	established	establish	VERB
ijassa-135	16	8	,	,	PUNCT
ijassa-135	16	9	duan	duan	PROPN
ijassa-135	16	10	and	and	CCONJ
ijassa-135	16	11	lin	lin	PROPN
ijassa-135	16	12	use	use	VERB
ijassa-135	16	13	it	it	PRON
ijassa-135	16	14	to	to	PART
ijassa-135	16	15	investigate	investigate	VERB
ijassa-135	16	16	the	the	DET
ijassa-135	16	17	evolution	evolution	NOUN
ijassa-135	16	18	direction	direction	NOUN
ijassa-135	16	19	of	of	ADP
ijassa-135	16	20	the	the	DET
ijassa-135	16	21	process	process	NOUN
ijassa-135	16	22	of	of	ADP
ijassa-135	16	23	a	a	DET
ijassa-135	16	24	system	system	NOUN
ijassa-135	16	25	evaluation	evaluation	NOUN
ijassa-135	16	26	and	and	CCONJ
ijassa-135	16	27	estimation	estimation	NOUN
ijassa-135	16	28	.	.	PUNCT
ijassa-135	17	1	continuing	continue	VERB
ijassa-135	17	2	what	what	PRON
ijassa-135	17	3	is	be	AUX
ijassa-135	17	4	obtained	obtain	VERB
ijassa-135	17	5	in	in	ADP
ijassa-135	17	6	literature[1	literature[1	PROPN
ijassa-135	17	7	]	]	PUNCT
ijassa-135	17	8	,	,	PUNCT
ijassa-135	17	9	in	in	ADP
ijassa-135	17	10	this	this	DET
ijassa-135	17	11	paper	paper	NOUN
ijassa-135	17	12	,	,	PUNCT
ijassa-135	17	13	we	we	PRON
ijassa-135	17	14	show	show	VERB
ijassa-135	17	15	that	that	SCONJ
ijassa-135	17	16	for	for	ADP
ijassa-135	17	17	linear	linear	PROPN
ijassa-135	17	18	systems	system	NOUN
ijassa-135	17	19	,	,	PUNCT
ijassa-135	17	20	when	when	SCONJ
ijassa-135	17	21	different	different	ADJ
ijassa-135	17	22	types	type	NOUN
ijassa-135	17	23	of	of	ADP
ijassa-135	17	24	data	datum	NOUN
ijassa-135	17	25	are	be	AUX
ijassa-135	17	26	available	available	ADJ
ijassa-135	17	27	for	for	ADP
ijassa-135	17	28	systems	system	NOUN
ijassa-135	17	29	evaluation	evaluation	NOUN
ijassa-135	17	30	and	and	CCONJ
ijassa-135	17	31	estimation	estimation	NOUN
ijassa-135	17	32	,	,	PUNCT
ijassa-135	17	33	then	then	ADV
ijassa-135	17	34	the	the	DET
ijassa-135	17	35	analysis	analysis	NOUN
ijassa-135	17	36	outcomes	outcome	NOUN
ijassa-135	17	37	and	and	CCONJ
ijassa-135	17	38	precisions	precision	NOUN
ijassa-135	17	39	achieved	achieve	VERB
ijassa-135	17	40	are	be	AUX
ijassa-135	17	41	greatly	greatly	ADV
ijassa-135	17	42	determined	determine	VERB
ijassa-135	17	43	by	by	ADP
ijassa-135	17	44	the	the	DET
ijassa-135	17	45	weights	weight	NOUN
ijassa-135	17	46	placed	place	VERB
ijassa-135	17	47	on	on	ADP
ijassa-135	17	48	the	the	DET
ijassa-135	17	49	data	datum	NOUN
ijassa-135	17	50	.	.	PUNCT
ijassa-135	18	1	more	more	ADV
ijassa-135	18	2	specifically	specifically	ADV
ijassa-135	18	3	,	,	PUNCT
ijassa-135	18	4	the	the	DET
ijassa-135	18	5	gauss	gaus	VERB
ijassa-135	18	6	-	-	PUNCT
ijassa-135	18	7	markov	markov	NOUN
ijassa-135	18	8	theorem	theorem	NOUN
ijassa-135	18	9	,	,	PUNCT
ijassa-135	18	10	established	establish	VERB
ijassa-135	18	11	on	on	ADP
ijassa-135	18	12	the	the	DET
ijassa-135	18	13	method	method	NOUN
ijassa-135	18	14	of	of	ADP
ijassa-135	18	15	least	least	ADJ
ijassa-135	18	16	squares	square	NOUN
ijassa-135	18	17	method	method	NOUN
ijassa-135	18	18	,	,	PUNCT
ijassa-135	18	19	holds	hold	VERB
ijassa-135	18	20	true	true	ADJ
ijassa-135	18	21	.	.	PUNCT
ijassa-135	19	1	however	however	ADV
ijassa-135	19	2	,	,	PUNCT
ijassa-135	19	3	when	when	SCONJ
ijassa-135	19	4	nonlinear	nonlinear	ADJ
ijassa-135	19	5	systems	system	NOUN
ijassa-135	19	6	are	be	AUX
ijassa-135	19	7	involved	involve	VERB
ijassa-135	19	8	,	,	PUNCT
ijassa-135	19	9	the	the	DET
ijassa-135	19	10	classical	classical	ADJ
ijassa-135	19	11	gauss	gauss	ADJ
ijassa-135	19	12	-	-	PUNCT
ijassa-135	19	13	markov	markov	NOUN
ijassa-135	19	14	theorem	theorem	NOUN
ijassa-135	19	15	of	of	ADP
ijassa-135	19	16	linear	linear	PROPN
ijassa-135	19	17	models	model	NOUN
ijassa-135	19	18	no	no	ADV
ijassa-135	19	19	longer	long	ADV
ijassa-135	19	20	holds	hold	VERB
ijassa-135	19	21	.	.	PUNCT
ijassa-135	20	1	that	that	PRON
ijassa-135	20	2	is	is	ADV
ijassa-135	20	3	,	,	PUNCT
ijassa-135	20	4	the	the	DET
ijassa-135	20	5	structure	structure	NOUN
ijassa-135	20	6	of	of	ADP
ijassa-135	20	7	the	the	DET
ijassa-135	20	8	weight	weight	NOUN
ijassa-135	20	9	matrix	matrix	NOUN
ijassa-135	20	10	is	be	AUX
ijassa-135	20	11	not	not	PART
ijassa-135	20	12	uniquely	uniquely	ADV
ijassa-135	20	13	determined	determine	VERB
ijassa-135	20	14	by	by	ADP
ijassa-135	20	15	the	the	DET
ijassa-135	20	16	precisions	precision	NOUN
ijassa-135	20	17	of	of	ADP
ijassa-135	20	18	the	the	DET
ijassa-135	20	19	available	available	ADJ
ijassa-135	20	20	data	datum	NOUN
ijassa-135	20	21	.	.	PUNCT
ijassa-135	21	1	to	to	ADP
ijassa-135	21	2	this	this	DET
ijassa-135	21	3	end	end	NOUN
ijassa-135	21	4	,	,	PUNCT
ijassa-135	21	5	we	we	PRON
ijassa-135	21	6	provide	provide	VERB
ijassa-135	21	7	a	a	DET
ijassa-135	21	8	specific	specific	ADJ
ijassa-135	21	9	method	method	NOUN
ijassa-135	21	10	of	of	ADP
ijassa-135	21	11	determining	determine	VERB
ijassa-135	21	12	the	the	DET
ijassa-135	21	13	optimal	optimal	ADJ
ijassa-135	21	14	weighting	weighting	NOUN
ijassa-135	21	15	factor	factor	NOUN
ijassa-135	21	16	and	and	CCONJ
ijassa-135	21	17	the	the	DET
ijassa-135	21	18	relevant	relevant	ADJ
ijassa-135	21	19	computational	computational	ADJ
ijassa-135	21	20	method	method	NOUN
ijassa-135	21	21	for	for	ADP
ijassa-135	21	22	estimating	estimate	VERB
ijassa-135	21	23	the	the	DET
ijassa-135	21	24	parameters	parameter	NOUN
ijassa-135	21	25	.	.	PUNCT
ijassa-135	22	1	after	after	ADP
ijassa-135	22	2	this	this	DET
ijassa-135	22	3	theoretical	theoretical	ADJ
ijassa-135	22	4	exploration	exploration	NOUN
ijassa-135	22	5	,	,	PUNCT
ijassa-135	22	6	combined	combine	VERB
ijassa-135	22	7	with	with	ADP
ijassa-135	22	8	the	the	DET
ijassa-135	22	9	conservation	conservation	NOUN
ijassa-135	22	10	law	law	NOUN
ijassa-135	22	11	of	of	ADP
ijassa-135	22	12	information	information	NOUN
ijassa-135	22	13	of	of	ADP
ijassa-135	22	14	system	system	NOUN
ijassa-135	22	15	evaluations	evaluation	NOUN
ijassa-135	22	16	and	and	CCONJ
ijassa-135	22	17	estimations	estimation	NOUN
ijassa-135	22	18	,	,	PUNCT
ijassa-135	22	19	we	we	PRON
ijassa-135	22	20	construct	construct	VERB
ijassa-135	22	21	three	three	NUM
ijassa-135	22	22	case	case	NOUN
ijassa-135	22	23	studies	study	NOUN
ijassa-135	22	24	to	to	PART
ijassa-135	22	25	show	show	VERB
ijassa-135	22	26	(	(	PUNCT
ijassa-135	22	27	1)how	1)how	NUM
ijassa-135	22	28	to	to	PART
ijassa-135	22	29	quantitatively	quantitatively	ADV
ijassa-135	22	30	measure	measure	VERB
ijassa-135	22	31	prior	prior	ADJ
ijassa-135	22	32	knowledge	knowledge	NOUN
ijassa-135	22	33	and	and	CCONJ
ijassa-135	22	34	observational	observational	ADJ
ijassa-135	22	35	data	datum	NOUN
ijassa-135	22	36	so	so	SCONJ
ijassa-135	22	37	that	that	SCONJ
ijassa-135	22	38	better	well	ADJ
ijassa-135	22	39	evaluation	evaluation	NOUN
ijassa-135	22	40	and	and	CCONJ
ijassa-135	22	41	estimation	estimation	NOUN
ijassa-135	22	42	results	result	NOUN
ijassa-135	22	43	can	can	AUX
ijassa-135	22	44	be	be	AUX
ijassa-135	22	45	obtained	obtain	VERB
ijassa-135	22	46	using	use	VERB
ijassa-135	22	47	prior	prior	ADJ
ijassa-135	22	48	knowledge	knowledge	NOUN
ijassa-135	22	49	;	;	PUNCT
ijassa-135	22	50	(	(	PUNCT
ijassa-135	22	51	2)how	2)how	NUM
ijassa-135	22	52	to	to	PART
ijassa-135	22	53	excavate	excavate	VERB
ijassa-135	22	54	the	the	DET
ijassa-135	22	55	available	available	ADJ
ijassa-135	22	56	observational	observational	ADJ
ijassa-135	22	57	data	datum	NOUN
ijassa-135	22	58	of	of	ADP
ijassa-135	22	59	processes	process	NOUN
ijassa-135	22	60	so	so	SCONJ
ijassa-135	22	61	that	that	SCONJ
ijassa-135	22	62	the	the	DET
ijassa-135	22	63	process	process	NOUN
ijassa-135	22	64	information	information	NOUN
ijassa-135	22	65	collected	collect	VERB
ijassa-135	22	66	under	under	ADP
ijassa-135	22	67	different	different	ADJ
ijassa-135	22	68	test	test	NOUN
ijassa-135	22	69	environments	environment	NOUN
ijassa-135	22	70	and	and	CCONJ
ijassa-135	22	71	directly	directly	ADV
ijassa-135	22	72	measured	measure	VERB
ijassa-135	22	73	data	datum	NOUN
ijassa-135	22	74	of	of	ADP
ijassa-135	22	75	the	the	DET
ijassa-135	22	76	specific	specific	ADJ
ijassa-135	22	77	indices	index	NOUN
ijassa-135	22	78	can	can	AUX
ijassa-135	22	79	be	be	AUX
ijassa-135	22	80	employed	employ	VERB
ijassa-135	22	81	jointly	jointly	ADV
ijassa-135	22	82	to	to	ADP
ijassa-135	22	83	fine	fine	ADJ
ijassa-135	22	84	-	-	PUNCT
ijassa-135	22	85	tune	tune	NOUN
ijassa-135	22	86	the	the	DET
ijassa-135	22	87	model	model	NOUN
ijassa-135	22	88	,	,	PUNCT
ijassa-135	22	89	leading	lead	VERB
ijassa-135	22	90	to	to	ADP
ijassa-135	22	91	improved	improved	ADJ
ijassa-135	22	92	system	system	NOUN
ijassa-135	22	93	evaluations	evaluation	NOUN
ijassa-135	22	94	,	,	PUNCT
ijassa-135	22	95	estimations	estimation	NOUN
ijassa-135	22	96	,	,	PUNCT
ijassa-135	22	97	and	and	CCONJ
ijassa-135	22	98	more	more	ADV
ijassa-135	22	99	accurate	accurate	ADJ
ijassa-135	22	100	test	test	NOUN
ijassa-135	22	101	results	result	NOUN
ijassa-135	22	102	,	,	PUNCT
ijassa-135	22	103	and	and	CCONJ
ijassa-135	22	104	(	(	PUNCT
ijassa-135	22	105	3)how	3)how	NUM
ijassa-135	22	106	to	to	PART
ijassa-135	22	107	make	make	VERB
ijassa-135	22	108	prior	prior	ADJ
ijassa-135	22	109	knowledge	knowledge	NOUN
ijassa-135	22	110	and	and	CCONJ
ijassa-135	22	111	heterogeneous	heterogeneous	ADJ
ijassa-135	22	112	sets	set	NOUN
ijassa-135	22	113	of	of	ADP
ijassa-135	22	114	data	datum	NOUN
ijassa-135	22	115	work	work	VERB
ijassa-135	22	116	effectively	effectively	ADV
ijassa-135	22	117	together	together	ADV
ijassa-135	22	118	.	.	PUNCT
ijassa-135	23	1	these	these	DET
ijassa-135	23	2	case	case	NOUN
ijassa-135	23	3	studies	study	NOUN
ijassa-135	23	4	further	far	ADV
ijassa-135	23	5	verify	verify	VERB
ijassa-135	23	6	the	the	DET
ijassa-135	23	7	validity	validity	NOUN
ijassa-135	23	8	of	of	ADP
ijassa-135	23	9	the	the	DET
ijassa-135	23	10	conservation	conservation	NOUN
ijassa-135	23	11	of	of	ADP
ijassa-135	23	12	information	information	NOUN
ijassa-135	23	13	of	of	ADP
ijassa-135	23	14	the	the	DET
ijassa-135	23	15	model	model	NOUN
ijassa-135	23	16	information	information	NOUN
ijassa-135	23	17	,	,	PUNCT
ijassa-135	23	18	prior	prior	ADJ
ijassa-135	23	19	knowledge	knowledge	NOUN
ijassa-135	23	20	,	,	PUNCT
ijassa-135	23	21	and	and	CCONJ
ijassa-135	23	22	observational	observational	ADJ
ijassa-135	23	23	data	datum	NOUN
ijassa-135	23	24	in	in	ADP
ijassa-135	23	25	the	the	DET
ijassa-135	23	26	recognition	recognition	NOUN
ijassa-135	23	27	process	process	NOUN
ijassa-135	23	28	of	of	ADP
ijassa-135	23	29	systems	system	NOUN
ijassa-135	23	30	and	and	CCONJ
ijassa-135	23	31	the	the	DET
ijassa-135	23	32	evolutionary	evolutionary	ADJ
ijassa-135	23	33	relationship	relationship	NOUN
ijassa-135	23	34	between	between	ADP
ijassa-135	23	35	three	three	NUM
ijassa-135	23	36	main	main	ADJ
ijassa-135	23	37	sources	source	NOUN
ijassa-135	23	38	of	of	ADP
ijassa-135	23	39	information	information	NOUN
ijassa-135	23	40	.	.	PUNCT
ijassa-135	24	1	this	this	DET
ijassa-135	24	2	paper	paper	NOUN
ijassa-135	24	3	is	be	AUX
ijassa-135	24	4	organized	organize	VERB
ijassa-135	24	5	as	as	SCONJ
ijassa-135	24	6	follows	follow	VERB
ijassa-135	24	7	:	:	PUNCT
ijassa-135	24	8	section	section	NOUN
ijassa-135	24	9	2	2	NUM
ijassa-135	24	10	looks	look	VERB
ijassa-135	24	11	at	at	ADP
ijassa-135	24	12	various	various	ADJ
ijassa-135	24	13	ways	way	NOUN
ijassa-135	24	14	one	one	PRON
ijassa-135	24	15	can	can	AUX
ijassa-135	24	16	fuse	fuse	VERB
ijassa-135	24	17	information	information	NOUN
ijassa-135	24	18	in	in	ADP
ijassa-135	24	19	his	his	PRON
ijassa-135	24	20	analysis	analysis	NOUN
ijassa-135	24	21	of	of	ADP
ijassa-135	24	22	complex	complex	ADJ
ijassa-135	24	23	systems	system	NOUN
ijassa-135	24	24	.	.	PUNCT
ijassa-135	25	1	section	section	NOUN
ijassa-135	25	2	3	3	NUM
ijassa-135	25	3	focuses	focus	VERB
ijassa-135	25	4	on	on	ADP
ijassa-135	25	5	three	three	NUM
ijassa-135	25	6	specific	specific	ADJ
ijassa-135	25	7	cases	case	NOUN
ijassa-135	25	8	studies	study	NOUN
ijassa-135	25	9	.	.	PUNCT
ijassa-135	26	1	and	and	CCONJ
ijassa-135	26	2	,	,	PUNCT
ijassa-135	26	3	the	the	DET
ijassa-135	26	4	paper	paper	NOUN
ijassa-135	26	5	is	be	AUX
ijassa-135	26	6	concluded	conclude	VERB
ijassa-135	26	7	by	by	ADP
ijassa-135	26	8	section	section	NOUN
ijassa-135	26	9	4	4	NUM
ijassa-135	26	10	.	.	NOUN
ijassa-135	26	11	2	2	NUM
ijassa-135	26	12	ways	way	NOUN
ijassa-135	26	13	information	information	NOUN
ijassa-135	26	14	fusion	fusion	NOUN
ijassa-135	26	15	takes	take	VERB
ijassa-135	26	16	place	place	NOUN
ijassa-135	26	17	in	in	ADP
ijassa-135	26	18	processes	process	NOUN
ijassa-135	26	19	of	of	ADP
ijassa-135	26	20	system	system	NOUN
ijassa-135	26	21	evaluation	evaluation	NOUN
ijassa-135	26	22	with	with	ADP
ijassa-135	26	23	the	the	DET
ijassa-135	26	24	requirement	requirement	NOUN
ijassa-135	26	25	of	of	ADP
ijassa-135	26	26	precision	precision	NOUN
ijassa-135	26	27	given	give	VERB
ijassa-135	26	28	,	,	PUNCT
ijassa-135	26	29	we	we	PRON
ijassa-135	26	30	can	can	AUX
ijassa-135	26	31	optimize	optimize	VERB
ijassa-135	26	32	the	the	DET
ijassa-135	26	33	process	process	NOUN
ijassa-135	26	34	of	of	ADP
ijassa-135	26	35	a	a	DET
ijassa-135	26	36	system	system	NOUN
ijassa-135	26	37	evaluation	evaluation	NOUN
ijassa-135	26	38	.	.	PUNCT
ijassa-135	27	1	that	that	PRON
ijassa-135	27	2	is	be	AUX
ijassa-135	27	3	such	such	DET
ijassa-135	27	4	a	a	DET
ijassa-135	27	5	problem	problem	NOUN
ijassa-135	27	6	as	as	ADP
ijassa-135	27	7	how	how	SCONJ
ijassa-135	27	8	to	to	PART
ijassa-135	27	9	obtain	obtain	VERB
ijassa-135	27	10	the	the	DET
ijassa-135	27	11	optimal	optimal	ADJ
ijassa-135	27	12	evaluation	evaluation	NOUN
ijassa-135	27	13	results	result	NOUN
ijassa-135	27	14	when	when	SCONJ
ijassa-135	27	15	multiple	multiple	ADJ
ijassa-135	27	16	types	type	NOUN
ijassa-135	27	17	of	of	ADP
ijassa-135	27	18	models	model	NOUN
ijassa-135	27	19	and	and	CCONJ
ijassa-135	27	20	multiple	multiple	ADJ
ijassa-135	27	21	kinds	kind	NOUN
ijassa-135	27	22	of	of	ADP
ijassa-135	27	23	data	datum	NOUN
ijassa-135	27	24	are	be	AUX
ijassa-135	27	25	available	available	ADJ
ijassa-135	27	26	.	.	PUNCT
ijassa-135	28	1	this	this	DET
ijassa-135	28	2	end	end	NOUN
ijassa-135	28	3	can	can	AUX
ijassa-135	28	4	be	be	AUX
ijassa-135	28	5	analyzed	analyze	VERB
ijassa-135	28	6	by	by	ADP
ijassa-135	28	7	placing	place	VERB
ijassa-135	28	8	various	various	ADJ
ijassa-135	28	9	weights	weight	NOUN
ijassa-135	28	10	on	on	ADP
ijassa-135	28	11	the	the	DET
ijassa-135	28	12	multiple	multiple	ADJ
ijassa-135	28	13	kinds	kind	NOUN
ijassa-135	28	14	of	of	ADP
ijassa-135	28	15	data	datum	NOUN
ijassa-135	28	16	and	and	CCONJ
ijassa-135	28	17	prior	prior	ADJ
ijassa-135	28	18	information	information	NOUN
ijassa-135	28	19	.	.	PUNCT
ijassa-135	29	1	xiaojun	xiaojun	PROPN
ijassa-135	29	2	duan	duan	PROPN
ijassa-135	29	3	,	,	PUNCT
ijassa-135	29	4	yi	yi	PROPN
ijassa-135	29	5	lin	lin	PROPN
ijassa-135	29	6	:	:	PUNCT
ijassa-135	29	7	ways	way	NOUN
ijassa-135	29	8	of	of	ADP
ijassa-135	29	9	fusing	fuse	VERB
ijassa-135	29	10	different	different	ADJ
ijassa-135	29	11	types	type	NOUN
ijassa-135	29	12	of	of	ADP
ijassa-135	29	13	information	information	NOUN
ijassa-135	29	14	and	and	CCONJ
ijassa-135	29	15	how	how	SCONJ
ijassa-135	29	16	systemic	systemic	ADJ
ijassa-135	29	17	...	...	PUNCT
ijassa-135	29	18	236	236	NUM
ijassa-135	29	19	when	when	SCONJ
ijassa-135	29	20	dealing	deal	VERB
ijassa-135	29	21	with	with	ADP
ijassa-135	29	22	information	information	NOUN
ijassa-135	29	23	by	by	ADP
ijassa-135	29	24	combining	combine	VERB
ijassa-135	29	25	heterogeneous	heterogeneous	ADJ
ijassa-135	29	26	data	datum	NOUN
ijassa-135	29	27	,	,	PUNCT
ijassa-135	29	28	the	the	DET
ijassa-135	29	29	most	most	ADV
ijassa-135	29	30	typical	typical	ADJ
ijassa-135	29	31	case	case	NOUN
ijassa-135	29	32	is	be	AUX
ijassa-135	29	33	the	the	DET
ijassa-135	29	34	fusion	fusion	NOUN
ijassa-135	29	35	of	of	ADP
ijassa-135	29	36	such	such	ADJ
ijassa-135	29	37	information	information	NOUN
ijassa-135	29	38	that	that	PRON
ijassa-135	29	39	are	be	AUX
ijassa-135	29	40	of	of	ADP
ijassa-135	29	41	different	different	ADJ
ijassa-135	29	42	types	type	NOUN
ijassa-135	29	43	and	and	CCONJ
ijassa-135	29	44	various	various	ADJ
ijassa-135	29	45	precisions	precision	NOUN
ijassa-135	29	46	.	.	PUNCT
ijassa-135	30	1	when	when	SCONJ
ijassa-135	30	2	observational	observational	ADJ
ijassa-135	30	3	information	information	NOUN
ijassa-135	30	4	is	be	AUX
ijassa-135	30	5	expressed	express	VERB
ijassa-135	30	6	by	by	ADP
ijassa-135	30	7	using	use	VERB
ijassa-135	30	8	a	a	DET
ijassa-135	30	9	parametric	parametric	ADJ
ijassa-135	30	10	model	model	NOUN
ijassa-135	30	11	,	,	PUNCT
ijassa-135	30	12	the	the	DET
ijassa-135	30	13	problem	problem	NOUN
ijassa-135	30	14	of	of	ADP
ijassa-135	30	15	how	how	SCONJ
ijassa-135	30	16	to	to	PART
ijassa-135	30	17	fuse	fuse	VERB
ijassa-135	30	18	the	the	DET
ijassa-135	30	19	information	information	NOUN
ijassa-135	30	20	together	together	ADV
ijassa-135	30	21	can	can	AUX
ijassa-135	30	22	be	be	AUX
ijassa-135	30	23	transformed	transform	VERB
ijassa-135	30	24	into	into	ADP
ijassa-135	30	25	that	that	PRON
ijassa-135	30	26	of	of	ADP
ijassa-135	30	27	estimating	estimate	VERB
ijassa-135	30	28	the	the	DET
ijassa-135	30	29	parameters	parameter	NOUN
ijassa-135	30	30	of	of	ADP
ijassa-135	30	31	some	some	DET
ijassa-135	30	32	regression	regression	NOUN
ijassa-135	30	33	models	model	NOUN
ijassa-135	30	34	.	.	PUNCT
ijassa-135	31	1	here	here	ADV
ijassa-135	31	2	,	,	PUNCT
ijassa-135	31	3	by	by	ADP
ijassa-135	31	4	different	different	ADJ
ijassa-135	31	5	types	type	NOUN
ijassa-135	31	6	of	of	ADP
ijassa-135	31	7	information	information	NOUN
ijassa-135	31	8	,	,	PUNCT
ijassa-135	31	9	we	we	PRON
ijassa-135	31	10	mean	mean	VERB
ijassa-135	31	11	such	such	ADJ
ijassa-135	31	12	information	information	NOUN
ijassa-135	31	13	that	that	PRON
ijassa-135	31	14	is	be	AUX
ijassa-135	31	15	of	of	ADP
ijassa-135	31	16	different	different	ADJ
ijassa-135	31	17	functional	functional	ADJ
ijassa-135	31	18	relationships	relationship	NOUN
ijassa-135	31	19	with	with	ADP
ijassa-135	31	20	the	the	DET
ijassa-135	31	21	parameters	parameter	NOUN
ijassa-135	31	22	to	to	PART
ijassa-135	31	23	be	be	AUX
ijassa-135	31	24	estimated	estimate	VERB
ijassa-135	31	25	so	so	SCONJ
ijassa-135	31	26	that	that	SCONJ
ijassa-135	31	27	their	their	PRON
ijassa-135	31	28	various	various	ADJ
ijassa-135	31	29	orders	order	NOUN
ijassa-135	31	30	of	of	ADP
ijassa-135	31	31	derivatives	derivative	NOUN
ijassa-135	31	32	are	be	AUX
ijassa-135	31	33	also	also	ADV
ijassa-135	31	34	different	different	ADJ
ijassa-135	31	35	.	.	PUNCT
ijassa-135	32	1	if	if	SCONJ
ijassa-135	32	2	in	in	ADP
ijassa-135	32	3	our	our	PRON
ijassa-135	32	4	treatment	treatment	NOUN
ijassa-135	32	5	we	we	PRON
ijassa-135	32	6	have	have	VERB
ijassa-135	32	7	to	to	PART
ijassa-135	32	8	deal	deal	VERB
ijassa-135	32	9	with	with	ADP
ijassa-135	32	10	different	different	ADJ
ijassa-135	32	11	types	type	NOUN
ijassa-135	32	12	of	of	ADP
ijassa-135	32	13	information	information	NOUN
ijassa-135	32	14	of	of	ADP
ijassa-135	32	15	varying	vary	VERB
ijassa-135	32	16	precision	precision	NOUN
ijassa-135	32	17	,	,	PUNCT
ijassa-135	32	18	different	different	ADJ
ijassa-135	32	19	weightings	weighting	NOUN
ijassa-135	32	20	placed	place	VERB
ijassa-135	32	21	on	on	ADP
ijassa-135	32	22	these	these	DET
ijassa-135	32	23	information	information	NOUN
ijassa-135	32	24	will	will	AUX
ijassa-135	32	25	have	have	VERB
ijassa-135	32	26	direct	direct	ADJ
ijassa-135	32	27	effect	effect	NOUN
ijassa-135	32	28	on	on	ADP
ijassa-135	32	29	the	the	DET
ijassa-135	32	30	estimations	estimation	NOUN
ijassa-135	32	31	of	of	ADP
ijassa-135	32	32	the	the	DET
ijassa-135	32	33	parameters	parameter	NOUN
ijassa-135	32	34	.	.	PUNCT
ijassa-135	33	1	sometimes	sometimes	ADV
ijassa-135	33	2	,	,	PUNCT
ijassa-135	33	3	the	the	DET
ijassa-135	33	4	effects	effect	NOUN
ijassa-135	33	5	can	can	AUX
ijassa-135	33	6	also	also	ADV
ijassa-135	33	7	be	be	AUX
ijassa-135	33	8	quite	quite	ADV
ijassa-135	33	9	significant	significant	ADJ
ijassa-135	33	10	.	.	PUNCT
ijassa-135	34	1	hence	hence	ADV
ijassa-135	34	2	,	,	PUNCT
ijassa-135	34	3	how	how	SCONJ
ijassa-135	34	4	to	to	PART
ijassa-135	34	5	place	place	VERB
ijassa-135	34	6	weights	weight	NOUN
ijassa-135	34	7	on	on	ADP
ijassa-135	34	8	the	the	DET
ijassa-135	34	9	information	information	NOUN
ijassa-135	34	10	that	that	PRON
ijassa-135	34	11	are	be	AUX
ijassa-135	34	12	of	of	ADP
ijassa-135	34	13	heterogeneous	heterogeneous	ADJ
ijassa-135	34	14	types	type	NOUN
ijassa-135	34	15	and	and	CCONJ
ijassa-135	34	16	varied	varied	ADJ
ijassa-135	34	17	precisions	precision	NOUN
ijassa-135	34	18	becomes	become	VERB
ijassa-135	34	19	a	a	DET
ijassa-135	34	20	key	key	ADJ
ijassa-135	34	21	technique	technique	NOUN
ijassa-135	34	22	for	for	ADP
ijassa-135	34	23	obtaining	obtain	VERB
ijassa-135	34	24	high	high	ADJ
ijassa-135	34	25	accuracies	accuracy	NOUN
ijassa-135	34	26	in	in	ADP
ijassa-135	34	27	the	the	DET
ijassa-135	34	28	parameter	parameter	NOUN
ijassa-135	34	29	estimations	estimation	NOUN
ijassa-135	34	30	.	.	PUNCT
ijassa-135	35	1	as	as	ADP
ijassa-135	35	2	for	for	ADP
ijassa-135	35	3	the	the	DET
ijassa-135	35	4	parameter	parameter	NOUN
ijassa-135	35	5	estimations	estimation	NOUN
ijassa-135	35	6	of	of	ADP
ijassa-135	35	7	linear	linear	PROPN
ijassa-135	35	8	regression	regression	NOUN
ijassa-135	35	9	models	model	NOUN
ijassa-135	35	10	,	,	PUNCT
ijassa-135	35	11	gauss	gauss	ADJ
ijassa-135	35	12	-	-	PUNCT
ijassa-135	35	13	markov	markov	NOUN
ijassa-135	35	14	theorem	theorem	NOUN
ijassa-135	35	15	provides	provide	VERB
ijassa-135	35	16	the	the	DET
ijassa-135	35	17	most	most	ADV
ijassa-135	35	18	optimal	optimal	ADJ
ijassa-135	35	19	weighting	weighting	NOUN
ijassa-135	35	20	method	method	NOUN
ijassa-135	35	21	for	for	ADP
ijassa-135	35	22	observational	observational	ADJ
ijassa-135	35	23	data	datum	NOUN
ijassa-135	35	24	of	of	ADP
ijassa-135	35	25	different	different	ADJ
ijassa-135	35	26	precisions	precision	NOUN
ijassa-135	35	27	[	[	X
ijassa-135	35	28	3	3	NUM
ijassa-135	35	29	]	]	PUNCT
ijassa-135	35	30	.	.	PUNCT
ijassa-135	36	1	as	as	ADP
ijassa-135	36	2	for	for	ADP
ijassa-135	36	3	nonlinear	nonlinear	ADJ
ijassa-135	36	4	regression	regression	NOUN
ijassa-135	36	5	models	model	NOUN
ijassa-135	36	6	,	,	PUNCT
ijassa-135	36	7	current	current	ADJ
ijassa-135	36	8	publications	publication	NOUN
ijassa-135	36	9	have	have	AUX
ijassa-135	36	10	assumed	assume	VERB
ijassa-135	36	11	that	that	SCONJ
ijassa-135	36	12	all	all	DET
ijassa-135	36	13	observational	observational	ADJ
ijassa-135	36	14	data	datum	NOUN
ijassa-135	36	15	have	have	VERB
ijassa-135	36	16	the	the	DET
ijassa-135	36	17	same	same	ADJ
ijassa-135	36	18	scale	scale	NOUN
ijassa-135	36	19	of	of	ADP
ijassa-135	36	20	precision	precision	NOUN
ijassa-135	36	21	.	.	PUNCT
ijassa-135	37	1	that	that	PRON
ijassa-135	37	2	is	be	AUX
ijassa-135	37	3	,	,	PUNCT
ijassa-135	37	4	the	the	DET
ijassa-135	37	5	random	random	ADJ
ijassa-135	37	6	errors	error	NOUN
ijassa-135	37	7	in	in	ADP
ijassa-135	37	8	these	these	DET
ijassa-135	37	9	data	datum	NOUN
ijassa-135	37	10	are	be	AUX
ijassa-135	37	11	identically	identically	ADV
ijassa-135	37	12	independently	independently	ADV
ijassa-135	37	13	distributed	distribute	VERB
ijassa-135	37	14	[	[	X
ijassa-135	37	15	3	3	NUM
ijassa-135	37	16	]	]	PUNCT
ijassa-135	37	17	.	.	PUNCT
ijassa-135	38	1	to	to	ADP
ijassa-135	38	2	this	this	DET
ijassa-135	38	3	end	end	NOUN
ijassa-135	38	4	,	,	PUNCT
ijassa-135	38	5	our	our	PRON
ijassa-135	38	6	work	work	NOUN
ijassa-135	38	7	in	in	ADP
ijassa-135	38	8	this	this	DET
ijassa-135	38	9	section	section	NOUN
ijassa-135	38	10	theoretically	theoretically	ADV
ijassa-135	38	11	shows	show	VERB
ijassa-135	38	12	that	that	SCONJ
ijassa-135	38	13	when	when	SCONJ
ijassa-135	38	14	jointly	jointly	ADV
ijassa-135	38	15	dealing	deal	VERB
ijassa-135	38	16	with	with	ADP
ijassa-135	38	17	heterogeneous	heterogeneous	ADJ
ijassa-135	38	18	sets	set	NOUN
ijassa-135	38	19	of	of	ADP
ijassa-135	38	20	data	datum	NOUN
ijassa-135	38	21	of	of	ADP
ijassa-135	38	22	varied	varied	ADJ
ijassa-135	38	23	scales	scale	NOUN
ijassa-135	38	24	of	of	ADP
ijassa-135	38	25	precision	precision	NOUN
ijassa-135	38	26	,	,	PUNCT
ijassa-135	38	27	the	the	DET
ijassa-135	38	28	structure	structure	NOUN
ijassa-135	38	29	of	of	ADP
ijassa-135	38	30	the	the	DET
ijassa-135	38	31	weight	weight	NOUN
ijassa-135	38	32	matrix	matrix	NOUN
ijassa-135	38	33	is	be	AUX
ijassa-135	38	34	no	no	ADV
ijassa-135	38	35	longer	long	ADV
ijassa-135	38	36	uniquely	uniquely	ADV
ijassa-135	38	37	determined	determine	VERB
ijassa-135	38	38	by	by	ADP
ijassa-135	38	39	the	the	DET
ijassa-135	38	40	precision	precision	NOUN
ijassa-135	38	41	of	of	ADP
ijassa-135	38	42	the	the	DET
ijassa-135	38	43	observational	observational	ADJ
ijassa-135	38	44	data	datum	NOUN
ijassa-135	38	45	;	;	PUNCT
ijassa-135	38	46	instead	instead	ADV
ijassa-135	38	47	,	,	PUNCT
ijassa-135	38	48	it	it	PRON
ijassa-135	38	49	also	also	ADV
ijassa-135	38	50	has	have	VERB
ijassa-135	38	51	something	something	PRON
ijassa-135	38	52	to	to	PART
ijassa-135	38	53	do	do	VERB
ijassa-135	38	54	with	with	ADP
ijassa-135	38	55	the	the	DET
ijassa-135	38	56	degree	degree	NOUN
ijassa-135	38	57	of	of	ADP
ijassa-135	38	58	nonlinearity	nonlinearity	NOUN
ijassa-135	38	59	of	of	ADP
ijassa-135	38	60	the	the	DET
ijassa-135	38	61	model	model	NOUN
ijassa-135	38	62	,	,	PUNCT
ijassa-135	38	63	which	which	PRON
ijassa-135	38	64	can	can	AUX
ijassa-135	38	65	be	be	AUX
ijassa-135	38	66	measured	measure	VERB
ijassa-135	38	67	by	by	ADP
ijassa-135	38	68	different	different	ADJ
ijassa-135	38	69	orders	order	NOUN
ijassa-135	38	70	of	of	ADP
ijassa-135	38	71	derivative	derivative	ADJ
ijassa-135	38	72	functions	function	NOUN
ijassa-135	38	73	.	.	PUNCT
ijassa-135	39	1	that	that	PRON
ijassa-135	39	2	is	be	AUX
ijassa-135	39	3	,	,	PUNCT
ijassa-135	39	4	the	the	DET
ijassa-135	39	5	classical	classical	ADJ
ijassa-135	39	6	gauss	gauss	ADJ
ijassa-135	39	7	-	-	PUNCT
ijassa-135	39	8	markov	markov	NOUN
ijassa-135	39	9	theorem	theorem	NOUN
ijassa-135	39	10	of	of	ADP
ijassa-135	39	11	linear	linear	PROPN
ijassa-135	39	12	models	model	NOUN
ijassa-135	39	13	does	do	AUX
ijassa-135	39	14	not	not	PART
ijassa-135	39	15	hold	hold	VERB
ijassa-135	39	16	true	true	ADJ
ijassa-135	39	17	anymore	anymore	ADV
ijassa-135	39	18	.	.	PUNCT
ijassa-135	40	1	in	in	ADP
ijassa-135	40	2	the	the	DET
ijassa-135	40	3	following	following	NOUN
ijassa-135	40	4	,	,	PUNCT
ijassa-135	40	5	we	we	PRON
ijassa-135	40	6	will	will	AUX
ijassa-135	40	7	specifically	specifically	ADV
ijassa-135	40	8	address	address	VERB
ijassa-135	40	9	the	the	DET
ijassa-135	40	10	problem	problem	NOUN
ijassa-135	40	11	of	of	ADP
ijassa-135	40	12	how	how	SCONJ
ijassa-135	40	13	to	to	PART
ijassa-135	40	14	determine	determine	VERB
ijassa-135	40	15	the	the	DET
ijassa-135	40	16	most	most	ADV
ijassa-135	40	17	optimal	optimal	ADJ
ijassa-135	40	18	weighting	weighting	NOUN
ijassa-135	40	19	factor	factor	NOUN
ijassa-135	40	20	,	,	PUNCT
ijassa-135	40	21	while	while	SCONJ
ijassa-135	40	22	providing	provide	VERB
ijassa-135	40	23	the	the	DET
ijassa-135	40	24	relevant	relevant	ADJ
ijassa-135	40	25	computational	computational	ADJ
ijassa-135	40	26	method	method	NOUN
ijassa-135	40	27	for	for	ADP
ijassa-135	40	28	estimating	estimate	VERB
ijassa-135	40	29	the	the	DET
ijassa-135	40	30	parameters	parameter	NOUN
ijassa-135	40	31	.	.	PUNCT
ijassa-135	41	1	2.1	2.1	NUM
ijassa-135	41	2	the	the	DET
ijassa-135	41	3	optimally	optimally	ADV
ijassa-135	41	4	weighted	weight	VERB
ijassa-135	41	5	information	information	NOUN
ijassa-135	41	6	fusion	fusion	NOUN
ijassa-135	41	7	of	of	ADP
ijassa-135	41	8	linear	linear	ADJ
ijassa-135	41	9	system	system	NOUN
ijassa-135	41	10	evaluation	evaluation	NOUN
ijassa-135	41	11	according	accord	VERB
ijassa-135	41	12	to	to	ADP
ijassa-135	41	13	the	the	DET
ijassa-135	41	14	research	research	NOUN
ijassa-135	41	15	on	on	ADP
ijassa-135	41	16	the	the	DET
ijassa-135	41	17	mean	mean	ADJ
ijassa-135	41	18	square	square	ADJ
ijassa-135	41	19	errors	error	NOUN
ijassa-135	41	20	of	of	ADP
ijassa-135	41	21	parameter	parameter	NOUN
ijassa-135	41	22	estimations	estimation	NOUN
ijassa-135	41	23	of	of	ADP
ijassa-135	41	24	linear	linear	PROPN
ijassa-135	41	25	systems	system	NOUN
ijassa-135	41	26	,	,	PUNCT
ijassa-135	41	27	it	it	PRON
ijassa-135	41	28	is	be	AUX
ijassa-135	41	29	readily	readily	ADV
ijassa-135	41	30	to	to	PART
ijassa-135	41	31	show	show	VERB
ijassa-135	41	32	that	that	SCONJ
ijassa-135	41	33	the	the	DET
ijassa-135	41	34	estimate	estimate	NOUN
ijassa-135	41	35	corresponding	correspond	VERB
ijassa-135	41	36	to	to	ADP
ijassa-135	41	37	the	the	DET
ijassa-135	41	38	optimal	optimal	ADJ
ijassa-135	41	39	weighting	weighting	NOUN
ijassa-135	41	40	factor	factor	NOUN
ijassa-135	41	41	is	be	AUX
ijassa-135	41	42	the	the	DET
ijassa-135	41	43	bayesian	bayesian	NOUN
ijassa-135	41	44	estimation	estimation	NOUN
ijassa-135	41	45	,	,	PUNCT
ijassa-135	41	46	which	which	PRON
ijassa-135	41	47	is	be	AUX
ijassa-135	41	48	gauss	gauss	ADJ
ijassa-135	41	49	-	-	PUNCT
ijassa-135	41	50	markov	markov	NOUN
ijassa-135	41	51	theorem[1,6	theorem[1,6	PROPN
ijassa-135	41	52	]	]	PUNCT
ijassa-135	41	53	.	.	PUNCT
ijassa-135	42	1	for	for	ADP
ijassa-135	42	2	the	the	DET
ijassa-135	42	3	problem	problem	NOUN
ijassa-135	42	4	of	of	ADP
ijassa-135	42	5	estimating	estimate	VERB
ijassa-135	42	6	parameters	parameter	NOUN
ijassa-135	42	7	βp×1	βp×1	ADV
ijassa-135	42	8	,	,	PUNCT
ijassa-135	42	9	assume	assume	VERB
ijassa-135	42	10	that	that	SCONJ
ijassa-135	42	11	there	there	PRON
ijassa-135	42	12	are	be	VERB
ijassa-135	42	13	the	the	DET
ijassa-135	42	14	following	follow	VERB
ijassa-135	42	15	two	two	NUM
ijassa-135	42	16	types	type	NOUN
ijassa-135	42	17	of	of	ADP
ijassa-135	42	18	observational	observational	ADJ
ijassa-135	42	19	information	information	NOUN
ijassa-135	42	20	:	:	PUNCT
ijassa-135	42	21	{	{	PUNCT
ijassa-135	43	1	ym×1	ym×1	NOUN
ijassa-135	43	2	=	=	SYM
ijassa-135	43	3	xm×pβp×1	xm×pβp×1	PUNCT
ijassa-135	44	1	+	+	NUM
ijassa-135	45	1	εm×1	εm×1	NOUN
ijassa-135	45	2	eε	eε	ADJ
ijassa-135	45	3	=	=	PUNCT
ijassa-135	45	4	0;cov(ε	0;cov(ε	PROPN
ijassa-135	45	5	,	,	PUNCT
ijassa-135	45	6	ε	ε	PROPN
ijassa-135	45	7	)	)	PUNCT
ijassa-135	46	1	=	=	PROPN
ijassa-135	46	2	σ2	σ2	PROPN
ijassa-135	46	3	1im×m	1im×m	PROPN
ijassa-135	46	4	(	(	PUNCT
ijassa-135	46	5	2	2	NUM
ijassa-135	46	6	)	)	PUNCT
ijassa-135	46	7	and	and	CCONJ
ijassa-135	46	8	{	{	PUNCT
ijassa-135	46	9	β̃k×1	β̃k×1	PUNCT
ijassa-135	46	10	=	=	SYM
ijassa-135	46	11	zk×pβp×1	zk×pβp×1	NOUN
ijassa-135	46	12	+	+	CCONJ
ijassa-135	46	13	ηk×1	ηk×1	PROPN
ijassa-135	46	14	η	η	PROPN
ijassa-135	46	15	∼	∼	NOUN
ijassa-135	46	16	n(0	n(0	PROPN
ijassa-135	46	17	,	,	PUNCT
ijassa-135	46	18	σ2	σ2	NOUN
ijassa-135	46	19	2ik×k	2ik×k	NUM
ijassa-135	46	20	)	)	PUNCT
ijassa-135	46	21	(	(	PUNCT
ijassa-135	46	22	3	3	X
ijassa-135	46	23	)	)	SYM
ijassa-135	46	24	237	237	NUM
ijassa-135	46	25	advances	advance	NOUN
ijassa-135	46	26	in	in	ADP
ijassa-135	46	27	systems	system	NOUN
ijassa-135	46	28	science	science	NOUN
ijassa-135	46	29	and	and	CCONJ
ijassa-135	46	30	applications	application	NOUN
ijassa-135	46	31	(	(	PUNCT
ijassa-135	46	32	2013	2013	NUM
ijassa-135	46	33	)	)	PUNCT
ijassa-135	46	34	vol.13	vol.13	NOUN
ijassa-135	46	35	no.3	no.3	VERB
ijassa-135	46	36	satisfying	satisfy	VERB
ijassa-135	46	37	eεηt	eεηt	NOUN
ijassa-135	46	38	=	=	NOUN
ijassa-135	46	39	0	0	X
ijassa-135	46	40	.	.	PUNCT
ijassa-135	47	1	if	if	SCONJ
ijassa-135	47	2	we	we	PRON
ijassa-135	47	3	treat	treat	VERB
ijassa-135	47	4	model	model	NOUN
ijassa-135	47	5	(	(	PUNCT
ijassa-135	47	6	2	2	NUM
ijassa-135	47	7	)	)	PUNCT
ijassa-135	47	8	as	as	ADP
ijassa-135	47	9	the	the	DET
ijassa-135	47	10	direct	direct	ADJ
ijassa-135	47	11	observational	observational	ADJ
ijassa-135	47	12	data	datum	NOUN
ijassa-135	47	13	,	,	PUNCT
ijassa-135	47	14	while	while	SCONJ
ijassa-135	47	15	(	(	PUNCT
ijassa-135	47	16	3	3	X
ijassa-135	47	17	)	)	PUNCT
ijassa-135	47	18	the	the	DET
ijassa-135	47	19	prior	prior	ADJ
ijassa-135	47	20	information	information	NOUN
ijassa-135	47	21	on	on	ADP
ijassa-135	47	22	the	the	DET
ijassa-135	47	23	parameters	parameter	NOUN
ijassa-135	47	24	,	,	PUNCT
ijassa-135	47	25	then	then	ADV
ijassa-135	47	26	the	the	DET
ijassa-135	47	27	bayesian	bayesian	NOUN
ijassa-135	47	28	estimation	estimation	NOUN
ijassa-135	47	29	of	of	ADP
ijassa-135	47	30	the	the	DET
ijassa-135	47	31	parameters	parameter	NOUN
ijassa-135	47	32	is	be	AUX
ijassa-135	47	33	the	the	DET
ijassa-135	47	34	solution	solution	NOUN
ijassa-135	47	35	of	of	ADP
ijassa-135	47	36	the	the	DET
ijassa-135	47	37	following	following	ADJ
ijassa-135	47	38	extremum	extremum	ADJ
ijassa-135	47	39	problem	problem	NOUN
ijassa-135	47	40	:	:	PUNCT
ijassa-135	47	41	min	min	NOUN
ijassa-135	47	42	β∈rp	β∈rp	NOUN
ijassa-135	47	43	σ−2	σ−2	PROPN
ijassa-135	47	44	1	1	NUM
ijassa-135	47	45	∥	∥	SYM
ijassa-135	47	46	y	y	PROPN
ijassa-135	47	47	−xβ	−xβ	PROPN
ijassa-135	47	48	∥22	∥22	PROPN
ijassa-135	48	1	+	+	ADJ
ijassa-135	48	2	σ−2	σ−2	PROPN
ijassa-135	48	3	2	2	NUM
ijassa-135	48	4	∥	∥	NOUN
ijassa-135	48	5	β̃	β̃	PUNCT
ijassa-135	48	6	−	−	ADP
ijassa-135	48	7	zβ	zβ	PROPN
ijassa-135	48	8	∥22	∥22	PROPN
ijassa-135	48	9	(	(	PUNCT
ijassa-135	48	10	4	4	NUM
ijassa-135	48	11	)	)	PUNCT
ijassa-135	48	12	that	that	PRON
ijassa-135	48	13	is	be	AUX
ijassa-135	48	14	given	give	VERB
ijassa-135	48	15	as	as	SCONJ
ijassa-135	48	16	follows	follow	VERB
ijassa-135	48	17	:	:	PUNCT
ijassa-135	48	18	β̂b	β̂b	X
ijassa-135	48	19	=	=	SYM
ijassa-135	48	20	(	(	PUNCT
ijassa-135	48	21	σ−2	σ−2	PROPN
ijassa-135	48	22	1	1	NUM
ijassa-135	48	23	xtx	xtx	X
ijassa-135	48	24	+	+	X
ijassa-135	48	25	σ−2	σ−2	PROPN
ijassa-135	48	26	2	2	NUM
ijassa-135	48	27	ztz)−1(σ−2	ztz)−1(σ−2	NUM
ijassa-135	48	28	1	1	NUM
ijassa-135	48	29	xty	xty	PROPN
ijassa-135	48	30	+	+	CCONJ
ijassa-135	48	31	σ−2	σ−2	PROPN
ijassa-135	48	32	2	2	NUM
ijassa-135	48	33	zt	zt	PROPN
ijassa-135	48	34	β̃	β̃	PROPN
ijassa-135	48	35	)	)	PUNCT
ijassa-135	48	36	(	(	PUNCT
ijassa-135	48	37	5	5	NUM
ijassa-135	48	38	)	)	PUNCT
ijassa-135	48	39	therefore	therefore	ADV
ijassa-135	48	40	,	,	PUNCT
ijassa-135	48	41	the	the	DET
ijassa-135	48	42	following	follow	VERB
ijassa-135	48	43	conclusions	conclusion	NOUN
ijassa-135	48	44	can	can	AUX
ijassa-135	48	45	be	be	AUX
ijassa-135	48	46	shown	show	VERB
ijassa-135	48	47	readily[3	readily[3	NOUN
ijassa-135	48	48	-	-	PUNCT
ijassa-135	48	49	5	5	NUM
ijassa-135	48	50	]	]	PUNCT
ijassa-135	48	51	:	:	PUNCT
ijassa-135	48	52	(	(	PUNCT
ijassa-135	48	53	1)eβ̂b	1)eβ̂b	NUM
ijassa-135	48	54	=	=	SYM
ijassa-135	48	55	β	β	NOUN
ijassa-135	48	56	;	;	PUNCT
ijassa-135	48	57	that	that	PRON
ijassa-135	48	58	is	be	AUX
ijassa-135	48	59	the	the	DET
ijassa-135	48	60	bayesian	bayesian	NOUN
ijassa-135	48	61	estimate	estimate	NOUN
ijassa-135	48	62	is	be	AUX
ijassa-135	48	63	unbiased	unbiased	ADJ
ijassa-135	48	64	;	;	PUNCT
ijassa-135	48	65	and	and	CCONJ
ijassa-135	48	66	(	(	PUNCT
ijassa-135	48	67	2)mse(β̂b	2)mse(β̂b	NUM
ijassa-135	48	68	)	)	PUNCT
ijassa-135	48	69	=	=	PUNCT
ijassa-135	48	70	tr(σ−2	tr(σ−2	PROPN
ijassa-135	48	71	1	1	NUM
ijassa-135	48	72	xtx	xtx	X
ijassa-135	48	73	+	+	CCONJ
ijassa-135	48	74	σ−2	σ−2	PROPN
ijassa-135	48	75	2	2	NUM
ijassa-135	48	76	ztz)−1	ztz)−1	NOUN
ijassa-135	48	77	<	<	X
ijassa-135	48	78	mse(β̂ls	mse(β̂ls	PROPN
ijassa-135	48	79	)	)	PUNCT
ijassa-135	48	80	=	=	PROPN
ijassa-135	48	81	σ2	σ2	PROPN
ijassa-135	48	82	1tr(x	1tr(x	NUM
ijassa-135	48	83	tx)−1	tx)−1	NOUN
ijassa-135	48	84	that	that	PRON
ijassa-135	48	85	is	be	AUX
ijassa-135	48	86	,	,	PUNCT
ijassa-135	48	87	by	by	ADP
ijassa-135	48	88	making	make	VERB
ijassa-135	48	89	use	use	NOUN
ijassa-135	48	90	of	of	ADP
ijassa-135	48	91	appropriate	appropriate	ADJ
ijassa-135	48	92	prior	prior	ADJ
ijassa-135	48	93	knowledge	knowledge	NOUN
ijassa-135	48	94	,	,	PUNCT
ijassa-135	48	95	one	one	PRON
ijassa-135	48	96	can	can	AUX
ijassa-135	48	97	always	always	ADV
ijassa-135	48	98	improve	improve	VERB
ijassa-135	48	99	the	the	DET
ijassa-135	48	100	estimation	estimation	NOUN
ijassa-135	48	101	precision	precision	NOUN
ijassa-135	48	102	of	of	ADP
ijassa-135	48	103	the	the	DET
ijassa-135	48	104	parameters	parameter	NOUN
ijassa-135	48	105	,	,	PUNCT
ijassa-135	48	106	where	where	SCONJ
ijassa-135	48	107	tr(ak×k	tr(ak×k	ADJ
ijassa-135	48	108	)	)	PUNCT
ijassa-135	48	109	=	=	PUNCT
ijassa-135	49	1	∑k	∑k	PROPN
ijassa-135	49	2	i=1	i=1	PROPN
ijassa-135	49	3	ai	ai	VERB
ijassa-135	49	4	,	,	PUNCT
ijassa-135	49	5	i	i	PRON
ijassa-135	49	6	is	be	AUX
ijassa-135	49	7	the	the	DET
ijassa-135	49	8	trace	trace	NOUN
ijassa-135	49	9	of	of	ADP
ijassa-135	49	10	the	the	DET
ijassa-135	49	11	matrix	matrix	NOUN
ijassa-135	49	12	.	.	PUNCT
ijassa-135	50	1	when	when	SCONJ
ijassa-135	50	2	fusing	fuse	VERB
ijassa-135	50	3	these	these	DET
ijassa-135	50	4	data	datum	NOUN
ijassa-135	50	5	,	,	PUNCT
ijassa-135	50	6	the	the	DET
ijassa-135	50	7	weights	weight	NOUN
ijassa-135	50	8	placed	place	VERB
ijassa-135	50	9	on	on	ADP
ijassa-135	50	10	the	the	DET
ijassa-135	50	11	data	datum	NOUN
ijassa-135	50	12	have	have	VERB
ijassa-135	50	13	profound	profound	ADJ
ijassa-135	50	14	effects	effect	NOUN
ijassa-135	50	15	on	on	ADP
ijassa-135	50	16	the	the	DET
ijassa-135	50	17	outcomes	outcome	NOUN
ijassa-135	50	18	and	and	CCONJ
ijassa-135	50	19	the	the	DET
ijassa-135	50	20	achieved	achieve	VERB
ijassa-135	50	21	precisions	precision	NOUN
ijassa-135	50	22	.	.	PUNCT
ijassa-135	51	1	these	these	DET
ijassa-135	51	2	conclusions	conclusion	NOUN
ijassa-135	51	3	indicate	indicate	VERB
ijassa-135	51	4	that	that	SCONJ
ijassa-135	51	5	when	when	SCONJ
ijassa-135	51	6	fusing	fuse	VERB
ijassa-135	51	7	observations	observation	NOUN
ijassa-135	51	8	of	of	ADP
ijassa-135	51	9	different	different	ADJ
ijassa-135	51	10	precisions	precision	NOUN
ijassa-135	51	11	,	,	PUNCT
ijassa-135	51	12	the	the	DET
ijassa-135	51	13	unique	unique	ADJ
ijassa-135	51	14	optimal	optimal	ADJ
ijassa-135	51	15	weight	weight	NOUN
ijassa-135	51	16	matrix	matrix	NOUN
ijassa-135	51	17	is	be	AUX
ijassa-135	51	18	determined	determine	VERB
ijassa-135	51	19	by	by	ADP
ijassa-135	51	20	the	the	DET
ijassa-135	51	21	precisions	precision	NOUN
ijassa-135	51	22	of	of	ADP
ijassa-135	51	23	the	the	DET
ijassa-135	51	24	data	datum	NOUN
ijassa-135	51	25	,	,	PUNCT
ijassa-135	51	26	which	which	PRON
ijassa-135	51	27	in	in	ADP
ijassa-135	51	28	essence	essence	NOUN
ijassa-135	51	29	is	be	AUX
ijassa-135	51	30	still	still	ADV
ijassa-135	51	31	the	the	DET
ijassa-135	51	32	gaussmarkov	gaussmarkov	PROPN
ijassa-135	51	33	theorem	theorem	NOUN
ijassa-135	51	34	of	of	ADP
ijassa-135	51	35	linear	linear	PROPN
ijassa-135	51	36	models	model	NOUN
ijassa-135	51	37	established	establish	VERB
ijassa-135	51	38	on	on	ADP
ijassa-135	51	39	the	the	DET
ijassa-135	51	40	least	least	ADJ
ijassa-135	51	41	squares	square	NOUN
ijassa-135	51	42	method	method	NOUN
ijassa-135	51	43	.	.	PUNCT
ijassa-135	52	1	2.2	2.2	NUM
ijassa-135	52	2	the	the	DET
ijassa-135	52	3	optimally	optimally	ADV
ijassa-135	52	4	weighted	weight	VERB
ijassa-135	52	5	information	information	NOUN
ijassa-135	52	6	fusion	fusion	NOUN
ijassa-135	52	7	of	of	ADP
ijassa-135	52	8	nonlinear	nonlinear	ADJ
ijassa-135	52	9	system	system	NOUN
ijassa-135	52	10	evaluation	evaluation	NOUN
ijassa-135	52	11	for	for	ADP
ijassa-135	52	12	nonlinear	nonlinear	ADJ
ijassa-135	52	13	models	model	NOUN
ijassa-135	52	14	,	,	PUNCT
ijassa-135	52	15	we	we	PRON
ijassa-135	52	16	show	show	VERB
ijassa-135	52	17	in	in	ADP
ijassa-135	52	18	theory	theory	NOUN
ijassa-135	52	19	that	that	SCONJ
ijassa-135	52	20	when	when	SCONJ
ijassa-135	52	21	fusing	fuse	VERB
ijassa-135	52	22	heterogeneous	heterogeneous	ADJ
ijassa-135	52	23	sets	set	NOUN
ijassa-135	52	24	of	of	ADP
ijassa-135	52	25	data	datum	NOUN
ijassa-135	52	26	with	with	ADP
ijassa-135	52	27	varied	varied	ADJ
ijassa-135	52	28	scales	scale	NOUN
ijassa-135	52	29	of	of	ADP
ijassa-135	52	30	precision	precision	NOUN
ijassa-135	52	31	,	,	PUNCT
ijassa-135	52	32	the	the	DET
ijassa-135	52	33	structure	structure	NOUN
ijassa-135	52	34	of	of	ADP
ijassa-135	52	35	the	the	DET
ijassa-135	52	36	weight	weight	NOUN
ijassa-135	52	37	matrix	matrix	NOUN
ijassa-135	52	38	is	be	AUX
ijassa-135	52	39	no	no	ADV
ijassa-135	52	40	longer	long	ADV
ijassa-135	52	41	uniquely	uniquely	ADV
ijassa-135	52	42	determined	determine	VERB
ijassa-135	52	43	by	by	ADP
ijassa-135	52	44	the	the	DET
ijassa-135	52	45	precisions	precision	NOUN
ijassa-135	52	46	.	.	PUNCT
ijassa-135	53	1	that	that	PRON
ijassa-135	53	2	is	is	ADV
ijassa-135	53	3	,	,	PUNCT
ijassa-135	53	4	the	the	DET
ijassa-135	53	5	classical	classical	ADJ
ijassa-135	53	6	gaussmarkov	gaussmarkov	NOUN
ijassa-135	53	7	theorem	theorem	NOUN
ijassa-135	53	8	of	of	ADP
ijassa-135	53	9	linear	linear	PROPN
ijassa-135	53	10	models	model	NOUN
ijassa-135	53	11	no	no	ADV
ijassa-135	53	12	longer	long	ADV
ijassa-135	53	13	holds	hold	VERB
ijassa-135	53	14	true	true	ADJ
ijassa-135	53	15	.	.	PUNCT
ijassa-135	54	1	at	at	ADP
ijassa-135	54	2	the	the	DET
ijassa-135	54	3	same	same	ADJ
ijassa-135	54	4	time	time	NOUN
ijassa-135	54	5	,	,	PUNCT
ijassa-135	54	6	we	we	PRON
ijassa-135	54	7	establish	establish	VERB
ijassa-135	54	8	a	a	DET
ijassa-135	54	9	method	method	NOUN
ijassa-135	54	10	for	for	ADP
ijassa-135	54	11	determining	determine	VERB
ijassa-135	54	12	the	the	DET
ijassa-135	54	13	optimal	optimal	ADJ
ijassa-135	54	14	weighting	weighting	NOUN
ijassa-135	54	15	factor	factor	NOUN
ijassa-135	54	16	and	and	CCONJ
ijassa-135	54	17	the	the	DET
ijassa-135	54	18	relevant	relevant	ADJ
ijassa-135	54	19	computational	computational	ADJ
ijassa-135	54	20	method	method	NOUN
ijassa-135	54	21	for	for	ADP
ijassa-135	54	22	estimating	estimate	VERB
ijassa-135	54	23	the	the	DET
ijassa-135	54	24	parameters	parameter	NOUN
ijassa-135	54	25	.	.	PUNCT
ijassa-135	55	1	for	for	ADP
ijassa-135	55	2	the	the	DET
ijassa-135	55	3	sake	sake	NOUN
ijassa-135	55	4	of	of	ADP
ijassa-135	55	5	convenience	convenience	NOUN
ijassa-135	55	6	,	,	PUNCT
ijassa-135	55	7	for	for	ADP
ijassa-135	55	8	the	the	DET
ijassa-135	55	9	parameter	parameter	NOUN
ijassa-135	55	10	θ	θ	PROPN
ijassa-135	55	11	that	that	PRON
ijassa-135	55	12	is	be	AUX
ijassa-135	55	13	to	to	PART
ijassa-135	55	14	be	be	AUX
ijassa-135	55	15	estimated	estimate	VERB
ijassa-135	55	16	,	,	PUNCT
ijassa-135	55	17	we	we	PRON
ijassa-135	55	18	assume	assume	VERB
ijassa-135	55	19	that	that	SCONJ
ijassa-135	55	20	we	we	PRON
ijassa-135	55	21	have	have	VERB
ijassa-135	55	22	the	the	DET
ijassa-135	55	23	prior	prior	ADJ
ijassa-135	55	24	information	information	NOUN
ijassa-135	55	25	(	(	PUNCT
ijassa-135	55	26	3	3	NUM
ijassa-135	55	27	)	)	PUNCT
ijassa-135	55	28	for	for	ADP
ijassa-135	55	29	a	a	DET
ijassa-135	55	30	linear	linear	ADJ
ijassa-135	55	31	model	model	NOUN
ijassa-135	55	32	,	,	PUNCT
ijassa-135	55	33	where	where	SCONJ
ijassa-135	55	34	the	the	DET
ijassa-135	55	35	error	error	NOUN
ijassa-135	55	36	satisfies	satisfy	VERB
ijassa-135	55	37	eεηt	eεηt	NOUN
ijassa-135	55	38	=	=	SYM
ijassa-135	55	39	0	0	X
ijassa-135	55	40	.	.	PUNCT
ijassa-135	56	1	so	so	ADV
ijassa-135	56	2	,	,	PUNCT
ijassa-135	56	3	the	the	DET
ijassa-135	56	4	weighting	weighting	NOUN
ijassa-135	56	5	problem	problem	NOUN
ijassa-135	56	6	of	of	ADP
ijassa-135	56	7	fusing	fuse	VERB
ijassa-135	56	8	these	these	DET
ijassa-135	56	9	two	two	NUM
ijassa-135	56	10	types	type	NOUN
ijassa-135	56	11	of	of	ADP
ijassa-135	56	12	observational	observational	ADJ
ijassa-135	56	13	data	datum	NOUN
ijassa-135	56	14	can	can	AUX
ijassa-135	56	15	be	be	AUX
ijassa-135	56	16	reduced	reduce	VERB
ijassa-135	56	17	to	to	ADP
ijassa-135	56	18	the	the	DET
ijassa-135	56	19	following	follow	VERB
ijassa-135	56	20	minimization	minimization	NOUN
ijassa-135	56	21	problem	problem	NOUN
ijassa-135	56	22	:	:	PUNCT
ijassa-135	57	1	min	min	NOUN
ijassa-135	58	1	ρ∈r1,ρ>0	ρ∈r1,ρ>0	ADJ
ijassa-135	58	2	min	min	NOUN
ijassa-135	58	3	β∈rp	β∈rp	NOUN
ijassa-135	58	4	∥	∥	PROPN
ijassa-135	58	5	y	y	NOUN
ijassa-135	58	6	−	−	PROPN
ijassa-135	58	7	f(x	f(x	PROPN
ijassa-135	58	8	,	,	PUNCT
ijassa-135	58	9	β	β	NOUN
ijassa-135	58	10	)	)	PUNCT
ijassa-135	58	11	∥22	∥22	PROPN
ijassa-135	59	1	+	+	PROPN
ijassa-135	59	2	ρ	ρ	NOUN
ijassa-135	59	3	∥	∥	NUM
ijassa-135	59	4	β̃	β̃	PUNCT
ijassa-135	59	5	−	−	ADP
ijassa-135	59	6	zβ	zβ	PROPN
ijassa-135	59	7	∥22	∥22	PROPN
ijassa-135	59	8	(	(	PUNCT
ijassa-135	59	9	6	6	NUM
ijassa-135	59	10	)	)	PUNCT
ijassa-135	59	11	then	then	ADV
ijassa-135	59	12	,	,	PUNCT
ijassa-135	59	13	we	we	PRON
ijassa-135	59	14	have	have	VERB
ijassa-135	59	15	the	the	DET
ijassa-135	59	16	following	follow	VERB
ijassa-135	59	17	result	result	NOUN
ijassa-135	59	18	:	:	PUNCT
ijassa-135	60	1	theorem1	theorem1	X
ijassa-135	60	2	.	.	PUNCT
ijassa-135	61	1	denote	denote	VERB
ijassa-135	61	2	s(β	s(β	PROPN
ijassa-135	61	3	)	)	PUNCT
ijassa-135	62	1	=	=	SYM
ijassa-135	62	2	∥	∥	X
ijassa-135	62	3	y	y	PROPN
ijassa-135	62	4	−f(β	−f(β	NOUN
ijassa-135	62	5	)	)	PUNCT
ijassa-135	62	6	∥22	∥22	PROPN
ijassa-135	63	1	+	+	PROPN
ijassa-135	63	2	ρ	ρ	NOUN
ijassa-135	63	3	∥	∥	X
ijassa-135	63	4	β̃−zβ	β̃−zβ	NUM
ijassa-135	63	5	∥22	∥22	PROPN
ijassa-135	63	6	,	,	PUNCT
ijassa-135	63	7	s(β̂	s(β̂	PROPN
ijassa-135	63	8	)	)	PUNCT
ijassa-135	63	9	=	=	SYM
ijassa-135	63	10	minβ	minβ	VERB
ijassa-135	63	11	s(β	s(β	PROPN
ijassa-135	63	12	)	)	PUNCT
ijassa-135	63	13	,	,	PUNCT
ijassa-135	63	14	c	c	PROPN
ijassa-135	64	1	=	=	PRON
ijassa-135	64	2	∑m	∑m	PROPN
ijassa-135	64	3	i=1	i=1	PROPN
ijassa-135	64	4	ḟ	ḟ	VERB
ijassa-135	64	5	2	2	NUM
ijassa-135	64	6	i	i	PRON
ijassa-135	65	1	+	+	PROPN
ijassa-135	65	2	ρ	ρ	NOUN
ijassa-135	65	3	∑k	∑k	PROPN
ijassa-135	65	4	i=1	i=1	PROPN
ijassa-135	65	5	z	z	PROPN
ijassa-135	66	1	2	2	NUM
ijassa-135	66	2	i	i	PRON
ijassa-135	66	3	,	,	PUNCT
ijassa-135	66	4	d	d	X
ijassa-135	66	5	=	=	PUNCT
ijassa-135	66	6	∑m	∑m	PROPN
ijassa-135	66	7	i=1	i=1	PROPN
ijassa-135	66	8	ḟif̈i	ḟif̈i	PROPN
ijassa-135	66	9	,	,	PUNCT
ijassa-135	66	10	ξ	ξ	X
ijassa-135	66	11	=	=	SYM
ijassa-135	66	12	∑m	∑m	PROPN
ijassa-135	66	13	i=1	i=1	PROPN
ijassa-135	66	14	ḟiεi+ρ	ḟiεi+ρ	PROPN
ijassa-135	67	1	∑k	∑k	PROPN
ijassa-135	67	2	i=1	i=1	PROPN
ijassa-135	67	3	ziηi	ziηi	PROPN
ijassa-135	67	4	,	,	PUNCT
ijassa-135	67	5	a	a	DET
ijassa-135	67	6	=	=	PROPN
ijassa-135	67	7	σ2	σ2	PROPN
ijassa-135	67	8	1	1	NUM
ijassa-135	67	9	∑m	∑m	PROPN
ijassa-135	67	10	i=1	i=1	PROPN
ijassa-135	67	11	ḟ	ḟ	VERB
ijassa-135	67	12	2	2	NUM
ijassa-135	67	13	i	i	NOUN
ijassa-135	67	14	+	+	NUM
ijassa-135	67	15	xiaojun	xiaojun	PROPN
ijassa-135	67	16	duan	duan	PROPN
ijassa-135	67	17	,	,	PUNCT
ijassa-135	67	18	yi	yi	PROPN
ijassa-135	67	19	lin	lin	PROPN
ijassa-135	67	20	:	:	PUNCT
ijassa-135	67	21	ways	way	NOUN
ijassa-135	67	22	of	of	ADP
ijassa-135	67	23	fusing	fuse	VERB
ijassa-135	67	24	different	different	ADJ
ijassa-135	67	25	types	type	NOUN
ijassa-135	67	26	of	of	ADP
ijassa-135	67	27	information	information	NOUN
ijassa-135	67	28	and	and	CCONJ
ijassa-135	67	29	how	how	SCONJ
ijassa-135	67	30	systemic	systemic	ADJ
ijassa-135	67	31	...	...	PUNCT
ijassa-135	67	32	238	238	NUM
ijassa-135	67	33	ρ2σ2	ρ2σ2	SYM
ijassa-135	67	34	2	2	NUM
ijassa-135	67	35	∑k	∑k	PROPN
ijassa-135	67	36	i=1	i=1	PROPN
ijassa-135	67	37	z	z	PROPN
ijassa-135	67	38	2	2	NUM
ijassa-135	67	39	i	i	PRON
ijassa-135	67	40	,	,	PUNCT
ijassa-135	67	41	then	then	ADV
ijassa-135	67	42	under	under	ADP
ijassa-135	67	43	the	the	DET
ijassa-135	67	44	assumed	assume	VERB
ijassa-135	67	45	conditions	condition	NOUN
ijassa-135	67	46	(	(	PUNCT
ijassa-135	67	47	i	i	NOUN
ijassa-135	67	48	)	)	PUNCT
ijassa-135	67	49	and	and	CCONJ
ijassa-135	67	50	(	(	PUNCT
ijassa-135	67	51	ii	ii	NOUN
ijassa-135	67	52	)	)	PUNCT
ijassa-135	67	53	,	,	PUNCT
ijassa-135	67	54	the	the	DET
ijassa-135	67	55	following	follow	VERB
ijassa-135	67	56	estimation	estimation	NOUN
ijassa-135	67	57	holds	hold	VERB
ijassa-135	67	58	true	true	ADJ
ijassa-135	67	59	:	:	PUNCT
ijassa-135	67	60	β̂	β̂	ADP
ijassa-135	67	61	−	−	PUNCT
ijassa-135	67	62	β	β	X
ijassa-135	67	63	=	=	NOUN
ijassa-135	67	64	c−1ξ	c−1ξ	NOUN
ijassa-135	68	1	+	+	CCONJ
ijassa-135	68	2	c−2	c−2	NOUN
ijassa-135	68	3	m∑	m∑	NOUN
ijassa-135	68	4	i=1	i=1	PROPN
ijassa-135	68	5	f̈iεiξ	f̈iεiξ	PROPN
ijassa-135	68	6	−	−	PROPN
ijassa-135	68	7	3	3	NUM
ijassa-135	68	8	2	2	NUM
ijassa-135	68	9	c−3dξ2	c−3dξ2	NOUN
ijassa-135	68	10	+	+	CCONJ
ijassa-135	69	1	c−3	c−3	NOUN
ijassa-135	70	1	m∑	m∑	ADP
ijassa-135	70	2	i	i	PRON
ijassa-135	70	3	,	,	PUNCT
ijassa-135	70	4	j=1	j=1	ADJ
ijassa-135	70	5	f̈if̈jεiεjξ	f̈if̈jεiεjξ	NOUN
ijassa-135	70	6	−	−	NOUN
ijassa-135	70	7	9	9	NUM
ijassa-135	70	8	2	2	NUM
ijassa-135	70	9	c−4d	c−4d	NOUN
ijassa-135	70	10	m∑	m∑	ADP
ijassa-135	70	11	i=1	i=1	PROPN
ijassa-135	70	12	f̈iεiξ	f̈iεiξ	PROPN
ijassa-135	70	13	2	2	NUM
ijassa-135	70	14	+	+	CCONJ
ijassa-135	70	15	9	9	NUM
ijassa-135	70	16	2	2	NUM
ijassa-135	70	17	c−5d2ξ3	c−5d2ξ3	NOUN
ijassa-135	70	18	(	(	PUNCT
ijassa-135	70	19	7	7	NUM
ijassa-135	70	20	)	)	PUNCT
ijassa-135	70	21	with	with	ADP
ijassa-135	70	22	the	the	DET
ijassa-135	70	23	bias	bias	NOUN
ijassa-135	70	24	and	and	CCONJ
ijassa-135	70	25	mean	mean	ADJ
ijassa-135	70	26	square	square	ADJ
ijassa-135	70	27	error	error	NOUN
ijassa-135	70	28	approximated	approximate	VERB
ijassa-135	70	29	as	as	ADP
ijassa-135	70	30	follows:	follows:	PROPN
ijassa-135	70	31	e(β̂	e(β̂	PROPN
ijassa-135	70	32	−	−	PROPN
ijassa-135	70	33	β	β	NOUN
ijassa-135	70	34	)	)	PUNCT
ijassa-135	70	35	=	=	SYM
ijassa-135	71	1	−1	−1	NOUN
ijassa-135	71	2	2σ	2σ	NOUN
ijassa-135	71	3	2	2	NUM
ijassa-135	71	4	1c	1c	NOUN
ijassa-135	71	5	−2d−	−2d−	ADP
ijassa-135	71	6	3	3	NUM
ijassa-135	71	7	2c	2c	NUM
ijassa-135	71	8	−3dρ(ρσ2	−3dρ(ρσ2	ADP
ijassa-135	71	9	2	2	NUM
ijassa-135	71	10	−	−	PROPN
ijassa-135	71	11	σ2	σ2	PROPN
ijassa-135	71	12	1	1	NUM
ijassa-135	71	13	)	)	PUNCT
ijassa-135	71	14	∑k	∑k	PROPN
ijassa-135	71	15	i=1	i=1	PROPN
ijassa-135	71	16	z	z	PROPN
ijassa-135	71	17	2	2	NUM
ijassa-135	71	18	i	i	NOUN
ijassa-135	71	19	mse(β̂	mse(β̂	PROPN
ijassa-135	71	20	)	)	PUNCT
ijassa-135	71	21	=	=	NOUN
ijassa-135	71	22	c−2a+	c−2a+	PROPN
ijassa-135	71	23	6c−4d2σ4	6c−4d2σ4	NUM
ijassa-135	71	24	1	1	NUM
ijassa-135	71	25	+	+	NUM
ijassa-135	71	26	3c−4aσ2	3c−4aσ2	NUM
ijassa-135	71	27	1	1	NUM
ijassa-135	71	28	m∑	m∑	NOUN
ijassa-135	71	29	i=1	i=1	PROPN
ijassa-135	71	30	f̈2	f̈2	PROPN
ijassa-135	71	31	i	i	PRON
ijassa-135	71	32	+	+	CCONJ
ijassa-135	71	33	135	135	NUM
ijassa-135	71	34	4	4	NUM
ijassa-135	71	35	c−6d2a2	c−6d2a2	ADJ
ijassa-135	71	36	−	−	NOUN
ijassa-135	71	37	36c−5ad2σ2	36c−5ad2σ2	NUM
ijassa-135	71	38	1	1	NUM
ijassa-135	71	39	(	(	PUNCT
ijassa-135	71	40	8)	8)	NUM
ijassa-135	71	41	where	where	SCONJ
ijassa-135	71	42	the	the	DET
ijassa-135	71	43	assumed	assumed	ADJ
ijassa-135	71	44	conditions	condition	NOUN
ijassa-135	71	45	(	(	PUNCT
ijassa-135	71	46	i	i	NOUN
ijassa-135	71	47	)	)	PUNCT
ijassa-135	71	48	and	and	CCONJ
ijassa-135	71	49	(	(	PUNCT
ijassa-135	71	50	ii	ii	NOUN
ijassa-135	71	51	)	)	PUNCT
ijassa-135	71	52	are	be	AUX
ijassa-135	71	53	given	give	VERB
ijassa-135	71	54	below	below	ADV
ijassa-135	71	55	:	:	PUNCT
ijassa-135	71	56	(	(	PUNCT
ijassa-135	71	57	i	i	NOUN
ijassa-135	71	58	)	)	PUNCT
ijassa-135	71	59	the	the	DET
ijassa-135	71	60	derivative	derivative	NOUN
ijassa-135	71	61	of	of	ADP
ijassa-135	71	62	f(t	f(t	PROPN
ijassa-135	71	63	,	,	PUNCT
ijassa-135	71	64	β	β	NOUN
ijassa-135	71	65	)	)	PUNCT
ijassa-135	71	66	with	with	ADP
ijassa-135	71	67	respect	respect	NOUN
ijassa-135	71	68	to	to	ADP
ijassa-135	71	69	the	the	DET
ijassa-135	71	70	parameter	parameter	NOUN
ijassa-135	71	71	β	β	PROPN
ijassa-135	71	72	exists	exist	VERB
ijassa-135	71	73	and	and	CCONJ
ijassa-135	71	74	is	be	AUX
ijassa-135	71	75	continuous	continuous	ADJ
ijassa-135	71	76	,	,	PUNCT
ijassa-135	71	77	and	and	CCONJ
ijassa-135	71	78	lim	lim	PROPN
ijassa-135	71	79	m→+∞	m→+∞	PROPN
ijassa-135	71	80	1	1	NUM
ijassa-135	71	81	m	m	NOUN
ijassa-135	71	82	m∑	m∑	NOUN
ijassa-135	71	83	i=1	i=1	X
ijassa-135	72	1	=	=	PUNCT
ijassa-135	73	1	(	(	PUNCT
ijassa-135	73	2	df(ti	df(ti	PROPN
ijassa-135	73	3	,	,	PUNCT
ijassa-135	73	4	β	β	NOUN
ijassa-135	73	5	)	)	PUNCT
ijassa-135	73	6	dβ	dβ	ADJ
ijassa-135	73	7	)	)	PUNCT
ijassa-135	73	8	2	2	NUM
ijassa-135	73	9	=	=	SYM
ijassa-135	73	10	ω1(β	ω1(β	NOUN
ijassa-135	73	11	)	)	PUNCT
ijassa-135	73	12	>	>	X
ijassa-135	73	13	0	0	PUNCT
ijassa-135	74	1	(	(	PUNCT
ijassa-135	74	2	9	9	NUM
ijassa-135	74	3	)	)	PUNCT
ijassa-135	74	4	(	(	PUNCT
ijassa-135	74	5	ii	ii	NOUN
ijassa-135	74	6	)	)	PUNCT
ijassa-135	74	7	the	the	DET
ijassa-135	74	8	second	second	ADJ
ijassa-135	74	9	order	order	NOUN
ijassa-135	74	10	derivative	derivative	NOUN
ijassa-135	74	11	of	of	ADP
ijassa-135	74	12	f(t	f(t	PROPN
ijassa-135	74	13	,	,	PUNCT
ijassa-135	74	14	β	β	NOUN
ijassa-135	74	15	)	)	PUNCT
ijassa-135	74	16	with	with	ADP
ijassa-135	74	17	respect	respect	NOUN
ijassa-135	74	18	to	to	ADP
ijassa-135	74	19	β	β	NOUN
ijassa-135	74	20	exists	exist	NOUN
ijassa-135	74	21	and	and	CCONJ
ijassa-135	74	22	is	be	AUX
ijassa-135	74	23	continuous	continuous	ADJ
ijassa-135	74	24	,	,	PUNCT
ijassa-135	74	25	and	and	CCONJ
ijassa-135	74	26	lim	lim	PROPN
ijassa-135	74	27	m→+∞	m→+∞	PROPN
ijassa-135	74	28	1	1	NUM
ijassa-135	74	29	m	m	NOUN
ijassa-135	74	30	m∑	m∑	NOUN
ijassa-135	74	31	i=1	i=1	X
ijassa-135	75	1	=	=	PUNCT
ijassa-135	76	1	(	(	PUNCT
ijassa-135	76	2	d2f(ti	d2f(ti	PROPN
ijassa-135	76	3	,	,	PUNCT
ijassa-135	76	4	β	β	NOUN
ijassa-135	76	5	)	)	PUNCT
ijassa-135	76	6	dβ2	dβ2	VERB
ijassa-135	76	7	)	)	PUNCT
ijassa-135	76	8	2	2	X
ijassa-135	76	9	=	=	SYM
ijassa-135	76	10	ω2(β	ω2(β	PROPN
ijassa-135	76	11	)	)	PUNCT
ijassa-135	76	12	(	(	PUNCT
ijassa-135	76	13	10	10	X
ijassa-135	76	14	)	)	PUNCT
ijassa-135	76	15	proof	proof	NOUN
ijassa-135	76	16	.	.	PUNCT
ijassa-135	77	1	taking	take	VERB
ijassa-135	77	2	the	the	DET
ijassa-135	77	3	series	series	NOUN
ijassa-135	77	4	expansion	expansion	NOUN
ijassa-135	77	5	of	of	ADP
ijassa-135	77	6	ṡ(β̂	ṡ(β̂	NOUN
ijassa-135	77	7	)	)	PUNCT
ijassa-135	77	8	about	about	ADP
ijassa-135	77	9	the	the	DET
ijassa-135	77	10	true	true	ADJ
ijassa-135	77	11	value	value	NOUN
ijassa-135	77	12	of	of	ADP
ijassa-135	77	13	the	the	DET
ijassa-135	77	14	parameter	parameter	NOUN
ijassa-135	77	15	β	β	PROPN
ijassa-135	77	16	produces	produce	VERB
ijassa-135	77	17	ṡ(β̂	ṡ(β̂	NOUN
ijassa-135	77	18	)	)	PUNCT
ijassa-135	77	19	=	=	SYM
ijassa-135	77	20	ṡ(β	ṡ(β	NOUN
ijassa-135	77	21	)	)	PUNCT
ijassa-135	78	1	+	+	CCONJ
ijassa-135	78	2	s̈(β)(β̂	s̈(β)(β̂	NOUN
ijassa-135	78	3	−	−	ADP
ijassa-135	78	4	β	β	NOUN
ijassa-135	78	5	)	)	PUNCT
ijassa-135	78	6	+	+	CCONJ
ijassa-135	78	7	2−1	2−1	X
ijassa-135	78	8	...	...	PUNCT
ijassa-135	78	9	s	s	X
ijassa-135	78	10	(	(	PUNCT
ijassa-135	78	11	β)(β̂	β)(β̂	PROPN
ijassa-135	78	12	−	−	PROPN
ijassa-135	78	13	β)2	β)2	ADV
ijassa-135	78	14	notice	notice	VERB
ijassa-135	78	15	that	that	SCONJ
ijassa-135	78	16	ṡ(β̂	ṡ(β̂	VERB
ijassa-135	78	17	)	)	PUNCT
ijassa-135	78	18	=	=	SYM
ijassa-135	78	19	0	0	NUM
ijassa-135	78	20	,	,	PUNCT
ijassa-135	78	21	ṡ(β	ṡ(β	NOUN
ijassa-135	78	22	)	)	PUNCT
ijassa-135	78	23	=	=	SYM
ijassa-135	78	24	−2	−2	NOUN
ijassa-135	78	25	(	(	PUNCT
ijassa-135	78	26	∑m	∑m	PROPN
ijassa-135	78	27	i=1	i=1	X
ijassa-135	78	28	ḟiεi	ḟiεi	PROPN
ijassa-135	79	1	+	+	CCONJ
ijassa-135	79	2	ρ	ρ	PROPN
ijassa-135	79	3	∑m	∑m	PROPN
ijassa-135	79	4	i=1	i=1	PROPN
ijassa-135	79	5	ziηi	ziηi	PROPN
ijassa-135	79	6	)	)	PUNCT
ijassa-135	79	7	,	,	PUNCT
ijassa-135	79	8	s̈(β	s̈(β	PROPN
ijassa-135	79	9	)	)	PUNCT
ijassa-135	79	10	=	=	SYM
ijassa-135	79	11	2c	2c	NOUN
ijassa-135	79	12	−	−	NOUN
ijassa-135	79	13	2	2	NUM
ijassa-135	79	14	∑m	∑m	PROPN
ijassa-135	79	15	i=1	i=1	PROPN
ijassa-135	79	16	f̈iεi	f̈iεi	PROPN
ijassa-135	79	17	,	,	PUNCT
ijassa-135	79	18	...	...	PUNCT
ijassa-135	80	1	s	s	X
ijassa-135	80	2	(	(	PUNCT
ijassa-135	80	3	β	β	X
ijassa-135	80	4	)	)	PUNCT
ijassa-135	80	5	=	=	SYM
ijassa-135	81	1	6d	6d	NUM
ijassa-135	81	2	−	−	NOUN
ijassa-135	81	3	2	2	NUM
ijassa-135	81	4	∑m	∑m	PROPN
ijassa-135	81	5	i=1	i=1	PROPN
ijassa-135	81	6	...	...	PUNCT
ijassa-135	82	1	f	f	X
ijassa-135	82	2	iεi	iεi	NOUN
ijassa-135	82	3	,	,	PUNCT
ijassa-135	82	4	so	so	ADV
ijassa-135	82	5	,	,	PUNCT
ijassa-135	82	6	ignoring	ignore	VERB
ijassa-135	82	7	all	all	DET
ijassa-135	82	8	terms	term	NOUN
ijassa-135	82	9	of	of	ADP
ijassa-135	82	10	third	third	ADJ
ijassa-135	82	11	or	or	CCONJ
ijassa-135	82	12	higher	high	ADJ
ijassa-135	82	13	order	order	NOUN
ijassa-135	82	14	derivatives	derivative	NOUN
ijassa-135	82	15	produces	produce	VERB
ijassa-135	82	16	β̂	β̂	ADP
ijassa-135	82	17	−	−	PROPN
ijassa-135	82	18	β	β	X
ijassa-135	82	19	=	=	SYM
ijassa-135	82	20	c−1	c−1	PROPN
ijassa-135	82	21	{	{	PUNCT
ijassa-135	82	22	ξ	ξ	PROPN
ijassa-135	82	23	+	+	ADP
ijassa-135	82	24	m∑	m∑	CCONJ
ijassa-135	82	25	i=1	i=1	PRON
ijassa-135	82	26	f̈iεi(β̂	f̈iεi(β̂	PROPN
ijassa-135	82	27	−	−	PROPN
ijassa-135	82	28	β)−	β)−	NOUN
ijassa-135	82	29	3	3	NUM
ijassa-135	82	30	2	2	NUM
ijassa-135	82	31	d(β̂	d(β̂	NOUN
ijassa-135	82	32	−	−	NOUN
ijassa-135	82	33	β)2	β)2	NOUN
ijassa-135	82	34	+	+	CCONJ
ijassa-135	82	35	1	1	NUM
ijassa-135	82	36	2	2	NUM
ijassa-135	82	37	m∑	m∑	NOUN
ijassa-135	82	38	i=1	i=1	PRON
ijassa-135	82	39	...	...	PUNCT
ijassa-135	83	1	f	f	PROPN
ijassa-135	83	2	iεi(β̂	iεi(β̂	PROPN
ijassa-135	83	3	−	−	PROPN
ijassa-135	83	4	β)2	β)2	NOUN
ijassa-135	83	5	}	}	PUNCT
ijassa-135	83	6	=	=	SYM
ijassa-135	83	7	c−1ξ	c−1ξ	NOUN
ijassa-135	84	1	+	+	CCONJ
ijassa-135	84	2	c−2	c−2	NOUN
ijassa-135	84	3	m∑	m∑	NOUN
ijassa-135	84	4	i=1	i=1	PROPN
ijassa-135	84	5	f̈iεiξ	f̈iεiξ	PROPN
ijassa-135	84	6	−	−	PROPN
ijassa-135	84	7	3	3	NUM
ijassa-135	84	8	2	2	NUM
ijassa-135	84	9	c−3dξ2	c−3dξ2	NOUN
ijassa-135	84	10	+	+	CCONJ
ijassa-135	85	1	c−3	c−3	NOUN
ijassa-135	86	1	m∑	m∑	ADP
ijassa-135	86	2	i	i	PRON
ijassa-135	86	3	,	,	PUNCT
ijassa-135	86	4	j=1	j=1	ADJ
ijassa-135	86	5	f̈if̈jεiεjξ	f̈if̈jεiεjξ	NOUN
ijassa-135	86	6	−	−	NOUN
ijassa-135	86	7	9	9	NUM
ijassa-135	86	8	2	2	NUM
ijassa-135	86	9	c−4d	c−4d	NOUN
ijassa-135	86	10	m∑	m∑	ADP
ijassa-135	86	11	i=1	i=1	PROPN
ijassa-135	86	12	f̈iεiξ	f̈iεiξ	PROPN
ijassa-135	86	13	2	2	NUM
ijassa-135	86	14	+	+	CCONJ
ijassa-135	86	15	9	9	NUM
ijassa-135	86	16	2	2	NUM
ijassa-135	86	17	c−5d2ξ3	c−5d2ξ3	NOUN
ijassa-135	86	18	239	239	NUM
ijassa-135	86	19	advances	advance	NOUN
ijassa-135	86	20	in	in	ADP
ijassa-135	86	21	systems	system	NOUN
ijassa-135	86	22	science	science	NOUN
ijassa-135	86	23	and	and	CCONJ
ijassa-135	86	24	applications	application	NOUN
ijassa-135	86	25	(	(	PUNCT
ijassa-135	86	26	2013	2013	NUM
ijassa-135	86	27	)	)	PUNCT
ijassa-135	86	28	vol.13	vol.13	NOUN
ijassa-135	86	29	no.3	no.3	NOUN
ijassa-135	86	30	that	that	PRON
ijassa-135	86	31	is	be	AUX
ijassa-135	86	32	equ.(7	equ.(7	PROPN
ijassa-135	86	33	)	)	PUNCT
ijassa-135	86	34	holds	hold	VERB
ijassa-135	86	35	true	true	ADJ
ijassa-135	86	36	.	.	PUNCT
ijassa-135	87	1	because	because	SCONJ
ijassa-135	87	2	the	the	DET
ijassa-135	87	3	expected	expect	VERB
ijassa-135	87	4	values	value	NOUN
ijassa-135	87	5	of	of	ADP
ijassa-135	87	6	normal	normal	ADJ
ijassa-135	87	7	variables	variable	NOUN
ijassa-135	87	8	to	to	ADP
ijassa-135	87	9	odd	odd	ADJ
ijassa-135	87	10	powers	power	NOUN
ijassa-135	87	11	are	be	AUX
ijassa-135	87	12	zero	zero	NUM
ijassa-135	87	13	and	and	CCONJ
ijassa-135	87	14	ε	ε	PROPN
ijassa-135	87	15	and	and	CCONJ
ijassa-135	87	16	η	η	PROPN
ijassa-135	87	17	are	be	AUX
ijassa-135	87	18	independent	independent	ADJ
ijassa-135	87	19	,	,	PUNCT
ijassa-135	87	20	we	we	PRON
ijassa-135	87	21	obtain	obtain	VERB
ijassa-135	87	22	the	the	DET
ijassa-135	87	23	first	first	ADJ
ijassa-135	87	24	equation	equation	NOUN
ijassa-135	87	25	in	in	ADP
ijassa-135	87	26	equ	equ	PROPN
ijassa-135	87	27	.	.	PUNCT
ijassa-135	88	1	(	(	PUNCT
ijassa-135	88	2	8)	8)	NUM
ijassa-135	88	3	by	by	ADP
ijassa-135	88	4	ignoring	ignore	VERB
ijassa-135	88	5	the	the	DET
ijassa-135	88	6	error	error	NOUN
ijassa-135	88	7	terms	term	NOUN
ijassa-135	88	8	of	of	ADP
ijassa-135	88	9	the	the	DET
ijassa-135	88	10	fourth	fourth	ADJ
ijassa-135	88	11	and	and	CCONJ
ijassa-135	88	12	higher	high	ADJ
ijassa-135	88	13	orders	order	NOUN
ijassa-135	88	14	and	and	CCONJ
ijassa-135	88	15	then	then	ADV
ijassa-135	88	16	calculating	calculate	VERB
ijassa-135	88	17	the	the	DET
ijassa-135	88	18	expected	expect	VERB
ijassa-135	88	19	value	value	NOUN
ijassa-135	88	20	such	such	ADJ
ijassa-135	88	21	that	that	DET
ijassa-135	88	22	e(β̂−β)2	e(β̂−β)2	NOUN
ijassa-135	88	23	=	=	PUNCT
ijassa-135	88	24	c−2eξ2	c−2eξ2	PUNCT
ijassa-135	89	1	+	+	NOUN
ijassa-135	89	2	3c−4e	3c−4e	NUM
ijassa-135	89	3	(	(	PUNCT
ijassa-135	89	4	m∑	m∑	ADV
ijassa-135	89	5	i=1	i=1	PROPN
ijassa-135	89	6	f̈iεi	f̈iεi	PROPN
ijassa-135	89	7	)	)	PUNCT
ijassa-135	90	1	2ξ2	2ξ2	NUM
ijassa-135	90	2	+	+	NUM
ijassa-135	90	3	45	45	NUM
ijassa-135	90	4	4	4	NUM
ijassa-135	90	5	c−6d2eξ4−12c−5d	c−6d2eξ4−12c−5d	NOUN
ijassa-135	90	6	m∑	m∑	NOUN
ijassa-135	90	7	i=1	i=1	PROPN
ijassa-135	90	8	f̈iεiξ	f̈iεiξ	PROPN
ijassa-135	90	9	3	3	NUM
ijassa-135	90	10	(	(	PUNCT
ijassa-135	90	11	11	11	NUM
ijassa-135	90	12	)	)	PUNCT
ijassa-135	91	1	because	because	SCONJ
ijassa-135	91	2	eξ2	eξ2	NOUN
ijassa-135	91	3	=	=	SYM
ijassa-135	91	4	σ2	σ2	PROPN
ijassa-135	91	5	1	1	NUM
ijassa-135	91	6	m∑	m∑	NOUN
ijassa-135	91	7	i=1	i=1	PRON
ijassa-135	91	8	ḟ2i	ḟ2i	PROPN
ijassa-135	91	9	+	+	CCONJ
ijassa-135	91	10	ρ2σ2	ρ2σ2	X
ijassa-135	91	11	2	2	NUM
ijassa-135	91	12	k∑	k∑	NOUN
ijassa-135	91	13	i=1	i=1	PROPN
ijassa-135	91	14	z2i	z2i	PUNCT
ijassa-135	92	1	=	=	SYM
ijassa-135	92	2	̂a	̂a	ADJ
ijassa-135	92	3	,	,	PUNCT
ijassa-135	92	4	eξ4	eξ4	VERB
ijassa-135	92	5	=	=	SYM
ijassa-135	93	1	3σ4	3σ4	NUM
ijassa-135	93	2	1	1	NUM
ijassa-135	93	3	(	(	PUNCT
ijassa-135	93	4	m∑	m∑	CCONJ
ijassa-135	93	5	i=1	i=1	PROPN
ijassa-135	93	6	ḟ2i	ḟ2i	ADJ
ijassa-135	93	7	)	)	PUNCT
ijassa-135	93	8	2	2	NUM
ijassa-135	94	1	+	+	NUM
ijassa-135	94	2	6ρ2σ2	6ρ2σ2	NUM
ijassa-135	94	3	1σ	1σ	NOUN
ijassa-135	94	4	2	2	NUM
ijassa-135	94	5	2	2	NUM
ijassa-135	94	6	m∑	m∑	NOUN
ijassa-135	94	7	i=1	i=1	PRON
ijassa-135	94	8	ḟ2i	ḟ2i	NUM
ijassa-135	94	9	k∑	k∑	VERB
ijassa-135	94	10	i=1	i=1	PROPN
ijassa-135	94	11	z2i	z2i	PROPN
ijassa-135	95	1	+	+	CCONJ
ijassa-135	95	2	3ρ4σ4	3ρ4σ4	NUM
ijassa-135	95	3	2	2	NUM
ijassa-135	95	4	(	(	PUNCT
ijassa-135	95	5	m∑	m∑	INTJ
ijassa-135	95	6	i=1	i=1	PROPN
ijassa-135	95	7	z2i	z2i	PROPN
ijassa-135	95	8	)	)	PUNCT
ijassa-135	95	9	2	2	NUM
ijassa-135	95	10	=	=	SYM
ijassa-135	95	11	3a2	3a2	NUM
ijassa-135	95	12	,	,	PUNCT
ijassa-135	95	13	e	e	NOUN
ijassa-135	95	14	(	(	PUNCT
ijassa-135	95	15	m∑	m∑	INTJ
ijassa-135	95	16	i=1	i=1	PROPN
ijassa-135	95	17	f̈iεi	f̈iεi	PROPN
ijassa-135	95	18	)	)	PUNCT
ijassa-135	95	19	2ξ2	2ξ2	NUM
ijassa-135	96	1	=	=	SYM
ijassa-135	96	2	2d2σ4	2d2σ4	NUM
ijassa-135	96	3	1	1	NUM
ijassa-135	97	1	+	+	NUM
ijassa-135	97	2	σ4	σ4	NOUN
ijassa-135	97	3	1	1	NUM
ijassa-135	97	4	m∑	m∑	NOUN
ijassa-135	97	5	i=1	i=1	PROPN
ijassa-135	98	1	ḟ2	ḟ2	PROPN
ijassa-135	99	1	i	i	PRON
ijassa-135	99	2	m∑	m∑	AUX
ijassa-135	99	3	i=1	i=1	PROPN
ijassa-135	99	4	f̈2	f̈2	PROPN
ijassa-135	100	1	i	i	PRON
ijassa-135	100	2	+	+	CCONJ
ijassa-135	100	3	ρ2σ2	ρ2σ2	VERB
ijassa-135	100	4	1σ	1σ	NUM
ijassa-135	100	5	2	2	NUM
ijassa-135	100	6	2	2	NUM
ijassa-135	100	7	m∑	m∑	NOUN
ijassa-135	100	8	i=1	i=1	PROPN
ijassa-135	100	9	f̈2	f̈2	PROPN
ijassa-135	101	1	i	i	PRON
ijassa-135	101	2	k∑	k∑	VERB
ijassa-135	101	3	i=1	i=1	PROPN
ijassa-135	101	4	z2i	z2i	PUNCT
ijassa-135	102	1	=	=	PUNCT
ijassa-135	103	1	2d2σ4	2d2σ4	NUM
ijassa-135	103	2	1	1	NUM
ijassa-135	103	3	+	+	NUM
ijassa-135	103	4	σ2	σ2	NOUN
ijassa-135	103	5	1a	1a	NOUN
ijassa-135	103	6	m∑	m∑	INTJ
ijassa-135	103	7	i=1	i=1	PROPN
ijassa-135	103	8	f̈2	f̈2	PROPN
ijassa-135	104	1	i	i	PRON
ijassa-135	104	2	,	,	PUNCT
ijassa-135	104	3	e	e	NOUN
ijassa-135	104	4	m∑	m∑	CCONJ
ijassa-135	104	5	i=1	i=1	PROPN
ijassa-135	104	6	f̈iεiξ	f̈iεiξ	PROPN
ijassa-135	104	7	3	3	NUM
ijassa-135	104	8	=	=	SYM
ijassa-135	104	9	3dσ4	3dσ4	NUM
ijassa-135	104	10	1	1	NUM
ijassa-135	104	11	m∑	m∑	NOUN
ijassa-135	104	12	i=1	i=1	PRON
ijassa-135	104	13	ḟ2i	ḟ2i	PROPN
ijassa-135	104	14	+	+	CCONJ
ijassa-135	104	15	3ρ2σ2	3ρ2σ2	NUM
ijassa-135	104	16	1σ	1σ	NOUN
ijassa-135	104	17	2	2	NUM
ijassa-135	104	18	2d	2d	NUM
ijassa-135	104	19	k∑	k∑	VERB
ijassa-135	104	20	i=1	i=1	PROPN
ijassa-135	104	21	z2i	z2i	PROPN
ijassa-135	105	1	=	=	PUNCT
ijassa-135	106	1	3daσ2	3daσ2	NUM
ijassa-135	106	2	1	1	NUM
ijassa-135	106	3	,	,	PUNCT
ijassa-135	106	4	substituting	substitute	VERB
ijassa-135	106	5	these	these	DET
ijassa-135	106	6	equations	equation	NOUN
ijassa-135	106	7	into	into	ADP
ijassa-135	106	8	equ.(11	equ.(11	PROPN
ijassa-135	106	9	)	)	PUNCT
ijassa-135	106	10	leads	lead	VERB
ijassa-135	106	11	to	to	ADP
ijassa-135	106	12	e(β̂−β)2	e(β̂−β)2	NOUN
ijassa-135	106	13	=	=	SYM
ijassa-135	106	14	c−2a+6c−4d2σ4	c−2a+6c−4d2σ4	NOUN
ijassa-135	106	15	1	1	NUM
ijassa-135	106	16	+3c−4aσ2	+3c−4aσ2	SYM
ijassa-135	106	17	1	1	NUM
ijassa-135	106	18	m∑	m∑	NOUN
ijassa-135	106	19	i=1	i=1	PROPN
ijassa-135	106	20	f̈2i	f̈2i	PROPN
ijassa-135	107	1	+	+	CCONJ
ijassa-135	107	2	135	135	NUM
ijassa-135	107	3	4	4	NUM
ijassa-135	107	4	c−6d2a2−36c−5ad2σ2	c−6d2a2−36c−5ad2σ2	NOUN
ijassa-135	107	5	1	1	NUM
ijassa-135	107	6	that	that	PRON
ijassa-135	107	7	is	be	AUX
ijassa-135	107	8	the	the	DET
ijassa-135	107	9	second	second	ADJ
ijassa-135	107	10	equation	equation	NOUN
ijassa-135	107	11	in	in	ADP
ijassa-135	107	12	equ.(8	equ.(8	NOUN
ijassa-135	107	13	)	)	PUNCT
ijassa-135	107	14	.	.	PUNCT
ijassa-135	108	1	qed	qed	PROPN
ijassa-135	108	2	.	.	PUNCT
ijassa-135	109	1	theorem2	theorem2	PROPN
ijassa-135	109	2	.	.	PROPN
ijassa-135	110	1	for	for	ADP
ijassa-135	110	2	mse(β̂)(ρ	mse(β̂)(ρ	PRON
ijassa-135	110	3	)	)	PUNCT
ijassa-135	110	4	in	in	ADP
ijassa-135	110	5	theorem	theorem	NOUN
ijassa-135	110	6	1	1	NUM
ijassa-135	110	7	,	,	PUNCT
ijassa-135	110	8	the	the	DET
ijassa-135	110	9	solution	solution	NOUN
ijassa-135	110	10	to	to	ADP
ijassa-135	110	11	the	the	DET
ijassa-135	110	12	following	follow	VERB
ijassa-135	110	13	minimization	minimization	NOUN
ijassa-135	110	14	problem	problem	NOUN
ijassa-135	110	15	min	min	PROPN
ijassa-135	110	16	ρ	ρ	PROPN
ijassa-135	110	17	mse(β̂)(ρ	mse(β̂)(ρ	PROPN
ijassa-135	110	18	)	)	PUNCT
ijassa-135	110	19	(	(	PUNCT
ijassa-135	110	20	12	12	NUM
ijassa-135	110	21	)	)	PUNCT
ijassa-135	110	22	exists	exist	VERB
ijassa-135	110	23	,	,	PUNCT
ijassa-135	110	24	satisfying	satisfy	VERB
ijassa-135	110	25	min	min	PROPN
ijassa-135	110	26	ρ	ρ	PROPN
ijassa-135	110	27	mse(β̂)(ρ	mse(β̂)(ρ	PROPN
ijassa-135	110	28	)	)	PUNCT
ijassa-135	110	29	<	<	X
ijassa-135	110	30	minρmse(β̂	minρmse(β̂	NOUN
ijassa-135	110	31	)	)	PUNCT
ijassa-135	110	32	(	(	PUNCT
ijassa-135	110	33	σ2	σ2	PROPN
ijassa-135	110	34	1	1	NUM
ijassa-135	110	35	σ2	σ2	PROPN
ijassa-135	110	36	2	2	NUM
ijassa-135	110	37	)	)	PUNCT
ijassa-135	110	38	.	.	PUNCT
ijassa-135	111	1	proof	proof	NOUN
ijassa-135	111	2	.	.	PUNCT
ijassa-135	112	1	because	because	SCONJ
ijassa-135	112	2	lim	lim	PROPN
ijassa-135	112	3	ρ→+∞	ρ→+∞	PROPN
ijassa-135	112	4	mse(β̂)(ρ	mse(β̂)(ρ	PROPN
ijassa-135	112	5	)	)	PUNCT
ijassa-135	112	6	=	=	SYM
ijassa-135	112	7	σ2	σ2	NOUN
ijassa-135	112	8	2	2	NUM
ijassa-135	112	9	(	(	PUNCT
ijassa-135	112	10	∑k	∑k	PROPN
ijassa-135	112	11	i=1	i=1	PROPN
ijassa-135	112	12	z	z	PROPN
ijassa-135	112	13	2	2	NUM
ijassa-135	112	14	i	i	NOUN
ijassa-135	112	15	)	)	PUNCT
ijassa-135	112	16	−1	−1	NOUN
ijassa-135	112	17	,	,	PUNCT
ijassa-135	112	18	mse(β̂)(ρ	mse(β̂)(ρ	PROPN
ijassa-135	112	19	)	)	PUNCT
ijassa-135	112	20	is	be	AUX
ijassa-135	112	21	infinitely	infinitely	ADV
ijassa-135	112	22	difxiaojun	difxiaojun	PROPN
ijassa-135	112	23	duan	duan	PROPN
ijassa-135	112	24	,	,	PUNCT
ijassa-135	112	25	yi	yi	PROPN
ijassa-135	112	26	lin	lin	PROPN
ijassa-135	112	27	:	:	PUNCT
ijassa-135	112	28	ways	way	NOUN
ijassa-135	112	29	of	of	ADP
ijassa-135	112	30	fusing	fuse	VERB
ijassa-135	112	31	different	different	ADJ
ijassa-135	112	32	types	type	NOUN
ijassa-135	112	33	of	of	ADP
ijassa-135	112	34	information	information	NOUN
ijassa-135	112	35	and	and	CCONJ
ijassa-135	112	36	how	how	SCONJ
ijassa-135	112	37	systemic	systemic	ADJ
ijassa-135	112	38	...	...	PUNCT
ijassa-135	112	39	240	240	NUM
ijassa-135	112	40	ferentiable	ferentiable	NOUN
ijassa-135	112	41	on	on	ADP
ijassa-135	112	42	[	[	X
ijassa-135	112	43	0,+∞	0,+∞	NUM
ijassa-135	112	44	)	)	PUNCT
ijassa-135	112	45	,	,	PUNCT
ijassa-135	112	46	mse(β̂)(ρ	mse(β̂)(ρ	PROPN
ijassa-135	112	47	)	)	PUNCT
ijassa-135	112	48	has	have	VERB
ijassa-135	112	49	its	its	PRON
ijassa-135	112	50	minimum	minimum	ADJ
ijassa-135	112	51	value	value	NOUN
ijassa-135	112	52	on	on	ADP
ijassa-135	112	53	[	[	X
ijassa-135	112	54	0,+∞	0,+∞	NUM
ijassa-135	112	55	)	)	PUNCT
ijassa-135	112	56	.	.	PUNCT
ijassa-135	113	1	because	because	SCONJ
ijassa-135	113	2	d	d	PROPN
ijassa-135	113	3	dρ	dρ	ADJ
ijassa-135	113	4	mse(β̂)(ρ	mse(β̂)(ρ	PROPN
ijassa-135	113	5	)	)	PUNCT
ijassa-135	114	1	=	=	PRON
ijassa-135	114	2	(	(	PUNCT
ijassa-135	114	3	k∑	k∑	NOUN
ijassa-135	114	4	i=1	i=1	PROPN
ijassa-135	114	5	z2i	z2i	PROPN
ijassa-135	114	6	)	)	PUNCT
ijassa-135	114	7	(	(	PUNCT
ijassa-135	114	8	−2c−3a+	−2c−3a+	NOUN
ijassa-135	114	9	2ρc−2σ2	2ρc−2σ2	NOUN
ijassa-135	114	10	2	2	NUM
ijassa-135	114	11	−	−	NOUN
ijassa-135	114	12	24c−5d2σ4	24c−5d2σ4	NOUN
ijassa-135	114	13	1	1	NUM
ijassa-135	114	14	−	−	NUM
ijassa-135	114	15	12c−5σ2	12c−5σ2	NUM
ijassa-135	114	16	1	1	NUM
ijassa-135	114	17	m∑	m∑	NOUN
ijassa-135	114	18	i=1	i=1	PROPN
ijassa-135	114	19	f̈2	f̈2	PROPN
ijassa-135	115	1	i	i	PRON
ijassa-135	115	2	+	+	PROPN
ijassa-135	115	3	6ρc−4σ2	6ρc−4σ2	ADJ
ijassa-135	115	4	1σ	1σ	NOUN
ijassa-135	115	5	2	2	NUM
ijassa-135	115	6	2	2	NUM
ijassa-135	115	7	m∑	m∑	NOUN
ijassa-135	115	8	i=1	i=1	PROPN
ijassa-135	115	9	f̈2	f̈2	PROPN
ijassa-135	116	1	i	i	PRON
ijassa-135	116	2	−	−	PROPN
ijassa-135	117	1	405	405	NUM
ijassa-135	117	2	2	2	NUM
ijassa-135	117	3	c−7d2a2	c−7d2a2	NOUN
ijassa-135	117	4	+	+	CCONJ
ijassa-135	117	5	135ρc−6d2aσ2	135ρc−6d2aσ2	NUM
ijassa-135	117	6	2	2	NUM
ijassa-135	117	7	+	+	SYM
ijassa-135	117	8	180c−6ad2σ2	180c−6ad2σ2	NUM
ijassa-135	117	9	1	1	NUM
ijassa-135	117	10	−	−	NOUN
ijassa-135	117	11	72ρc−5d2σ2	72ρc−5d2σ2	NUM
ijassa-135	117	12	1σ	1σ	NOUN
ijassa-135	117	13	2	2	NUM
ijassa-135	117	14	2	2	NUM
ijassa-135	117	15	)	)	PUNCT
ijassa-135	117	16	(	(	PUNCT
ijassa-135	117	17	13	13	NUM
ijassa-135	117	18	)	)	PUNCT
ijassa-135	117	19	we	we	PRON
ijassa-135	117	20	have	have	AUX
ijassa-135	117	21	d	d	PROPN
ijassa-135	117	22	dρ	dρ	ADJ
ijassa-135	117	23	mse(β̂)(0	mse(β̂)(0	NOUN
ijassa-135	117	24	)	)	PUNCT
ijassa-135	118	1	=	=	SYM
ijassa-135	118	2	−	−	PROPN
ijassa-135	118	3	(	(	PUNCT
ijassa-135	118	4	k∑	k∑	NOUN
ijassa-135	118	5	i=1	i=1	PROPN
ijassa-135	118	6	z2i	z2i	PROPN
ijassa-135	118	7	)	)	PUNCT
ijassa-135	118	8	(	(	PUNCT
ijassa-135	118	9	2	2	NUM
ijassa-135	118	10	(	(	PUNCT
ijassa-135	118	11	m∑	m∑	INTJ
ijassa-135	118	12	i=1	i=1	PROPN
ijassa-135	118	13	ḟ2	ḟ2	VERB
ijassa-135	118	14	i	i	NOUN
ijassa-135	118	15	)	)	PUNCT
ijassa-135	118	16	−2σ2	−2σ2	NUM
ijassa-135	118	17	1	1	NUM
ijassa-135	119	1	+	+	CCONJ
ijassa-135	119	2	93	93	NUM
ijassa-135	119	3	2	2	NUM
ijassa-135	119	4	(	(	PUNCT
ijassa-135	119	5	m∑	m∑	INTJ
ijassa-135	119	6	i=1	i=1	PROPN
ijassa-135	119	7	ḟ2	ḟ2	VERB
ijassa-135	120	1	i	i	NOUN
ijassa-135	120	2	)	)	PUNCT
ijassa-135	120	3	−5d2σ4	−5d2σ4	PROPN
ijassa-135	120	4	1	1	NUM
ijassa-135	121	1	+	+	NUM
ijassa-135	121	2	12	12	NUM
ijassa-135	121	3	(	(	PUNCT
ijassa-135	121	4	m∑	m∑	INTJ
ijassa-135	121	5	i=1	i=1	PROPN
ijassa-135	121	6	ḟ2	ḟ2	VERB
ijassa-135	121	7	i	i	NOUN
ijassa-135	121	8	)	)	PUNCT
ijassa-135	122	1	−5	−5	ADP
ijassa-135	123	1	m∑	m∑	X
ijassa-135	123	2	i=1	i=1	PROPN
ijassa-135	124	1	ḟ2	ḟ2	VERB
ijassa-135	125	1	i	i	PRON
ijassa-135	125	2	m∑	m∑	AUX
ijassa-135	125	3	i=1	i=1	PROPN
ijassa-135	125	4	f̈2	f̈2	PROPN
ijassa-135	126	1	i	i	PRON
ijassa-135	126	2	σ	σ	NUM
ijassa-135	126	3	4	4	NUM
ijassa-135	126	4	1	1	NUM
ijassa-135	126	5	)	)	PUNCT
ijassa-135	126	6	<	<	X
ijassa-135	126	7	0	0	PUNCT
ijassa-135	127	1	also	also	ADV
ijassa-135	127	2	,	,	PUNCT
ijassa-135	127	3	because	because	SCONJ
ijassa-135	127	4	lim	lim	PROPN
ijassa-135	127	5	ρ→+∞	ρ→+∞	PROPN
ijassa-135	127	6	d	d	PROPN
ijassa-135	127	7	dρmse(β̂)(ρ	dρmse(β̂)(ρ	PROPN
ijassa-135	127	8	)	)	PUNCT
ijassa-135	127	9	=	=	PUNCT
ijassa-135	127	10	0	0	NUM
ijassa-135	127	11	,	,	PUNCT
ijassa-135	127	12	and	and	CCONJ
ijassa-135	127	13	when	when	SCONJ
ijassa-135	127	14	ρ	ρ	PROPN
ijassa-135	127	15	→	→	SYM
ijassa-135	127	16	+	+	PROPN
ijassa-135	127	17	∞	∞	PROPN
ijassa-135	127	18	,	,	PUNCT
ijassa-135	127	19	each	each	DET
ijassa-135	127	20	term	term	NOUN
ijassa-135	127	21	starting	start	VERB
ijassa-135	127	22	from	from	ADP
ijassa-135	127	23	the	the	DET
ijassa-135	127	24	third	third	NOUN
ijassa-135	127	25	in	in	ADP
ijassa-135	127	26	equ.(13	equ.(13	PROPN
ijassa-135	127	27	)	)	PUNCT
ijassa-135	127	28	is	be	AUX
ijassa-135	127	29	a	a	DET
ijassa-135	127	30	higher	high	ADJ
ijassa-135	127	31	order	order	NOUN
ijassa-135	127	32	infinitesimal	infinitesimal	ADJ
ijassa-135	127	33	when	when	SCONJ
ijassa-135	127	34	compared	compare	VERB
ijassa-135	127	35	to	to	ADP
ijassa-135	127	36	the	the	DET
ijassa-135	127	37	previous	previous	ADJ
ijassa-135	127	38	two	two	NUM
ijassa-135	127	39	terms	term	NOUN
ijassa-135	127	40	;	;	PUNCT
ijassa-135	127	41	and	and	CCONJ
ijassa-135	127	42	when	when	SCONJ
ijassa-135	127	43	ρ	ρ	PROPN
ijassa-135	127	44	>	>	X
ijassa-135	127	45	σ2	σ2	PROPN
ijassa-135	127	46	1σ	1σ	PROPN
ijassa-135	127	47	−2	−2	NOUN
ijassa-135	127	48	2	2	NUM
ijassa-135	127	49	,	,	PUNCT
ijassa-135	127	50	the	the	DET
ijassa-135	127	51	sum	sum	NOUN
ijassa-135	127	52	of	of	ADP
ijassa-135	127	53	the	the	DET
ijassa-135	127	54	previous	previous	ADJ
ijassa-135	127	55	two	two	NUM
ijassa-135	127	56	terms	term	NOUN
ijassa-135	127	57	is	be	AUX
ijassa-135	127	58	greater	great	ADJ
ijassa-135	127	59	than	than	ADP
ijassa-135	127	60	zero	zero	NUM
ijassa-135	127	61	there	there	PRON
ijassa-135	127	62	is	be	VERB
ijassa-135	127	63	ρ0	ρ0	PROPN
ijassa-135	127	64	>	>	X
ijassa-135	127	65	0	0	PUNCT
ijassa-135	128	1	so	so	SCONJ
ijassa-135	128	2	that	that	SCONJ
ijassa-135	128	3	d	d	X
ijassa-135	128	4	dρmse(β̂)(ρ	dρmse(β̂)(ρ	PROPN
ijassa-135	128	5	)	)	PUNCT
ijassa-135	128	6	>	>	X
ijassa-135	128	7	0	0	PUNCT
ijassa-135	129	1	when	when	SCONJ
ijassa-135	129	2	ρ	ρ	PROPN
ijassa-135	129	3	∈	∈	PROPN
ijassa-135	129	4	[	[	X
ijassa-135	129	5	ρ0,+∞	ρ0,+∞	NUM
ijassa-135	129	6	)	)	PUNCT
ijassa-135	129	7	.	.	PUNCT
ijassa-135	130	1	therefore	therefore	ADV
ijassa-135	130	2	,	,	PUNCT
ijassa-135	130	3	the	the	DET
ijassa-135	130	4	solution	solution	NOUN
ijassa-135	130	5	of	of	ADP
ijassa-135	130	6	min	min	PROPN
ijassa-135	130	7	ρ	ρ	PROPN
ijassa-135	130	8	mse(β̂)(ρ	mse(β̂)(ρ	PROPN
ijassa-135	130	9	)	)	PUNCT
ijassa-135	130	10	satisfies	satisfy	VERB
ijassa-135	130	11	ρ̂	ρ̂	NUM
ijassa-135	130	12	∈	∈	PROPN
ijassa-135	130	13	(	(	PUNCT
ijassa-135	130	14	0	0	NUM
ijassa-135	130	15	,	,	PUNCT
ijassa-135	130	16	ρ0	ρ0	PROPN
ijassa-135	130	17	)	)	PUNCT
ijassa-135	130	18	.	.	PUNCT
ijassa-135	131	1	and	and	CCONJ
ijassa-135	131	2	because	because	SCONJ
ijassa-135	131	3	d	d	PROPN
ijassa-135	131	4	dρ	dρ	ADJ
ijassa-135	131	5	mse(β̂	mse(β̂	PROPN
ijassa-135	131	6	)	)	PUNCT
ijassa-135	131	7	(	(	PUNCT
ijassa-135	131	8	σ2	σ2	PROPN
ijassa-135	131	9	1	1	NUM
ijassa-135	131	10	σ2	σ2	NOUN
ijassa-135	131	11	2	2	NUM
ijassa-135	131	12	)	)	PUNCT
ijassa-135	131	13	=	=	NOUN
ijassa-135	131	14	σ4	σ4	NOUN
ijassa-135	131	15	1	1	NUM
ijassa-135	131	16	2c5	2c5	NUM
ijassa-135	131	17	k∑	k∑	VERB
ijassa-135	131	18	i=1	i=1	PROPN
ijassa-135	132	1	z2i	z2i	PROPN
ijassa-135	132	2	(	(	PUNCT
ijassa-135	132	3	33d	33d	ADV
ijassa-135	132	4	2	2	NUM
ijassa-135	132	5	−	−	NOUN
ijassa-135	132	6	12	12	NUM
ijassa-135	132	7	(	(	PUNCT
ijassa-135	132	8	m∑	m∑	CCONJ
ijassa-135	132	9	i=1	i=1	PROPN
ijassa-135	132	10	ḟ2i	ḟ2i	PROPN
ijassa-135	132	11	+	+	CCONJ
ijassa-135	132	12	σ2	σ2	PROPN
ijassa-135	132	13	1	1	NUM
ijassa-135	132	14	σ2	σ2	PROPN
ijassa-135	132	15	2	2	NUM
ijassa-135	132	16	k∑	k∑	NOUN
ijassa-135	132	17	i=1	i=1	PROPN
ijassa-135	132	18	z2i	z2i	PROPN
ijassa-135	132	19	)	)	PUNCT
ijassa-135	133	1	m∑	m∑	CCONJ
ijassa-135	133	2	i=1	i=1	PROPN
ijassa-135	133	3	f̈2i	f̈2i	PROPN
ijassa-135	133	4	)	)	PUNCT
ijassa-135	134	1	̸=	̸=	PROPN
ijassa-135	134	2	0	0	NUM
ijassa-135	134	3	,	,	PUNCT
ijassa-135	134	4	ρ	ρ	PROPN
ijassa-135	134	5	=	=	PROPN
ijassa-135	134	6	σ2	σ2	PROPN
ijassa-135	134	7	1σ	1σ	ADJ
ijassa-135	134	8	−2	−2	NOUN
ijassa-135	134	9	2	2	NUM
ijassa-135	134	10	is	be	AUX
ijassa-135	134	11	not	not	PART
ijassa-135	134	12	a	a	DET
ijassa-135	134	13	solution	solution	NOUN
ijassa-135	134	14	of	of	ADP
ijassa-135	134	15	min	min	PROPN
ijassa-135	134	16	ρ	ρ	PROPN
ijassa-135	134	17	mse(β̂)(ρ	mse(β̂)(ρ	PROPN
ijassa-135	134	18	)	)	PUNCT
ijassa-135	134	19	.	.	PUNCT
ijassa-135	135	1	hence	hence	ADV
ijassa-135	135	2	,	,	PUNCT
ijassa-135	135	3	theorem	theorem	ADJ
ijassa-135	135	4	2	2	NUM
ijassa-135	135	5	is	be	AUX
ijassa-135	135	6	proven	prove	VERB
ijassa-135	135	7	.	.	PUNCT
ijassa-135	136	1	qed	qed	PROPN
ijassa-135	136	2	.	.	PUNCT
ijassa-135	137	1	remarks	remark	VERB
ijassa-135	137	2	:	:	PUNCT
ijassa-135	137	3	(	(	PUNCT
ijassa-135	137	4	1	1	X
ijassa-135	137	5	)	)	PUNCT
ijassa-135	137	6	theorem	theorem	NOUN
ijassa-135	137	7	2	2	NUM
ijassa-135	137	8	indicates	indicate	VERB
ijassa-135	137	9	that	that	SCONJ
ijassa-135	137	10	for	for	ADP
ijassa-135	137	11	nonlinear	nonlinear	ADJ
ijassa-135	137	12	models	model	NOUN
ijassa-135	137	13	,	,	PUNCT
ijassa-135	137	14	because	because	SCONJ
ijassa-135	137	15	their	their	PRON
ijassa-135	137	16	least	least	ADJ
ijassa-135	137	17	squares	square	NOUN
ijassa-135	137	18	estimates	estimate	NOUN
ijassa-135	137	19	are	be	AUX
ijassa-135	137	20	generally	generally	ADV
ijassa-135	137	21	biased	bias	VERB
ijassa-135	137	22	,	,	PUNCT
ijassa-135	137	23	when	when	SCONJ
ijassa-135	137	24	fusing	fuse	VERB
ijassa-135	137	25	observational	observational	ADJ
ijassa-135	137	26	data	datum	NOUN
ijassa-135	137	27	of	of	ADP
ijassa-135	137	28	varied	varied	ADJ
ijassa-135	137	29	scales	scale	NOUN
ijassa-135	137	30	of	of	ADP
ijassa-135	137	31	precision	precision	NOUN
ijassa-135	137	32	,	,	PUNCT
ijassa-135	137	33	the	the	DET
ijassa-135	137	34	weight	weight	NOUN
ijassa-135	137	35	matrix	matrix	NOUN
ijassa-135	137	36	obtained	obtain	VERB
ijassa-135	137	37	by	by	ADP
ijassa-135	137	38	using	use	VERB
ijassa-135	137	39	gauss	gauss	ADJ
ijassa-135	137	40	-	-	PUNCT
ijassa-135	137	41	markov	markov	NOUN
ijassa-135	137	42	theorem	theorem	NOUN
ijassa-135	137	43	,	,	PUNCT
ijassa-135	137	44	which	which	PRON
ijassa-135	137	45	is	be	AUX
ijassa-135	137	46	derived	derive	VERB
ijassa-135	137	47	out	out	ADP
ijassa-135	137	48	of	of	ADP
ijassa-135	137	49	the	the	DET
ijassa-135	137	50	least	least	ADJ
ijassa-135	137	51	squares	square	NOUN
ijassa-135	137	52	estimation	estimation	NOUN
ijassa-135	137	53	for	for	ADP
ijassa-135	137	54	linear	linear	PROPN
ijassa-135	137	55	models	model	NOUN
ijassa-135	137	56	,	,	PUNCT
ijassa-135	137	57	is	be	AUX
ijassa-135	137	58	no	no	ADV
ijassa-135	137	59	longer	long	ADV
ijassa-135	137	60	optimal	optimal	ADJ
ijassa-135	137	61	.	.	PUNCT
ijassa-135	138	1	the	the	DET
ijassa-135	138	2	optimal	optimal	ADJ
ijassa-135	138	3	weights	weight	NOUN
ijassa-135	138	4	can	can	AUX
ijassa-135	138	5	be	be	AUX
ijassa-135	138	6	obtained	obtain	VERB
ijassa-135	138	7	by	by	ADP
ijassa-135	138	8	solving	solve	VERB
ijassa-135	138	9	the	the	DET
ijassa-135	138	10	minimization	minimization	NOUN
ijassa-135	138	11	problem	problem	NOUN
ijassa-135	138	12	in	in	ADP
ijassa-135	138	13	equ.(12	equ.(12	PROPN
ijassa-135	138	14	)	)	PUNCT
ijassa-135	138	15	.	.	PUNCT
ijassa-135	139	1	(	(	PUNCT
ijassa-135	139	2	2	2	X
ijassa-135	139	3	)	)	PUNCT
ijassa-135	139	4	if	if	SCONJ
ijassa-135	139	5	the	the	DET
ijassa-135	139	6	prior	prior	ADJ
ijassa-135	139	7	knowledge	knowledge	NOUN
ijassa-135	139	8	equ	equ	PROPN
ijassa-135	139	9	.	.	PUNCT
ijassa-135	140	1	(	(	PUNCT
ijassa-135	140	2	3	3	X
ijassa-135	140	3	)	)	PUNCT
ijassa-135	140	4	is	be	AUX
ijassa-135	140	5	a	a	DET
ijassa-135	140	6	nonlinear	nonlinear	ADJ
ijassa-135	140	7	model	model	NOUN
ijassa-135	140	8	and	and	CCONJ
ijassa-135	140	9	the	the	DET
ijassa-135	140	10	first	first	ADJ
ijassa-135	140	11	and	and	CCONJ
ijassa-135	140	12	second	second	ADJ
ijassa-135	140	13	order	order	NOUN
ijassa-135	140	14	derivatives	derivative	NOUN
ijassa-135	140	15	of	of	ADP
ijassa-135	140	16	the	the	DET
ijassa-135	140	17	model	model	NOUN
ijassa-135	140	18	are	be	AUX
ijassa-135	140	19	the	the	DET
ijassa-135	140	20	same	same	ADJ
ijassa-135	140	21	as	as	ADP
ijassa-135	140	22	those	those	PRON
ijassa-135	140	23	of	of	ADP
ijassa-135	140	24	nonlinear	nonlinear	ADJ
ijassa-135	140	25	function	function	NOUN
ijassa-135	140	26	f(x	f(x	PROPN
ijassa-135	140	27	,	,	PUNCT
ijassa-135	140	28	β	β	NOUN
ijassa-135	140	29	)	)	PUNCT
ijassa-135	140	30	,	,	PUNCT
ijassa-135	140	31	then	then	ADV
ijassa-135	140	32	the	the	DET
ijassa-135	140	33	optimal	optimal	ADJ
ijassa-135	140	34	weight	weight	NOUN
ijassa-135	140	35	can	can	AUX
ijassa-135	140	36	be	be	AUX
ijassa-135	140	37	approximated	approximate	VERB
ijassa-135	140	38	by	by	ADP
ijassa-135	140	39	ρ	ρ	PROPN
ijassa-135	140	40	=	=	PROPN
ijassa-135	140	41	σ2	σ2	PROPN
ijassa-135	140	42	1σ	1σ	PROPN
ijassa-135	140	43	−2	−2	NOUN
ijassa-135	140	44	2	2	NUM
ijassa-135	140	45	.	.	PUNCT
ijassa-135	141	1	241	241	NUM
ijassa-135	141	2	advances	advance	NOUN
ijassa-135	141	3	in	in	ADP
ijassa-135	141	4	systems	system	NOUN
ijassa-135	141	5	science	science	NOUN
ijassa-135	141	6	and	and	CCONJ
ijassa-135	141	7	applications	application	NOUN
ijassa-135	141	8	(	(	PUNCT
ijassa-135	141	9	2013	2013	NUM
ijassa-135	141	10	)	)	PUNCT
ijassa-135	141	11	vol.13	vol.13	NOUN
ijassa-135	141	12	no.3	no.3	VERB
ijassa-135	141	13	2.3	2.3	NUM
ijassa-135	141	14	the	the	DET
ijassa-135	141	15	parameter	parameter	NOUN
ijassa-135	141	16	estimation	estimation	NOUN
ijassa-135	141	17	of	of	ADP
ijassa-135	141	18	heterogeneous	heterogeneous	ADJ
ijassa-135	141	19	data	datum	NOUN
ijassa-135	141	20	fusion	fusion	NOUN
ijassa-135	141	21	when	when	SCONJ
ijassa-135	141	22	solving	solve	VERB
ijassa-135	141	23	problem	problem	NOUN
ijassa-135	141	24	(	(	PUNCT
ijassa-135	141	25	6	6	NUM
ijassa-135	141	26	)	)	PUNCT
ijassa-135	141	27	,	,	PUNCT
ijassa-135	141	28	one	one	PRON
ijassa-135	141	29	can	can	AUX
ijassa-135	141	30	simply	simply	ADV
ijassa-135	141	31	follow	follow	VERB
ijassa-135	141	32	the	the	DET
ijassa-135	141	33	following	following	ADJ
ijassa-135	141	34	iterative	iterative	NOUN
ijassa-135	141	35	method	method	NOUN
ijassa-135	141	36	:	:	PUNCT
ijassa-135	141	37	step	step	NOUN
ijassa-135	141	38	1	1	NUM
ijassa-135	141	39	:	:	PUNCT
ijassa-135	141	40	for	for	ADP
ijassa-135	141	41	an	an	DET
ijassa-135	141	42	initial	initial	ADJ
ijassa-135	141	43	weight	weight	NOUN
ijassa-135	141	44	value	value	NOUN
ijassa-135	141	45	ρ0	ρ0	PROPN
ijassa-135	141	46	=	=	PROPN
ijassa-135	141	47	σ2	σ2	PROPN
ijassa-135	141	48	1σ	1σ	PROPN
ijassa-135	141	49	−2	−2	NOUN
ijassa-135	141	50	2	2	NUM
ijassa-135	141	51	,	,	PUNCT
ijassa-135	141	52	solve	solve	VERB
ijassa-135	141	53	the	the	DET
ijassa-135	141	54	following	follow	VERB
ijassa-135	141	55	minimization	minimization	NOUN
ijassa-135	141	56	problem	problem	NOUN
ijassa-135	141	57	min	min	PROPN
ijassa-135	141	58	β∈r1	β∈r1	X
ijassa-135	142	1	∥	∥	PUNCT
ijassa-135	143	1	y	y	PROPN
ijassa-135	144	1	−	−	PROPN
ijassa-135	144	2	f(x	f(x	PROPN
ijassa-135	144	3	,	,	PUNCT
ijassa-135	144	4	β	β	NOUN
ijassa-135	144	5	)	)	PUNCT
ijassa-135	144	6	∥2	∥2	NOUN
ijassa-135	145	1	+	+	VERB
ijassa-135	145	2	ρ0	ρ0	PROPN
ijassa-135	145	3	∥	∥	PUNCT
ijassa-135	145	4	β̃	β̃	PROPN
ijassa-135	145	5	−	−	NOUN
ijassa-135	145	6	zβ	zβ	PROPN
ijassa-135	145	7	∥2	∥2	PROPN
ijassa-135	145	8	(	(	PUNCT
ijassa-135	145	9	14	14	NUM
ijassa-135	145	10	)	)	PUNCT
ijassa-135	145	11	to	to	PART
ijassa-135	145	12	obtain	obtain	VERB
ijassa-135	145	13	its	its	PRON
ijassa-135	145	14	solution	solution	NOUN
ijassa-135	145	15	β̂(1	β̂(1	NUM
ijassa-135	145	16	)	)	PUNCT
ijassa-135	145	17	;	;	PUNCT
ijassa-135	145	18	step	step	NOUN
ijassa-135	145	19	2	2	NUM
ijassa-135	145	20	:	:	PUNCT
ijassa-135	145	21	calculate	calculate	VERB
ijassa-135	145	22	the	the	DET
ijassa-135	145	23	mean	mean	ADJ
ijassa-135	145	24	square	square	ADJ
ijassa-135	145	25	error	error	NOUN
ijassa-135	145	26	mse(β̂(1))(β̂(1	mse(β̂(1))(β̂(1	PROPN
ijassa-135	145	27	)	)	PUNCT
ijassa-135	145	28	,	,	PUNCT
ijassa-135	145	29	β	β	X
ijassa-135	145	30	)	)	PUNCT
ijassa-135	145	31	of	of	ADP
ijassa-135	145	32	the	the	DET
ijassa-135	145	33	estimated	estimate	VERB
ijassa-135	145	34	parameter	parameter	NOUN
ijassa-135	145	35	at	at	ADP
ijassa-135	145	36	β̂(1	β̂(1	PROPN
ijassa-135	145	37	)	)	PUNCT
ijassa-135	145	38	;	;	PUNCT
ijassa-135	145	39	step	step	NOUN
ijassa-135	145	40	3	3	NUM
ijassa-135	145	41	:	:	PUNCT
ijassa-135	145	42	solve	solve	VERB
ijassa-135	145	43	the	the	DET
ijassa-135	145	44	minimization	minimization	NOUN
ijassa-135	145	45	problem	problem	NOUN
ijassa-135	145	46	min	min	PROPN
ijassa-135	145	47	ρ>0	ρ>0	PROPN
ijassa-135	145	48	mse(β̂(1))(β̂(1	mse(β̂(1))(β̂(1	PROPN
ijassa-135	145	49	)	)	PUNCT
ijassa-135	145	50	,	,	PUNCT
ijassa-135	145	51	β	β	X
ijassa-135	145	52	)	)	PUNCT
ijassa-135	145	53	to	to	PART
ijassa-135	145	54	obtain	obtain	VERB
ijassa-135	145	55	ρ1	ρ1	NOUN
ijassa-135	145	56	;	;	PUNCT
ijassa-135	145	57	and	and	CCONJ
ijassa-135	145	58	step	step	NOUN
ijassa-135	145	59	4	4	NUM
ijassa-135	145	60	:	:	PUNCT
ijassa-135	145	61	repeat	repeat	VERB
ijassa-135	145	62	steps	step	NOUN
ijassa-135	145	63	1	1	NUM
ijassa-135	145	64	-	-	SYM
ijassa-135	145	65	4	4	NUM
ijassa-135	145	66	with	with	ADP
ijassa-135	145	67	the	the	DET
ijassa-135	145	68	initial	initial	ADJ
ijassa-135	145	69	value	value	NOUN
ijassa-135	145	70	ρ0	ρ0	PROPN
ijassa-135	145	71	replaced	replace	VERB
ijassa-135	145	72	by	by	ADP
ijassa-135	145	73	ρ1	ρ1	NOUN
ijassa-135	145	74	until	until	SCONJ
ijassa-135	145	75	the	the	DET
ijassa-135	145	76	estimated	estimate	VERB
ijassa-135	145	77	value	value	NOUN
ijassa-135	145	78	of	of	ADP
ijassa-135	145	79	the	the	DET
ijassa-135	145	80	parameter	parameter	NOUN
ijassa-135	145	81	becomes	become	VERB
ijassa-135	145	82	stable	stable	ADJ
ijassa-135	145	83	.	.	PUNCT
ijassa-135	146	1	fig.2	fig.2	VERB
ijassa-135	146	2	the	the	DET
ijassa-135	146	3	three	three	NUM
ijassa-135	146	4	samples	sample	NOUN
ijassa-135	146	5	and	and	CCONJ
ijassa-135	146	6	their	their	PRON
ijassa-135	146	7	relationships	relationship	NOUN
ijassa-135	146	8	to	to	ADP
ijassa-135	146	9	the	the	DET
ijassa-135	146	10	information	information	NOUN
ijassa-135	146	11	flow	flow	NOUN
ijassa-135	146	12	of	of	ADP
ijassa-135	146	13	the	the	DET
ijassa-135	146	14	yoyo	yoyo	PROPN
ijassa-135	146	15	model	model	NOUN
ijassa-135	146	16	3	3	NUM
ijassa-135	146	17	case	case	NOUN
ijassa-135	146	18	studies	study	NOUN
ijassa-135	146	19	in	in	ADP
ijassa-135	146	20	this	this	DET
ijassa-135	146	21	section	section	NOUN
ijassa-135	146	22	,	,	PUNCT
ijassa-135	146	23	we	we	PRON
ijassa-135	146	24	will	will	AUX
ijassa-135	146	25	use	use	VERB
ijassa-135	146	26	case	case	NOUN
ijassa-135	146	27	studies	study	NOUN
ijassa-135	146	28	to	to	PART
ijassa-135	146	29	illustrate	illustrate	VERB
ijassa-135	146	30	the	the	DET
ijassa-135	146	31	systemic	systemic	ADJ
ijassa-135	146	32	yoyo	yoyo	PROPN
ijassa-135	146	33	model	model	NOUN
ijassa-135	146	34	and	and	CCONJ
ijassa-135	146	35	the	the	DET
ijassa-135	146	36	evolutionary	evolutionary	ADJ
ijassa-135	146	37	process	process	NOUN
ijassa-135	146	38	naturally	naturally	ADV
ijassa-135	146	39	existing	exist	VERB
ijassa-135	146	40	in	in	ADP
ijassa-135	146	41	system	system	NOUN
ijassa-135	146	42	evaluations	evaluation	NOUN
ijassa-135	146	43	and	and	CCONJ
ijassa-135	146	44	estimations	estimation	NOUN
ijassa-135	146	45	.	.	PUNCT
ijassa-135	147	1	fig.2	fig.2	PROPN
ijassa-135	147	2	shows	show	VERB
ijassa-135	147	3	the	the	DET
ijassa-135	147	4	connection	connection	NOUN
ijassa-135	147	5	of	of	ADP
ijassa-135	147	6	these	these	DET
ijassa-135	147	7	examples	example	NOUN
ijassa-135	147	8	and	and	CCONJ
ijassa-135	147	9	their	their	PRON
ijassa-135	147	10	individual	individual	ADJ
ijassa-135	147	11	relationships	relationship	NOUN
ijassa-135	147	12	with	with	ADP
ijassa-135	147	13	the	the	DET
ijassa-135	147	14	information	information	NOUN
ijassa-135	147	15	flow	flow	NOUN
ijassa-135	147	16	of	of	ADP
ijassa-135	147	17	the	the	DET
ijassa-135	147	18	systemic	systemic	ADJ
ijassa-135	147	19	yoyo	yoyo	PROPN
ijassa-135	147	20	model	model	NOUN
ijassa-135	147	21	.	.	PUNCT
ijassa-135	148	1	we	we	PRON
ijassa-135	148	2	will	will	AUX
ijassa-135	148	3	mainly	mainly	ADV
ijassa-135	148	4	consider	consider	VERB
ijassa-135	148	5	the	the	DET
ijassa-135	148	6	scenario	scenario	NOUN
ijassa-135	148	7	of	of	ADP
ijassa-135	148	8	supplementing	supplement	VERB
ijassa-135	148	9	prior	prior	ADJ
ijassa-135	148	10	information	information	NOUN
ijassa-135	148	11	.	.	PUNCT
ijassa-135	149	1	because	because	SCONJ
ijassa-135	149	2	of	of	ADP
ijassa-135	149	3	the	the	DET
ijassa-135	149	4	shortage	shortage	NOUN
ijassa-135	149	5	of	of	ADP
ijassa-135	149	6	observational	observational	ADJ
ijassa-135	149	7	data	datum	NOUN
ijassa-135	149	8	,	,	PUNCT
ijassa-135	149	9	the	the	DET
ijassa-135	149	10	convergence	convergence	NOUN
ijassa-135	149	11	of	of	ADP
ijassa-135	149	12	the	the	DET
ijassa-135	149	13	system	system	NOUN
ijassa-135	149	14	evaluation	evaluation	NOUN
ijassa-135	149	15	and	and	CCONJ
ijassa-135	149	16	estimation	estimation	NOUN
ijassa-135	149	17	process	process	NOUN
ijassa-135	149	18	is	be	AUX
ijassa-135	149	19	very	very	ADV
ijassa-135	149	20	slow	slow	ADJ
ijassa-135	149	21	or	or	CCONJ
ijassa-135	149	22	becomes	become	VERB
ijassa-135	149	23	stagnant	stagnant	ADJ
ijassa-135	149	24	after	after	ADP
ijassa-135	149	25	converging	converge	VERB
ijassa-135	149	26	to	to	ADP
ijassa-135	149	27	a	a	DET
ijassa-135	149	28	certain	certain	ADJ
ijassa-135	149	29	degree	degree	NOUN
ijassa-135	149	30	.	.	PUNCT
ijassa-135	150	1	however	however	ADV
ijassa-135	150	2	,	,	PUNCT
ijassa-135	150	3	after	after	SCONJ
ijassa-135	150	4	additional	additional	ADJ
ijassa-135	150	5	prior	prior	ADJ
ijassa-135	150	6	information	information	NOUN
ijassa-135	150	7	becomes	become	VERB
ijassa-135	150	8	available	available	ADJ
ijassa-135	150	9	,	,	PUNCT
ijassa-135	150	10	the	the	DET
ijassa-135	150	11	stagnated	stagnate	VERB
ijassa-135	150	12	process	process	NOUN
ijassa-135	150	13	will	will	AUX
ijassa-135	150	14	continue	continue	VERB
ijassa-135	150	15	to	to	PART
ijassa-135	150	16	converge	converge	VERB
ijassa-135	150	17	;	;	PUNCT
ijassa-135	150	18	and	and	CCONJ
ijassa-135	150	19	the	the	DET
ijassa-135	150	20	speed	speed	NOUN
ijassa-135	150	21	of	of	ADP
ijassa-135	150	22	the	the	DET
ijassa-135	150	23	resumed	resume	VERB
ijassa-135	150	24	convergence	convergence	NOUN
ijassa-135	150	25	is	be	AUX
ijassa-135	150	26	dependent	dependent	ADJ
ijassa-135	150	27	on	on	ADP
ijassa-135	150	28	the	the	DET
ijassa-135	150	29	quality	quality	NOUN
ijassa-135	150	30	of	of	ADP
ijassa-135	150	31	the	the	DET
ijassa-135	150	32	newly	newly	ADV
ijassa-135	150	33	supplied	supply	VERB
ijassa-135	150	34	prior	prior	ADJ
ijassa-135	150	35	information	information	NOUN
ijassa-135	150	36	and	and	CCONJ
ijassa-135	150	37	how	how	SCONJ
ijassa-135	150	38	consistent	consistent	ADJ
ijassa-135	150	39	it	it	PRON
ijassa-135	150	40	is	be	AUX
ijassa-135	150	41	with	with	ADP
ijassa-135	150	42	the	the	DET
ijassa-135	150	43	observational	observational	ADJ
ijassa-135	150	44	data	datum	NOUN
ijassa-135	150	45	.	.	PUNCT
ijassa-135	151	1	we	we	PRON
ijassa-135	151	2	will	will	AUX
ijassa-135	151	3	look	look	VERB
ijassa-135	151	4	at	at	ADP
ijassa-135	151	5	three	three	NUM
ijassa-135	151	6	examples	example	NOUN
ijassa-135	151	7	to	to	PART
ijassa-135	151	8	respectively	respectively	ADV
ijassa-135	151	9	illustrate	illustrate	VERB
ijassa-135	151	10	the	the	DET
ijassa-135	151	11	following	following	NOUN
ijassa-135	151	12	:	:	PUNCT
ijassa-135	151	13	(	(	PUNCT
ijassa-135	151	14	1	1	X
ijassa-135	151	15	)	)	PUNCT
ijassa-135	151	16	how	how	SCONJ
ijassa-135	151	17	to	to	PART
ijassa-135	151	18	quantitatively	quantitatively	ADV
ijassa-135	151	19	measure	measure	VERB
ijassa-135	151	20	both	both	CCONJ
ijassa-135	151	21	the	the	DET
ijassa-135	151	22	prior	prior	ADJ
ijassa-135	151	23	and	and	CCONJ
ijassa-135	151	24	data	datum	NOUN
ijassa-135	151	25	information	information	NOUN
ijassa-135	151	26	;	;	PUNCT
ijassa-135	151	27	(	(	PUNCT
ijassa-135	151	28	2	2	X
ijassa-135	151	29	)	)	PUNCT
ijassa-135	151	30	how	how	SCONJ
ijassa-135	151	31	to	to	ADP
ijassa-135	151	32	xiaojun	xiaojun	PROPN
ijassa-135	151	33	duan	duan	PROPN
ijassa-135	151	34	,	,	PUNCT
ijassa-135	151	35	yi	yi	PROPN
ijassa-135	151	36	lin	lin	PROPN
ijassa-135	151	37	:	:	PUNCT
ijassa-135	151	38	ways	way	NOUN
ijassa-135	151	39	of	of	ADP
ijassa-135	151	40	fusing	fuse	VERB
ijassa-135	151	41	different	different	ADJ
ijassa-135	151	42	types	type	NOUN
ijassa-135	151	43	of	of	ADP
ijassa-135	151	44	information	information	NOUN
ijassa-135	151	45	and	and	CCONJ
ijassa-135	151	46	how	how	SCONJ
ijassa-135	151	47	systemic	systemic	ADJ
ijassa-135	151	48	...	...	PUNCT
ijassa-135	151	49	242	242	NUM
ijassa-135	151	50	excavate	excavate	VERB
ijassa-135	151	51	a	a	DET
ijassa-135	151	52	new	new	ADJ
ijassa-135	151	53	source	source	NOUN
ijassa-135	151	54	of	of	ADP
ijassa-135	151	55	observational	observational	ADJ
ijassa-135	151	56	process	process	NOUN
ijassa-135	151	57	data	datum	NOUN
ijassa-135	151	58	so	so	SCONJ
ijassa-135	151	59	that	that	SCONJ
ijassa-135	151	60	the	the	DET
ijassa-135	151	61	quality	quality	NOUN
ijassa-135	151	62	of	of	ADP
ijassa-135	151	63	the	the	DET
ijassa-135	151	64	ultimate	ultimate	ADJ
ijassa-135	151	65	system	system	NOUN
ijassa-135	151	66	evaluation	evaluation	NOUN
ijassa-135	151	67	and	and	CCONJ
ijassa-135	151	68	estimation	estimation	NOUN
ijassa-135	151	69	is	be	AUX
ijassa-135	151	70	improved	improve	VERB
ijassa-135	151	71	;	;	PUNCT
ijassa-135	151	72	and	and	CCONJ
ijassa-135	151	73	(	(	PUNCT
ijassa-135	151	74	3	3	X
ijassa-135	151	75	)	)	PUNCT
ijassa-135	151	76	how	how	SCONJ
ijassa-135	151	77	to	to	PART
ijassa-135	151	78	fuse	fuse	VERB
ijassa-135	151	79	prior	prior	ADJ
ijassa-135	151	80	information	information	NOUN
ijassa-135	151	81	with	with	ADP
ijassa-135	151	82	heterogeneous	heterogeneous	ADJ
ijassa-135	151	83	sets	set	NOUN
ijassa-135	151	84	of	of	ADP
ijassa-135	151	85	data	datum	NOUN
ijassa-135	151	86	effectively	effectively	ADV
ijassa-135	151	87	.	.	PUNCT
ijassa-135	152	1	fig.3	fig.3	PROPN
ijassa-135	152	2	the	the	DET
ijassa-135	152	3	relationship	relationship	NOUN
ijassa-135	152	4	between	between	ADP
ijassa-135	152	5	the	the	DET
ijassa-135	152	6	accuracy	accuracy	NOUN
ijassa-135	152	7	of	of	ADP
ijassa-135	152	8	post	post	NOUN
ijassa-135	152	9	fusion	fusion	NOUN
ijassa-135	152	10	parameter	parameter	NOUN
ijassa-135	152	11	estimation	estimation	NOUN
ijassa-135	152	12	and	and	CCONJ
ijassa-135	152	13	sample	sample	NOUN
ijassa-135	152	14	size	size	NOUN
ijassa-135	152	15	(	(	PUNCT
ijassa-135	152	16	the	the	DET
ijassa-135	152	17	left	left	NOUN
ijassa-135	152	18	represents	represent	VERB
ijassa-135	152	19	posterior	posterior	ADJ
ijassa-135	152	20	fusion	fusion	NOUN
ijassa-135	152	21	estimation	estimation	NOUN
ijassa-135	152	22	accuracy	accuracy	NOUN
ijassa-135	152	23	(	(	PUNCT
ijassa-135	152	24	measured	measure	VERB
ijassa-135	152	25	by	by	ADP
ijassa-135	152	26	information	information	NOUN
ijassa-135	152	27	)	)	PUNCT
ijassa-135	152	28	;	;	PUNCT
ijassa-135	152	29	the	the	DET
ijassa-135	152	30	right	right	NOUN
ijassa-135	152	31	the	the	DET
ijassa-135	152	32	posterior	posterior	ADJ
ijassa-135	152	33	fusion	fusion	NOUN
ijassa-135	152	34	accuracy	accuracy	NOUN
ijassa-135	152	35	improvement	improvement	NOUN
ijassa-135	152	36	(	(	PUNCT
ijassa-135	152	37	measured	measure	VERB
ijassa-135	152	38	by	by	ADP
ijassa-135	152	39	gain	gain	NOUN
ijassa-135	152	40	in	in	ADP
ijassa-135	152	41	information	information	NOUN
ijassa-135	152	42	)	)	PUNCT
ijassa-135	152	43	)	)	PUNCT
ijassa-135	152	44	table	table	NOUN
ijassa-135	152	45	1	1	NUM
ijassa-135	152	46	the	the	DET
ijassa-135	152	47	relation	relation	NOUN
ijassa-135	152	48	between	between	ADP
ijassa-135	152	49	the	the	DET
ijassa-135	152	50	fisher	fisher	PROPN
ijassa-135	152	51	information	information	NOUN
ijassa-135	152	52	gain	gain	NOUN
ijassa-135	152	53	and	and	CCONJ
ijassa-135	152	54	the	the	DET
ijassa-135	152	55	increase	increase	NOUN
ijassa-135	152	56	in	in	ADP
ijassa-135	152	57	sample	sample	NOUN
ijassa-135	152	58	size	size	NOUN
ijassa-135	152	59	increase	increase	NOUN
ijassa-135	152	60	of	of	ADP
ijassa-135	152	61	sample	sample	NOUN
ijassa-135	152	62	size	size	NOUN
ijassa-135	152	63	1	1	NUM
ijassa-135	152	64	2	2	NUM
ijassa-135	152	65	3	3	NUM
ijassa-135	152	66	4	4	NUM
ijassa-135	152	67	5	5	NUM
ijassa-135	152	68	6	6	NUM
ijassa-135	152	69	7	7	NUM
ijassa-135	152	70	informa(1)without	informa(1)without	NOUN
ijassa-135	152	71	prior	prior	ADJ
ijassa-135	152	72	29.2893	29.2893	NUM
ijassa-135	152	73	12.9757	12.9757	NUM
ijassa-135	152	74	7.7350	7.7350	NUM
ijassa-135	152	75	5.2786	5.2786	NUM
ijassa-135	152	76	3.8965	3.8965	NUM
ijassa-135	152	77	3.0284	3.0284	NUM
ijassa-135	152	78	2.4411	2.4411	NUM
ijassa-135	152	79	(	(	PUNCT
ijassa-135	152	80	2)fuse	2)fuse	NUM
ijassa-135	152	81	prior	prior	ADV
ijassa-135	152	82	,	,	PUNCT
ijassa-135	152	83	w	w	NOUN
ijassa-135	152	84	=	=	NOUN
ijassa-135	152	85	0.4	0.4	NUM
ijassa-135	152	86	9.3127	9.3127	NUM
ijassa-135	152	87	6.0794	6.0794	NUM
ijassa-135	152	88	4.3675	4.3675	NUM
ijassa-135	152	89	3.3328	3.3328	NUM
ijassa-135	152	90	2.6511	2.6511	NUM
ijassa-135	152	91	2.1741	2.1741	NUM
ijassa-135	152	92	1.8249	1.8249	NUM
ijassa-135	152	93	tion	tion	NOUN
ijassa-135	152	94	gain	gain	NOUN
ijassa-135	152	95	(	(	PUNCT
ijassa-135	152	96	3)fuse	3)fuse	NUM
ijassa-135	152	97	prior	prior	ADV
ijassa-135	152	98	,	,	PUNCT
ijassa-135	152	99	w	w	NOUN
ijassa-135	152	100	=	=	SYM
ijassa-135	152	101	1	1	NUM
ijassa-135	152	102	3.8965	3.8965	NUM
ijassa-135	152	103	3.0284	3.0284	NUM
ijassa-135	152	104	2.4411	2.4411	NUM
ijassa-135	152	105	2.0220	2.0220	NUM
ijassa-135	152	106	1.7106	1.7106	NUM
ijassa-135	152	107	1.4716	1.4716	NUM
ijassa-135	152	108	1.2836	1.2836	NUM
ijassa-135	152	109	increase	increase	NOUN
ijassa-135	152	110	of	of	ADP
ijassa-135	152	111	sample	sample	NOUN
ijassa-135	152	112	size	size	NOUN
ijassa-135	152	113	8	8	NUM
ijassa-135	152	114	9	9	NUM
ijassa-135	152	115	10	10	NUM
ijassa-135	152	116	11	11	NUM
ijassa-135	152	117	12	12	NUM
ijassa-135	152	118	13	13	NUM
ijassa-135	152	119	14	14	NUM
ijassa-135	152	120	informa(1)without	informa(1)without	NOUN
ijassa-135	152	121	prior	prior	ADV
ijassa-135	152	122	2.0220	2.0220	NUM
ijassa-135	152	123	1.7106	1.7106	NUM
ijassa-135	152	124	1.4716	1.4716	NUM
ijassa-135	152	125	1.2836	1.2836	NUM
ijassa-135	152	126	1.1325	1.1325	NUM
ijassa-135	152	127	1.0089	1.0089	NUM
ijassa-135	152	128	0.9062	0.9062	NUM
ijassa-135	152	129	(	(	PUNCT
ijassa-135	152	130	2)fuse	2)fuse	NUM
ijassa-135	152	131	prior	prior	ADV
ijassa-135	152	132	,	,	PUNCT
ijassa-135	152	133	w	w	NOUN
ijassa-135	152	134	=	=	NOUN
ijassa-135	153	1	0.4	0.4	NUM
ijassa-135	153	2	1.5601	1.5601	NUM
ijassa-135	153	3	1.3537	1.3537	NUM
ijassa-135	153	4	1.1892	1.1892	NUM
ijassa-135	153	5	1.0555	1.0555	NUM
ijassa-135	153	6	0.9451	0.9451	NUM
ijassa-135	153	7	0.8527	0.8527	NUM
ijassa-135	153	8	0.7744	0.7744	NUM
ijassa-135	153	9	tion	tion	NOUN
ijassa-135	153	10	gain	gain	NOUN
ijassa-135	153	11	(	(	PUNCT
ijassa-135	153	12	3)fuse	3)fuse	NUM
ijassa-135	153	13	prior	prior	ADV
ijassa-135	153	14	,	,	PUNCT
ijassa-135	153	15	w	w	NOUN
ijassa-135	153	16	=	=	SYM
ijassa-135	153	17	1	1	NUM
ijassa-135	153	18	1.1325	1.1325	NUM
ijassa-135	153	19	1.0089	1.0089	NUM
ijassa-135	153	20	0.9062	0.9062	NUM
ijassa-135	153	21	0.8199	0.8199	NUM
ijassa-135	153	22	0.7464	0.7464	NUM
ijassa-135	153	23	0.6833	0.6833	NUM
ijassa-135	153	24	0.6287	0.6287	NUM
ijassa-135	153	25	increase	increase	NOUN
ijassa-135	153	26	of	of	ADP
ijassa-135	153	27	sample	sample	NOUN
ijassa-135	153	28	size	size	NOUN
ijassa-135	153	29	15	15	NUM
ijassa-135	153	30	16	16	NUM
ijassa-135	153	31	17	17	NUM
ijassa-135	153	32	18	18	NUM
ijassa-135	153	33	19	19	NUM
ijassa-135	153	34	informa(1)without	informa(1)without	NOUN
ijassa-135	153	35	prior	prior	ADV
ijassa-135	153	36	0.8199	0.8199	NUM
ijassa-135	153	37	0.7464	0.7464	NUM
ijassa-135	153	38	0.6833	0.6833	NUM
ijassa-135	153	39	0.6287	0.6287	NUM
ijassa-135	153	40	0.5809	0.5809	NUM
ijassa-135	153	41	(	(	PUNCT
ijassa-135	153	42	2)fuse	2)fuse	NUM
ijassa-135	153	43	prior	prior	ADV
ijassa-135	153	44	,	,	PUNCT
ijassa-135	153	45	w	w	NOUN
ijassa-135	153	46	=	=	NOUN
ijassa-135	153	47	0.4	0.4	NUM
ijassa-135	153	48	0.7075	0.7075	NUM
ijassa-135	153	49	0.6496	0.6496	NUM
ijassa-135	153	50	0.5992	0.5992	NUM
ijassa-135	153	51	0.5551	0.5551	NUM
ijassa-135	153	52	0.5161	0.5161	NUM
ijassa-135	153	53	tion	tion	NOUN
ijassa-135	153	54	gain	gain	NOUN
ijassa-135	153	55	(	(	PUNCT
ijassa-135	153	56	3)fuse	3)fuse	NUM
ijassa-135	153	57	prior	prior	ADV
ijassa-135	153	58	,	,	PUNCT
ijassa-135	153	59	w	w	NOUN
ijassa-135	153	60	=	=	NOUN
ijassa-135	153	61	1	1	NUM
ijassa-135	153	62	0.5809	0.5809	NUM
ijassa-135	153	63	0.5389	0.5389	NUM
ijassa-135	153	64	0.5017	0.5017	NUM
ijassa-135	153	65	0.4686	0.4686	NUM
ijassa-135	153	66	0.4390	0.4390	NUM
ijassa-135	153	67	example1	example1	NOUN
ijassa-135	153	68	.	.	PUNCT
ijassa-135	154	1	let	let	VERB
ijassa-135	154	2	us	we	PRON
ijassa-135	154	3	look	look	VERB
ijassa-135	154	4	at	at	ADP
ijassa-135	154	5	the	the	DET
ijassa-135	154	6	information	information	NOUN
ijassa-135	154	7	measurement	measurement	NOUN
ijassa-135	154	8	of	of	ADP
ijassa-135	154	9	the	the	DET
ijassa-135	154	10	prior	prior	ADJ
ijassa-135	154	11	and	and	CCONJ
ijassa-135	154	12	observational	observational	ADJ
ijassa-135	154	13	data	datum	NOUN
ijassa-135	154	14	.	.	PUNCT
ijassa-135	155	1	take	take	VERB
ijassa-135	155	2	the	the	DET
ijassa-135	155	3	prior	prior	ADJ
ijassa-135	155	4	parameter	parameter	NOUN
ijassa-135	155	5	variance	variance	NOUN
ijassa-135	155	6	to	to	PART
ijassa-135	155	7	be	be	AUX
ijassa-135	155	8	sigma0	sigma0	NOUN
ijassa-135	155	9	=	=	NOUN
ijassa-135	155	10	50	50	NUM
ijassa-135	155	11	and	and	CCONJ
ijassa-135	155	12	the	the	DET
ijassa-135	155	13	sample	sample	NOUN
ijassa-135	155	14	variance	variance	NOUN
ijassa-135	155	15	sigma1	sigma1	X
ijassa-135	156	1	=	=	SYM
ijassa-135	156	2	100	100	X
ijassa-135	156	3	.	.	PUNCT
ijassa-135	157	1	let	let	VERB
ijassa-135	157	2	us	we	PRON
ijassa-135	157	3	vary	vary	VERB
ijassa-135	157	4	the	the	DET
ijassa-135	157	5	sample	sample	NOUN
ijassa-135	157	6	size	size	NOUN
ijassa-135	157	7	from	from	ADP
ijassa-135	157	8	1	1	NUM
ijassa-135	157	9	to	to	PART
ijassa-135	157	10	20	20	NUM
ijassa-135	157	11	and	and	CCONJ
ijassa-135	157	12	consider	consider	VERB
ijassa-135	157	13	three	three	NUM
ijassa-135	157	14	scenarios	scenario	NOUN
ijassa-135	157	15	:	:	PUNCT
ijassa-135	157	16	no	no	DET
ijassa-135	157	17	prior	prior	ADJ
ijassa-135	157	18	information	information	NOUN
ijassa-135	157	19	is	be	AUX
ijassa-135	157	20	fused	fuse	VERB
ijassa-135	157	21	,	,	PUNCT
ijassa-135	157	22	and	and	CCONJ
ijassa-135	157	23	prior	prior	ADJ
ijassa-135	157	24	information	information	NOUN
ijassa-135	157	25	is	be	AUX
ijassa-135	157	26	fused	fuse	VERB
ijassa-135	157	27	with	with	ADP
ijassa-135	157	28	the	the	DET
ijassa-135	157	29	243	243	NUM
ijassa-135	157	30	advances	advance	NOUN
ijassa-135	157	31	in	in	ADP
ijassa-135	157	32	systems	system	NOUN
ijassa-135	157	33	science	science	NOUN
ijassa-135	157	34	and	and	CCONJ
ijassa-135	157	35	applications	application	NOUN
ijassa-135	157	36	(	(	PUNCT
ijassa-135	157	37	2013	2013	NUM
ijassa-135	157	38	)	)	PUNCT
ijassa-135	157	39	vol.13	vol.13	NOUN
ijassa-135	157	40	no.3	no.3	VERB
ijassa-135	157	41	consistency	consistency	NOUN
ijassa-135	157	42	weights	weight	VERB
ijassa-135	157	43	w	w	NOUN
ijassa-135	157	44	=	=	SYM
ijassa-135	157	45	1	1	NUM
ijassa-135	157	46	and	and	CCONJ
ijassa-135	157	47	w	w	NOUN
ijassa-135	157	48	=	=	NOUN
ijassa-135	157	49	0.4	0.4	NUM
ijassa-135	157	50	,	,	PUNCT
ijassa-135	157	51	respectively	respectively	ADV
ijassa-135	157	52	.	.	PUNCT
ijassa-135	158	1	figure	figure	NOUN
ijassa-135	158	2	3	3	NUM
ijassa-135	158	3	shows	show	VERB
ijassa-135	158	4	the	the	DET
ijassa-135	158	5	relationship	relationship	NOUN
ijassa-135	158	6	between	between	ADP
ijassa-135	158	7	the	the	DET
ijassa-135	158	8	accuracy	accuracy	NOUN
ijassa-135	158	9	of	of	ADP
ijassa-135	158	10	the	the	DET
ijassa-135	158	11	post	post	ADJ
ijassa-135	158	12	-	-	ADJ
ijassa-135	158	13	fusion	fusion	ADJ
ijassa-135	158	14	parameter	parameter	NOUN
ijassa-135	158	15	estimation	estimation	NOUN
ijassa-135	158	16	and	and	CCONJ
ijassa-135	158	17	the	the	DET
ijassa-135	158	18	sample	sample	NOUN
ijassa-135	158	19	size	size	NOUN
ijassa-135	158	20	.	.	PUNCT
ijassa-135	159	1	the	the	DET
ijassa-135	159	2	fisher	fisher	PROPN
ijassa-135	159	3	information	information	NOUN
ijassa-135	159	4	gain	gain	NOUN
ijassa-135	159	5	is	be	AUX
ijassa-135	159	6	shown	show	VERB
ijassa-135	159	7	in	in	ADP
ijassa-135	159	8	table	table	NOUN
ijassa-135	159	9	1	1	NUM
ijassa-135	159	10	.	.	PUNCT
ijassa-135	160	1	evidently	evidently	ADV
ijassa-135	160	2	,	,	PUNCT
ijassa-135	160	3	when	when	SCONJ
ijassa-135	160	4	the	the	DET
ijassa-135	160	5	threshold	threshold	NOUN
ijassa-135	160	6	of	of	ADP
ijassa-135	160	7	fusion	fusion	NOUN
ijassa-135	160	8	accuracy	accuracy	NOUN
ijassa-135	160	9	is	be	AUX
ijassa-135	160	10	fixed	fix	VERB
ijassa-135	160	11	at	at	ADP
ijassa-135	160	12	1.5	1.5	NUM
ijassa-135	160	13	,	,	PUNCT
ijassa-135	160	14	one	one	PRON
ijassa-135	160	15	needs	need	VERB
ijassa-135	160	16	to	to	PART
ijassa-135	160	17	repeat	repeat	VERB
ijassa-135	160	18	his	his	PRON
ijassa-135	160	19	test	test	NOUN
ijassa-135	160	20	ten	ten	NUM
ijassa-135	160	21	times	time	NOUN
ijassa-135	160	22	if	if	SCONJ
ijassa-135	160	23	he	he	PRON
ijassa-135	160	24	does	do	AUX
ijassa-135	160	25	not	not	PART
ijassa-135	160	26	fuse	fuse	VERB
ijassa-135	160	27	any	any	DET
ijassa-135	160	28	additional	additional	ADJ
ijassa-135	160	29	prior	prior	ADJ
ijassa-135	160	30	information	information	NOUN
ijassa-135	160	31	;	;	PUNCT
ijassa-135	160	32	if	if	SCONJ
ijassa-135	160	33	he	he	PRON
ijassa-135	160	34	fuses	fuse	VERB
ijassa-135	160	35	additional	additional	ADJ
ijassa-135	160	36	prior	prior	ADJ
ijassa-135	160	37	information	information	NOUN
ijassa-135	160	38	and	and	CCONJ
ijassa-135	160	39	sets	set	VERB
ijassa-135	160	40	its	its	PRON
ijassa-135	160	41	weight	weight	NOUN
ijassa-135	160	42	at	at	ADP
ijassa-135	160	43	w	w	PROPN
ijassa-135	160	44	=	=	PROPN
ijassa-135	160	45	0.4	0.4	NUM
ijassa-135	160	46	(	(	PUNCT
ijassa-135	160	47	that	that	PRON
ijassa-135	160	48	means	mean	VERB
ijassa-135	160	49	the	the	DET
ijassa-135	160	50	consistency	consistency	NOUN
ijassa-135	160	51	between	between	ADP
ijassa-135	160	52	the	the	DET
ijassa-135	160	53	additional	additional	ADJ
ijassa-135	160	54	prior	prior	ADJ
ijassa-135	160	55	information	information	NOUN
ijassa-135	160	56	and	and	CCONJ
ijassa-135	160	57	the	the	DET
ijassa-135	160	58	test	test	NOUN
ijassa-135	160	59	data	datum	NOUN
ijassa-135	160	60	is	be	AUX
ijassa-135	160	61	measured	measure	VERB
ijassa-135	160	62	by	by	ADP
ijassa-135	160	63	weight	weight	NOUN
ijassa-135	160	64	0.4	0.4	NUM
ijassa-135	160	65	)	)	PUNCT
ijassa-135	160	66	,	,	PUNCT
ijassa-135	160	67	then	then	ADV
ijassa-135	160	68	he	he	PRON
ijassa-135	160	69	needs	need	VERB
ijassa-135	160	70	to	to	PART
ijassa-135	160	71	repeat	repeat	VERB
ijassa-135	160	72	the	the	DET
ijassa-135	160	73	test	test	NOUN
ijassa-135	160	74	9	9	NUM
ijassa-135	160	75	times	time	NOUN
ijassa-135	160	76	;	;	PUNCT
ijassa-135	160	77	and	and	CCONJ
ijassa-135	160	78	if	if	SCONJ
ijassa-135	160	79	he	he	PRON
ijassa-135	160	80	fuses	fuse	VERB
ijassa-135	160	81	additional	additional	ADJ
ijassa-135	160	82	prior	prior	ADJ
ijassa-135	160	83	information	information	NOUN
ijassa-135	160	84	with	with	ADP
ijassa-135	160	85	weight	weight	NOUN
ijassa-135	160	86	set	set	VERB
ijassa-135	160	87	at	at	ADP
ijassa-135	160	88	w	w	PROPN
ijassa-135	160	89	=	=	SYM
ijassa-135	160	90	1	1	NUM
ijassa-135	160	91	(	(	PUNCT
ijassa-135	160	92	that	that	PRON
ijassa-135	160	93	means	mean	VERB
ijassa-135	160	94	the	the	DET
ijassa-135	160	95	additional	additional	ADJ
ijassa-135	160	96	prior	prior	ADJ
ijassa-135	160	97	information	information	NOUN
ijassa-135	160	98	has	have	VERB
ijassa-135	160	99	very	very	ADV
ijassa-135	160	100	good	good	ADJ
ijassa-135	160	101	consistency	consistency	NOUN
ijassa-135	160	102	with	with	ADP
ijassa-135	160	103	the	the	DET
ijassa-135	160	104	test	test	NOUN
ijassa-135	160	105	data	datum	NOUN
ijassa-135	160	106	)	)	PUNCT
ijassa-135	160	107	,	,	PUNCT
ijassa-135	160	108	then	then	ADV
ijassa-135	160	109	he	he	PRON
ijassa-135	160	110	only	only	ADV
ijassa-135	160	111	needs	need	VERB
ijassa-135	160	112	to	to	PART
ijassa-135	160	113	repeat	repeat	VERB
ijassa-135	160	114	the	the	DET
ijassa-135	160	115	test	test	NOUN
ijassa-135	160	116	6	6	NUM
ijassa-135	160	117	times	time	NOUN
ijassa-135	160	118	.	.	PUNCT
ijassa-135	161	1	this	this	DET
ijassa-135	161	2	result	result	NOUN
ijassa-135	161	3	indicates	indicate	VERB
ijassa-135	161	4	that	that	SCONJ
ijassa-135	161	5	with	with	ADP
ijassa-135	161	6	correct	correct	ADJ
ijassa-135	161	7	fusion	fusion	NOUN
ijassa-135	161	8	of	of	ADP
ijassa-135	161	9	prior	prior	ADJ
ijassa-135	161	10	information	information	NOUN
ijassa-135	161	11	,	,	PUNCT
ijassa-135	161	12	the	the	DET
ijassa-135	161	13	same	same	ADJ
ijassa-135	161	14	requirement	requirement	NOUN
ijassa-135	161	15	of	of	ADP
ijassa-135	161	16	precision	precision	NOUN
ijassa-135	161	17	can	can	AUX
ijassa-135	161	18	be	be	AUX
ijassa-135	161	19	met	meet	VERB
ijassa-135	161	20	with	with	ADP
ijassa-135	161	21	a	a	DET
ijassa-135	161	22	fewer	few	ADJ
ijassa-135	161	23	number	number	NOUN
ijassa-135	161	24	of	of	ADP
ijassa-135	161	25	times	time	NOUN
ijassa-135	161	26	the	the	DET
ijassa-135	161	27	test	test	NOUN
ijassa-135	161	28	is	be	AUX
ijassa-135	161	29	repeated	repeat	VERB
ijassa-135	161	30	.	.	PUNCT
ijassa-135	162	1	example2	example2	PROPN
ijassa-135	162	2	.	.	PUNCT
ijassa-135	163	1	in	in	ADP
ijassa-135	163	2	this	this	DET
ijassa-135	163	3	case	case	NOUN
ijassa-135	163	4	study	study	NOUN
ijassa-135	163	5	,	,	PUNCT
ijassa-135	163	6	we	we	PRON
ijassa-135	163	7	will	will	AUX
ijassa-135	163	8	see	see	VERB
ijassa-135	163	9	how	how	SCONJ
ijassa-135	163	10	we	we	PRON
ijassa-135	163	11	can	can	AUX
ijassa-135	163	12	speed	speed	VERB
ijassa-135	163	13	up	up	ADP
ijassa-135	163	14	the	the	DET
ijassa-135	163	15	convergence	convergence	NOUN
ijassa-135	163	16	of	of	ADP
ijassa-135	163	17	our	our	PRON
ijassa-135	163	18	recognition	recognition	NOUN
ijassa-135	163	19	of	of	ADP
ijassa-135	163	20	the	the	DET
ijassa-135	163	21	underlying	underlie	VERB
ijassa-135	163	22	system	system	NOUN
ijassa-135	163	23	by	by	ADP
ijassa-135	163	24	making	make	VERB
ijassa-135	163	25	use	use	NOUN
ijassa-135	163	26	of	of	ADP
ijassa-135	163	27	process	process	NOUN
ijassa-135	163	28	information	information	NOUN
ijassa-135	163	29	and	and	CCONJ
ijassa-135	163	30	data	datum	NOUN
ijassa-135	163	31	.	.	PUNCT
ijassa-135	164	1	the	the	DET
ijassa-135	164	2	precision	precision	NOUN
ijassa-135	164	3	evaluation	evaluation	NOUN
ijassa-135	164	4	of	of	ADP
ijassa-135	164	5	active	active	ADJ
ijassa-135	164	6	homing	home	VERB
ijassa-135	164	7	radar	radar	NOUN
ijassa-135	164	8	[	[	X
ijassa-135	164	9	6	6	NUM
ijassa-135	164	10	]	]	PUNCT
ijassa-135	164	11	is	be	AUX
ijassa-135	164	12	a	a	DET
ijassa-135	164	13	complex	complex	ADJ
ijassa-135	164	14	recognition	recognition	NOUN
ijassa-135	164	15	process	process	NOUN
ijassa-135	164	16	of	of	ADP
ijassa-135	164	17	systems	system	NOUN
ijassa-135	164	18	.	.	PUNCT
ijassa-135	165	1	the	the	DET
ijassa-135	165	2	impact	impact	NOUN
ijassa-135	165	3	error	error	NOUN
ijassa-135	165	4	of	of	ADP
ijassa-135	165	5	clustered	clustered	ADJ
ijassa-135	165	6	warhead	warhead	NOUN
ijassa-135	165	7	missiles	missile	NOUN
ijassa-135	165	8	with	with	ADP
ijassa-135	165	9	active	active	ADJ
ijassa-135	165	10	homing	homing	NOUN
ijassa-135	165	11	radar	radar	NOUN
ijassa-135	165	12	is	be	AUX
ijassa-135	165	13	mainly	mainly	ADV
ijassa-135	165	14	composed	compose	VERB
ijassa-135	165	15	of	of	ADP
ijassa-135	165	16	the	the	DET
ijassa-135	165	17	measurement	measurement	NOUN
ijassa-135	165	18	error	error	NOUN
ijassa-135	165	19	of	of	ADP
ijassa-135	165	20	the	the	DET
ijassa-135	165	21	radar	radar	NOUN
ijassa-135	165	22	navigation	navigation	NOUN
ijassa-135	165	23	system	system	NOUN
ijassa-135	165	24	,	,	PUNCT
ijassa-135	165	25	the	the	DET
ijassa-135	165	26	instrumental	instrumental	ADJ
ijassa-135	165	27	error	error	NOUN
ijassa-135	165	28	of	of	ADP
ijassa-135	165	29	the	the	DET
ijassa-135	165	30	inertial	inertial	ADJ
ijassa-135	165	31	navigation	navigation	NOUN
ijassa-135	165	32	system	system	NOUN
ijassa-135	165	33	(	(	PUNCT
ijassa-135	165	34	ins	ins	PROPN
ijassa-135	165	35	)	)	PUNCT
ijassa-135	165	36	,	,	PUNCT
ijassa-135	165	37	the	the	DET
ijassa-135	165	38	method	method	NOUN
ijassa-135	165	39	error	error	NOUN
ijassa-135	165	40	of	of	ADP
ijassa-135	165	41	the	the	DET
ijassa-135	165	42	terminal	terminal	ADJ
ijassa-135	165	43	guidance	guidance	NOUN
ijassa-135	165	44	,	,	PUNCT
ijassa-135	165	45	the	the	DET
ijassa-135	165	46	error	error	NOUN
ijassa-135	165	47	of	of	ADP
ijassa-135	165	48	the	the	DET
ijassa-135	165	49	distribution	distribution	NOUN
ijassa-135	165	50	,	,	PUNCT
ijassa-135	165	51	and	and	CCONJ
ijassa-135	165	52	some	some	DET
ijassa-135	165	53	random	random	ADJ
ijassa-135	165	54	error	error	NOUN
ijassa-135	165	55	.	.	PUNCT
ijassa-135	166	1	let	let	VERB
ijassa-135	166	2	us	we	PRON
ijassa-135	166	3	take	take	VERB
ijassa-135	166	4	the	the	DET
ijassa-135	166	5	impact	impact	NOUN
ijassa-135	166	6	error	error	NOUN
ijassa-135	166	7	of	of	ADP
ijassa-135	166	8	an	an	DET
ijassa-135	166	9	active	active	ADJ
ijassa-135	166	10	homing	home	VERB
ijassa-135	166	11	radar	radar	NOUN
ijassa-135	166	12	system	system	NOUN
ijassa-135	166	13	[	[	X
ijassa-135	166	14	6	6	NUM
ijassa-135	166	15	]	]	PUNCT
ijassa-135	166	16	as	as	ADP
ijassa-135	166	17	our	our	PRON
ijassa-135	166	18	system	system	NOUN
ijassa-135	166	19	evaluation	evaluation	NOUN
ijassa-135	166	20	performance	performance	NOUN
ijassa-135	166	21	index	index	NOUN
ijassa-135	166	22	and	and	CCONJ
ijassa-135	166	23	compare	compare	VERB
ijassa-135	166	24	the	the	DET
ijassa-135	166	25	outcomes	outcome	NOUN
ijassa-135	166	26	of	of	ADP
ijassa-135	166	27	the	the	DET
ijassa-135	166	28	following	follow	VERB
ijassa-135	166	29	two	two	NUM
ijassa-135	166	30	methods	method	NOUN
ijassa-135	166	31	:	:	PUNCT
ijassa-135	166	32	one	one	NUM
ijassa-135	166	33	is	be	AUX
ijassa-135	166	34	to	to	PART
ijassa-135	166	35	fuse	fuse	VERB
ijassa-135	166	36	the	the	DET
ijassa-135	166	37	different	different	ADJ
ijassa-135	166	38	observational	observational	ADJ
ijassa-135	166	39	information	information	NOUN
ijassa-135	166	40	,	,	PUNCT
ijassa-135	166	41	directly	directly	ADV
ijassa-135	166	42	observed	observe	VERB
ijassa-135	166	43	index	index	NOUN
ijassa-135	166	44	data	datum	NOUN
ijassa-135	166	45	,	,	PUNCT
ijassa-135	166	46	and	and	CCONJ
ijassa-135	166	47	some	some	DET
ijassa-135	166	48	indirectly	indirectly	ADV
ijassa-135	166	49	observed	observe	VERB
ijassa-135	166	50	data	datum	NOUN
ijassa-135	166	51	;	;	PUNCT
ijassa-135	166	52	and	and	CCONJ
ijassa-135	166	53	the	the	DET
ijassa-135	166	54	other	other	ADJ
ijassa-135	166	55	the	the	DET
ijassa-135	166	56	point	point	NOUN
ijassa-135	166	57	estimate	estimate	NOUN
ijassa-135	166	58	method	method	NOUN
ijassa-135	166	59	[	[	X
ijassa-135	166	60	7	7	X
ijassa-135	166	61	]	]	PUNCT
ijassa-135	166	62	for	for	ADP
ijassa-135	166	63	the	the	DET
ijassa-135	166	64	impact	impact	NOUN
ijassa-135	166	65	error	error	NOUN
ijassa-135	166	66	.	.	PUNCT
ijassa-135	167	1	the	the	DET
ijassa-135	167	2	main	main	ADJ
ijassa-135	167	3	difference	difference	NOUN
ijassa-135	167	4	here	here	ADV
ijassa-135	167	5	lies	lie	VERB
ijassa-135	167	6	in	in	ADP
ijassa-135	167	7	that	that	SCONJ
ijassa-135	167	8	the	the	DET
ijassa-135	167	9	later	later	ADJ
ijassa-135	167	10	,	,	PUNCT
ijassa-135	167	11	more	more	ADV
ijassa-135	167	12	traditional	traditional	ADJ
ijassa-135	167	13	method	method	NOUN
ijassa-135	167	14	uses	use	VERB
ijassa-135	167	15	only	only	ADV
ijassa-135	167	16	the	the	DET
ijassa-135	167	17	final	final	ADJ
ijassa-135	167	18	impact	impact	NOUN
ijassa-135	167	19	point	point	NOUN
ijassa-135	167	20	error	error	NOUN
ijassa-135	167	21	information	information	NOUN
ijassa-135	167	22	so	so	SCONJ
ijassa-135	167	23	that	that	SCONJ
ijassa-135	167	24	the	the	DET
ijassa-135	167	25	evaluation	evaluation	NOUN
ijassa-135	167	26	outcomes	outcome	NOUN
ijassa-135	167	27	are	be	AUX
ijassa-135	167	28	strongly	strongly	ADV
ijassa-135	167	29	influenced	influence	VERB
ijassa-135	167	30	by	by	ADP
ijassa-135	167	31	the	the	DET
ijassa-135	167	32	random	random	ADJ
ijassa-135	167	33	error	error	NOUN
ijassa-135	167	34	of	of	ADP
ijassa-135	167	35	the	the	DET
ijassa-135	167	36	impact	impact	NOUN
ijassa-135	167	37	points	point	NOUN
ijassa-135	167	38	,	,	PUNCT
ijassa-135	167	39	while	while	SCONJ
ijassa-135	167	40	the	the	DET
ijassa-135	167	41	former	former	ADJ
ijassa-135	167	42	method	method	NOUN
ijassa-135	167	43	validates	validate	VERB
ijassa-135	167	44	the	the	DET
ijassa-135	167	45	procedure	procedure	NOUN
ijassa-135	167	46	error	error	NOUN
ijassa-135	167	47	model	model	NOUN
ijassa-135	167	48	with	with	ADP
ijassa-135	167	49	systematic	systematic	ADJ
ijassa-135	167	50	error	error	NOUN
ijassa-135	167	51	and	and	CCONJ
ijassa-135	167	52	the	the	DET
ijassa-135	167	53	characteristic	characteristic	NOUN
ijassa-135	167	54	of	of	ADP
ijassa-135	167	55	the	the	DET
ijassa-135	167	56	random	random	ADJ
ijassa-135	167	57	error	error	NOUN
ijassa-135	167	58	by	by	ADP
ijassa-135	167	59	making	make	VERB
ijassa-135	167	60	using	use	VERB
ijassa-135	167	61	of	of	ADP
ijassa-135	167	62	all	all	DET
ijassa-135	167	63	the	the	DET
ijassa-135	167	64	observational	observational	ADJ
ijassa-135	167	65	information	information	NOUN
ijassa-135	167	66	.	.	PUNCT
ijassa-135	168	1	that	that	PRON
ijassa-135	168	2	is	be	AUX
ijassa-135	168	3	how	how	SCONJ
ijassa-135	168	4	the	the	DET
ijassa-135	168	5	former	former	ADJ
ijassa-135	168	6	method	method	NOUN
ijassa-135	168	7	provides	provide	VERB
ijassa-135	168	8	more	more	ADV
ijassa-135	168	9	robust	robust	ADJ
ijassa-135	168	10	evaluation	evaluation	NOUN
ijassa-135	168	11	results	result	NOUN
ijassa-135	168	12	.	.	PUNCT
ijassa-135	169	1	in	in	ADP
ijassa-135	169	2	order	order	NOUN
ijassa-135	169	3	to	to	PART
ijassa-135	169	4	avoid	avoid	VERB
ijassa-135	169	5	analyzing	analyze	VERB
ijassa-135	169	6	a	a	DET
ijassa-135	169	7	heterogeneous	heterogeneous	ADJ
ijassa-135	169	8	population	population	NOUN
ijassa-135	169	9	created	create	VERB
ijassa-135	169	10	by	by	ADP
ijassa-135	169	11	different	different	ADJ
ijassa-135	169	12	testing	testing	NOUN
ijassa-135	169	13	states	state	NOUN
ijassa-135	169	14	,	,	PUNCT
ijassa-135	169	15	we	we	PRON
ijassa-135	169	16	will	will	AUX
ijassa-135	169	17	transform	transform	VERB
ijassa-135	169	18	these	these	DET
ijassa-135	169	19	different	different	ADJ
ijassa-135	169	20	testing	testing	NOUN
ijassa-135	169	21	states	state	NOUN
ijassa-135	169	22	to	to	ADP
ijassa-135	169	23	standard	standard	ADJ
ijassa-135	169	24	full	full	ADJ
ijassa-135	169	25	range	range	NOUN
ijassa-135	169	26	process	process	NOUN
ijassa-135	169	27	testing	test	VERB
ijassa-135	169	28	states	state	NOUN
ijassa-135	169	29	so	so	SCONJ
ijassa-135	169	30	that	that	SCONJ
ijassa-135	169	31	the	the	DET
ijassa-135	169	32	consequent	consequent	ADJ
ijassa-135	169	33	analysis	analysis	NOUN
ijassa-135	169	34	will	will	AUX
ijassa-135	169	35	become	become	VERB
ijassa-135	169	36	manageable	manageable	ADJ
ijassa-135	169	37	.	.	PUNCT
ijassa-135	170	1	the	the	DET
ijassa-135	170	2	impact	impact	NOUN
ijassa-135	170	3	errors	error	NOUN
ijassa-135	170	4	of	of	ADP
ijassa-135	170	5	different	different	ADJ
ijassa-135	170	6	testing	testing	NOUN
ijassa-135	170	7	states	state	NOUN
ijassa-135	170	8	are	be	AUX
ijassa-135	170	9	denoted	denote	VERB
ijassa-135	170	10	as	as	SCONJ
ijassa-135	170	11	follows	follow	VERB
ijassa-135	170	12	:	:	PUNCT
ijassa-135	170	13	△	△	NOUN
ijassa-135	170	14	lradar	lradar	NOUN
ijassa-135	170	15	stands	stand	VERB
ijassa-135	170	16	for	for	ADP
ijassa-135	170	17	the	the	DET
ijassa-135	170	18	assessed	assess	VERB
ijassa-135	170	19	impact	impact	NOUN
ijassa-135	170	20	deviation	deviation	NOUN
ijassa-135	170	21	caused	cause	VERB
ijassa-135	170	22	by	by	ADP
ijassa-135	170	23	the	the	DET
ijassa-135	170	24	error	error	NOUN
ijassa-135	170	25	of	of	ADP
ijassa-135	170	26	the	the	DET
ijassa-135	170	27	radar	radar	NOUN
ijassa-135	170	28	measurement	measurement	NOUN
ijassa-135	170	29	in	in	ADP
ijassa-135	170	30	the	the	DET
ijassa-135	170	31	standard	standard	ADJ
ijassa-135	170	32	overall	overall	ADJ
ijassa-135	170	33	operational	operational	ADJ
ijassa-135	170	34	test	test	NOUN
ijassa-135	170	35	;	;	PUNCT
ijassa-135	170	36	∆l̃radar	∆l̃radar	VERB
ijassa-135	170	37	the	the	DET
ijassa-135	170	38	measured	measure	VERB
ijassa-135	170	39	impact	impact	NOUN
ijassa-135	170	40	xiaojun	xiaojun	PROPN
ijassa-135	170	41	duan	duan	PROPN
ijassa-135	170	42	,	,	PUNCT
ijassa-135	170	43	yi	yi	PROPN
ijassa-135	170	44	lin	lin	PROPN
ijassa-135	170	45	:	:	PUNCT
ijassa-135	170	46	ways	way	NOUN
ijassa-135	170	47	of	of	ADP
ijassa-135	170	48	fusing	fuse	VERB
ijassa-135	170	49	different	different	ADJ
ijassa-135	170	50	types	type	NOUN
ijassa-135	170	51	of	of	ADP
ijassa-135	170	52	information	information	NOUN
ijassa-135	170	53	and	and	CCONJ
ijassa-135	170	54	how	how	SCONJ
ijassa-135	170	55	systemic	systemic	ADJ
ijassa-135	170	56	...	...	PUNCT
ijassa-135	170	57	244	244	NUM
ijassa-135	170	58	deviation	deviation	NOUN
ijassa-135	170	59	caused	cause	VERB
ijassa-135	170	60	by	by	ADP
ijassa-135	170	61	the	the	DET
ijassa-135	170	62	error	error	NOUN
ijassa-135	170	63	of	of	ADP
ijassa-135	170	64	radar	radar	NOUN
ijassa-135	170	65	measurement	measurement	NOUN
ijassa-135	170	66	in	in	ADP
ijassa-135	170	67	a	a	DET
ijassa-135	170	68	substitute	substitute	NOUN
ijassa-135	170	69	test	test	NOUN
ijassa-135	170	70	.	.	PUNCT
ijassa-135	171	1	for	for	ADP
ijassa-135	171	2	a	a	DET
ijassa-135	171	3	missile	missile	NOUN
ijassa-135	171	4	with	with	ADP
ijassa-135	171	5	active	active	ADJ
ijassa-135	171	6	homing	homing	NOUN
ijassa-135	171	7	radar	radar	NOUN
ijassa-135	171	8	,	,	PUNCT
ijassa-135	171	9	its	its	PRON
ijassa-135	171	10	warhead	warhead	NOUN
ijassa-135	171	11	-	-	PUNCT
ijassa-135	171	12	target	target	NOUN
ijassa-135	171	13	relative	relative	ADJ
ijassa-135	171	14	positional	positional	ADJ
ijassa-135	171	15	x-	x-	PROPN
ijassa-135	171	16	,	,	PUNCT
ijassa-135	171	17	y-	y-	X
ijassa-135	171	18	,	,	PUNCT
ijassa-135	171	19	and	and	CCONJ
ijassa-135	171	20	z	z	NOUN
ijassa-135	171	21	-	-	PUNCT
ijassa-135	171	22	errors	error	NOUN
ijassa-135	171	23	are	be	AUX
ijassa-135	171	24	mainly	mainly	ADV
ijassa-135	171	25	caused	cause	VERB
ijassa-135	171	26	by	by	ADP
ijassa-135	171	27	its	its	PRON
ijassa-135	171	28	radar	radar	NOUN
ijassa-135	171	29	’s	’s	NOUN
ijassa-135	171	30	measurement	measurement	NOUN
ijassa-135	171	31	error	error	NOUN
ijassa-135	171	32	.	.	PUNCT
ijassa-135	172	1	what	what	PRON
ijassa-135	172	2	an	an	DET
ijassa-135	172	3	actual	actual	ADJ
ijassa-135	172	4	radar	radar	NOUN
ijassa-135	172	5	measures	measure	NOUN
ijassa-135	172	6	includes	include	VERB
ijassa-135	172	7	the	the	DET
ijassa-135	172	8	range	range	NOUN
ijassa-135	172	9	r	r	NOUN
ijassa-135	172	10	,	,	PUNCT
ijassa-135	172	11	azimuth	azimuth	PROPN
ijassa-135	172	12	angle	angle	NOUN
ijassa-135	172	13	a	a	PRON
ijassa-135	172	14	,	,	PUNCT
ijassa-135	172	15	and	and	CCONJ
ijassa-135	172	16	elevation	elevation	NOUN
ijassa-135	172	17	angle	angle	NOUN
ijassa-135	172	18	e.	e.	PROPN
ijassa-135	173	1	these	these	DET
ijassa-135	173	2	measurements	measurement	NOUN
ijassa-135	173	3	satisfy	satisfy	VERB
ijassa-135	173	4	the	the	DET
ijassa-135	173	5	following	follow	VERB
ijassa-135	173	6	transformational	transformational	ADJ
ijassa-135	173	7	connection	connection	NOUN
ijassa-135	173	8	with	with	ADP
ijassa-135	173	9	the	the	DET
ijassa-135	173	10	measured	measure	VERB
ijassa-135	173	11	warhead	warhead	NOUN
ijassa-135	173	12	-	-	PUNCT
ijassa-135	173	13	target	target	NOUN
ijassa-135	173	14	relative	relative	NOUN
ijassa-135	173	15	x-	x-	X
ijassa-135	173	16	,	,	PUNCT
ijassa-135	173	17	y-	y-	X
ijassa-135	173	18	,	,	PUNCT
ijassa-135	173	19	and	and	CCONJ
ijassa-135	173	20	z	z	X
ijassa-135	173	21	-	-	PUNCT
ijassa-135	173	22	positions:	positions:	NOUN
ijassa-135	173	23	x	x	NOUN
ijassa-135	174	1	=	=	PUNCT
ijassa-135	174	2	r	r	NOUN
ijassa-135	174	3	cose	cose	PROPN
ijassa-135	174	4	cosa	cosa	PROPN
ijassa-135	174	5	y	y	PROPN
ijassa-135	174	6	=	=	PUNCT
ijassa-135	174	7	r	r	NOUN
ijassa-135	174	8	sine	sine	NOUN
ijassa-135	174	9	z	z	NOUN
ijassa-135	174	10	=	=	PUNCT
ijassa-135	174	11	r	r	NOUN
ijassa-135	174	12	cose	cose	PROPN
ijassa-135	174	13	sina	sina	PROPN
ijassa-135	174	14	(	(	PUNCT
ijassa-135	174	15	15	15	NUM
ijassa-135	174	16	)	)	PUNCT
ijassa-135	174	17	that	that	PRON
ijassa-135	174	18	is	be	AUX
ijassa-135	174	19	,	,	PUNCT
ijassa-135	174	20	the	the	DET
ijassa-135	174	21	performance	performance	NOUN
ijassa-135	174	22	index	index	NOUN
ijassa-135	174	23	(	(	PUNCT
ijassa-135	174	24	that	that	PRON
ijassa-135	174	25	is	be	AUX
ijassa-135	174	26	to	to	PART
ijassa-135	174	27	be	be	AUX
ijassa-135	174	28	evaluated	evaluate	VERB
ijassa-135	174	29	)	)	PUNCT
ijassa-135	174	30	,	,	PUNCT
ijassa-135	174	31	the	the	DET
ijassa-135	174	32	relative	relative	ADJ
ijassa-135	174	33	positional	positional	ADJ
ijassa-135	174	34	error	error	NOUN
ijassa-135	174	35	of	of	ADP
ijassa-135	174	36	warhead	warhead	NOUN
ijassa-135	174	37	and	and	CCONJ
ijassa-135	174	38	target	target	NOUN
ijassa-135	174	39	,	,	PUNCT
ijassa-135	174	40	is	be	AUX
ijassa-135	174	41	a	a	DET
ijassa-135	174	42	function	function	NOUN
ijassa-135	174	43	of	of	ADP
ijassa-135	174	44	the	the	DET
ijassa-135	174	45	observational	observational	ADJ
ijassa-135	174	46	quantities	quantity	NOUN
ijassa-135	174	47	(	(	PUNCT
ijassa-135	174	48	range	range	NOUN
ijassa-135	174	49	r	r	NOUN
ijassa-135	174	50	,	,	PUNCT
ijassa-135	174	51	azimuth	azimuth	PROPN
ijassa-135	174	52	angle	angle	NOUN
ijassa-135	174	53	a	a	PRON
ijassa-135	174	54	,	,	PUNCT
ijassa-135	174	55	and	and	CCONJ
ijassa-135	174	56	elevation	elevation	NOUN
ijassa-135	174	57	angle	angle	NOUN
ijassa-135	174	58	e	e	NOUN
ijassa-135	174	59	)	)	PUNCT
ijassa-135	174	60	.	.	PUNCT
ijassa-135	175	1	for	for	ADP
ijassa-135	175	2	details	detail	NOUN
ijassa-135	175	3	,	,	PUNCT
ijassa-135	175	4	see	see	VERB
ijassa-135	175	5	fig.4	fig.4	PROPN
ijassa-135	175	6	.	.	PUNCT
ijassa-135	176	1	fig.4	fig.4	VERB
ijassa-135	176	2	the	the	DET
ijassa-135	176	3	relationship	relationship	NOUN
ijassa-135	176	4	between	between	ADP
ijassa-135	176	5	radar	radar	NOUN
ijassa-135	176	6	measurements	measurement	NOUN
ijassa-135	176	7	r	r	NOUN
ijassa-135	176	8	,	,	PUNCT
ijassa-135	176	9	a	a	PRON
ijassa-135	176	10	,	,	PUNCT
ijassa-135	176	11	and	and	CCONJ
ijassa-135	176	12	e	e	NOUN
ijassa-135	176	13	,	,	PUNCT
ijassa-135	176	14	and	and	CCONJ
ijassa-135	176	15	the	the	DET
ijassa-135	176	16	warhead	warhead	NOUN
ijassa-135	176	17	-	-	PUNCT
ijassa-135	176	18	target	target	NOUN
ijassa-135	176	19	relative	relative	NOUN
ijassa-135	176	20	x-	x-	X
ijassa-135	176	21	,	,	PUNCT
ijassa-135	176	22	y-	y-	X
ijassa-135	176	23	,	,	PUNCT
ijassa-135	176	24	and	and	CCONJ
ijassa-135	176	25	z	z	NOUN
ijassa-135	176	26	-	-	PUNCT
ijassa-135	176	27	positions	position	NOUN
ijassa-135	176	28	according	accord	VERB
ijassa-135	176	29	to	to	ADP
ijassa-135	176	30	the	the	DET
ijassa-135	176	31	gaussian	gaussian	ADJ
ijassa-135	176	32	law	law	NOUN
ijassa-135	176	33	of	of	ADP
ijassa-135	176	34	error	error	NOUN
ijassa-135	176	35	propagation	propagation	NOUN
ijassa-135	176	36	,	,	PUNCT
ijassa-135	176	37	combined	combine	VERB
ijassa-135	176	38	with	with	ADP
ijassa-135	176	39	equ	equ	PROPN
ijassa-135	176	40	.	.	PUNCT
ijassa-135	177	1	(	(	PUNCT
ijassa-135	177	2	15	15	NUM
ijassa-135	177	3	)	)	PUNCT
ijassa-135	177	4	,	,	PUNCT
ijassa-135	177	5	we	we	PRON
ijassa-135	177	6	can	can	AUX
ijassa-135	177	7	obtain	obtain	VERB
ijassa-135	177	8	the	the	DET
ijassa-135	177	9	transfer	transfer	NOUN
ijassa-135	177	10	relation	relation	NOUN
ijassa-135	177	11	from	from	ADP
ijassa-135	177	12	the	the	DET
ijassa-135	177	13	x-	x-	PROPN
ijassa-135	177	14	,	,	PUNCT
ijassa-135	177	15	y-	y-	X
ijassa-135	177	16	,	,	PUNCT
ijassa-135	177	17	and	and	CCONJ
ijassa-135	178	1	z	z	NOUN
ijassa-135	178	2	-	-	PUNCT
ijassa-135	178	3	errors	error	NOUN
ijassa-135	178	4	to	to	ADP
ijassa-135	178	5	the	the	DET
ijassa-135	178	6	r-	r-	NOUN
ijassa-135	178	7	,	,	PUNCT
ijassa-135	178	8	a-	a-	X
ijassa-135	178	9	,	,	PUNCT
ijassa-135	178	10	and	and	CCONJ
ijassa-135	178	11	e	e	NOUN
ijassa-135	178	12	-	-	NOUN
ijassa-135	178	13	errors	error	NOUN
ijassa-135	178	14	below:	below:	NOUN
ijassa-135	178	15	△	△	X
ijassa-135	178	16	x	x	X
ijassa-135	178	17	△	△	PROPN
ijassa-135	178	18	y	y	PROPN
ijassa-135	178	19	△	△	PROPN
ijassa-135	178	20	z	z	NOUN
ijassa-135	178	21			PROPN
ijassa-135	178	22	=	=	SYM
ijassa-135	178	23			PROPN
ijassa-135	178	24	∂x	∂x	PROPN
ijassa-135	178	25	∂r	∂r	PROPN
ijassa-135	178	26	∂x	∂x	PROPN
ijassa-135	179	1	∂a	∂a	CCONJ
ijassa-135	179	2	∂x	∂x	PROPN
ijassa-135	179	3	∂e	∂e	PROPN
ijassa-135	179	4	∂y	∂y	NOUN
ijassa-135	180	1	∂r	∂r	PROPN
ijassa-135	180	2	∂y	∂y	NOUN
ijassa-135	180	3	∂a	∂a	NOUN
ijassa-135	180	4	∂y	∂y	PROPN
ijassa-135	180	5	∂e	∂e	PROPN
ijassa-135	180	6	∂z	∂z	PROPN
ijassa-135	181	1	∂r	∂r	INTJ
ijassa-135	181	2	∂z	∂z	PROPN
ijassa-135	182	1	∂a	∂a	PROPN
ijassa-135	182	2	∂z	∂z	PROPN
ijassa-135	182	3	∂e	∂e	PROPN
ijassa-135	182	4			PUNCT
ijassa-135	183	1	△	△	PUNCT
ijassa-135	183	2	r	r	NOUN
ijassa-135	183	3	△	△	PROPN
ijassa-135	183	4	a	a	DET
ijassa-135	183	5	△	△	X
ijassa-135	183	6	e	e	NOUN
ijassa-135	183	7			PROPN
ijassa-135	183	8	=	=	SYM
ijassa-135	183	9			PROPN
ijassa-135	183	10	cose	cose	PROPN
ijassa-135	183	11	cosa	cosa	PROPN
ijassa-135	183	12	−r	−r	PROPN
ijassa-135	183	13	cose	cose	PROPN
ijassa-135	183	14	sina	sina	PROPN
ijassa-135	183	15	−r	−r	PROPN
ijassa-135	183	16	sine	sine	PROPN
ijassa-135	183	17	cosa	cosa	PROPN
ijassa-135	183	18	sine	sine	PROPN
ijassa-135	183	19	0	0	NUM
ijassa-135	184	1	r	r	NOUN
ijassa-135	184	2	cose	cose	PROPN
ijassa-135	184	3	cose	cose	PROPN
ijassa-135	184	4	sina	sina	PROPN
ijassa-135	184	5	r	r	PROPN
ijassa-135	184	6	cose	cose	PROPN
ijassa-135	184	7	cosa	cosa	PROPN
ijassa-135	184	8	−r	−r	PROPN
ijassa-135	184	9	sine	sine	PROPN
ijassa-135	184	10	sina	sina	PROPN
ijassa-135	184	11			PUNCT
ijassa-135	184	12	△	△	X
ijassa-135	184	13	r	r	NOUN
ijassa-135	184	14	△	△	PROPN
ijassa-135	184	15	a	a	DET
ijassa-135	184	16	△	△	X
ijassa-135	184	17	e	e	X
ijassa-135	184	18			PROPN
ijassa-135	184	19	(	(	PUNCT
ijassa-135	184	20	16	16	NUM
ijassa-135	184	21	)	)	PUNCT
ijassa-135	184	22	where	where	SCONJ
ijassa-135	184	23	△	△	NOUN
ijassa-135	184	24	x	x	NOUN
ijassa-135	184	25	,	,	PUNCT
ijassa-135	184	26	△	△	PROPN
ijassa-135	184	27	y	y	NOUN
ijassa-135	184	28	,	,	PUNCT
ijassa-135	184	29	and	and	CCONJ
ijassa-135	184	30	△	△	NOUN
ijassa-135	184	31	z	z	NOUN
ijassa-135	184	32	stand	stand	VERB
ijassa-135	184	33	for	for	ADP
ijassa-135	184	34	the	the	DET
ijassa-135	184	35	warhead	warhead	NOUN
ijassa-135	184	36	-	-	PUNCT
ijassa-135	184	37	target	target	NOUN
ijassa-135	184	38	relative	relative	ADJ
ijassa-135	184	39	positional	positional	ADJ
ijassa-135	184	40	errors	error	NOUN
ijassa-135	184	41	of	of	ADP
ijassa-135	184	42	the	the	DET
ijassa-135	184	43	standard	standard	ADJ
ijassa-135	184	44	testing	testing	NOUN
ijassa-135	184	45	state	state	NOUN
ijassa-135	184	46	,	,	PUNCT
ijassa-135	184	47	and	and	CCONJ
ijassa-135	184	48	△	△	PUNCT
ijassa-135	184	49	r	r	NOUN
ijassa-135	184	50	,	,	PUNCT
ijassa-135	184	51	△	△	X
ijassa-135	184	52	a	a	PRON
ijassa-135	184	53	,	,	PUNCT
ijassa-135	184	54	and	and	CCONJ
ijassa-135	184	55	△	△	NOUN
ijassa-135	184	56	e	e	NOUN
ijassa-135	184	57	the	the	DET
ijassa-135	184	58	errors	error	NOUN
ijassa-135	184	59	in	in	ADP
ijassa-135	184	60	the	the	DET
ijassa-135	184	61	radar	radar	NOUN
ijassa-135	184	62	measurements	measurement	NOUN
ijassa-135	184	63	r	r	NOUN
ijassa-135	184	64	,	,	PUNCT
ijassa-135	184	65	a	a	PRON
ijassa-135	184	66	,	,	PUNCT
ijassa-135	184	67	and	and	CCONJ
ijassa-135	184	68	e	e	X
ijassa-135	184	69	of	of	ADP
ijassa-135	184	70	the	the	DET
ijassa-135	184	71	whole	whole	ADJ
ijassa-135	184	72	testing	testing	NOUN
ijassa-135	184	73	state	state	NOUN
ijassa-135	184	74	.	.	PUNCT
ijassa-135	185	1	245	245	NUM
ijassa-135	185	2	advances	advance	NOUN
ijassa-135	185	3	in	in	ADP
ijassa-135	185	4	systems	system	NOUN
ijassa-135	185	5	science	science	NOUN
ijassa-135	185	6	and	and	CCONJ
ijassa-135	185	7	applications	application	NOUN
ijassa-135	185	8	(	(	PUNCT
ijassa-135	185	9	2013	2013	NUM
ijassa-135	185	10	)	)	PUNCT
ijassa-135	185	11	vol.13	vol.13	NOUN
ijassa-135	185	12	no.3	no.3	VERB
ijassa-135	185	13	firstly	firstly	ADV
ijassa-135	185	14	,	,	PUNCT
ijassa-135	185	15	we	we	PRON
ijassa-135	185	16	use	use	VERB
ijassa-135	185	17	the	the	DET
ijassa-135	185	18	observational	observational	ADJ
ijassa-135	185	19	data	datum	NOUN
ijassa-135	185	20	of	of	ADP
ijassa-135	185	21	actual	actual	ADJ
ijassa-135	185	22	tests	test	NOUN
ijassa-135	185	23	to	to	PART
ijassa-135	185	24	obtain	obtain	VERB
ijassa-135	185	25	the	the	DET
ijassa-135	185	26	errors	error	NOUN
ijassa-135	185	27	△	△	NOUN
ijassa-135	185	28	̃r	̃r	NOUN
ijassa-135	185	29	,	,	PUNCT
ijassa-135	185	30	△	△	NOUN
ijassa-135	185	31	̃a	̃a	PROPN
ijassa-135	185	32	,	,	PUNCT
ijassa-135	185	33	and	and	CCONJ
ijassa-135	185	34	△	△	X
ijassa-135	185	35	̃e	̃e	NOUN
ijassa-135	185	36	of	of	ADP
ijassa-135	185	37	radar	radar	NOUN
ijassa-135	185	38	measurements	measurement	NOUN
ijassa-135	185	39	.	.	PUNCT
ijassa-135	186	1	secondly	secondly	ADV
ijassa-135	186	2	,	,	PUNCT
ijassa-135	186	3	we	we	PRON
ijassa-135	186	4	analyze	analyze	VERB
ijassa-135	186	5	the	the	DET
ijassa-135	186	6	iterative	iterative	NOUN
ijassa-135	186	7	process	process	NOUN
ijassa-135	186	8	of	of	ADP
ijassa-135	186	9	the	the	DET
ijassa-135	186	10	errors	error	NOUN
ijassa-135	186	11	in	in	ADP
ijassa-135	186	12	the	the	DET
ijassa-135	186	13	measured	measured	ADJ
ijassa-135	186	14	range	range	NOUN
ijassa-135	186	15	and	and	CCONJ
ijassa-135	186	16	angles	angle	NOUN
ijassa-135	186	17	.	.	PUNCT
ijassa-135	187	1	in	in	ADP
ijassa-135	187	2	the	the	DET
ijassa-135	187	3	following	following	NOUN
ijassa-135	187	4	,	,	PUNCT
ijassa-135	187	5	we	we	PRON
ijassa-135	187	6	use	use	VERB
ijassa-135	187	7	a	a	DET
ijassa-135	187	8	monopulse	monopulse	ADJ
ijassa-135	187	9	radar	radar	NOUN
ijassa-135	187	10	system	system	NOUN
ijassa-135	187	11	as	as	ADP
ijassa-135	187	12	our	our	PRON
ijassa-135	187	13	example	example	NOUN
ijassa-135	187	14	to	to	PART
ijassa-135	187	15	specifically	specifically	ADV
ijassa-135	187	16	analyze	analyze	VERB
ijassa-135	187	17	the	the	DET
ijassa-135	187	18	influencing	influence	VERB
ijassa-135	187	19	factors	factor	NOUN
ijassa-135	187	20	on	on	ADP
ijassa-135	187	21	the	the	DET
ijassa-135	187	22	errors	error	NOUN
ijassa-135	187	23	in	in	ADP
ijassa-135	187	24	radar	radar	NOUN
ijassa-135	187	25	measured	measure	VERB
ijassa-135	187	26	range	range	NOUN
ijassa-135	187	27	and	and	CCONJ
ijassa-135	187	28	angles	angle	NOUN
ijassa-135	187	29	.	.	PUNCT
ijassa-135	188	1	based	base	VERB
ijassa-135	188	2	on	on	ADP
ijassa-135	188	3	the	the	DET
ijassa-135	188	4	analysis	analysis	NOUN
ijassa-135	188	5	on	on	ADP
ijassa-135	188	6	the	the	DET
ijassa-135	188	7	sources	source	NOUN
ijassa-135	188	8	of	of	ADP
ijassa-135	188	9	errors	error	NOUN
ijassa-135	188	10	in	in	ADP
ijassa-135	188	11	radar	radar	NOUN
ijassa-135	188	12	measurements	measurement	NOUN
ijassa-135	188	13	r	r	NOUN
ijassa-135	188	14	,	,	PUNCT
ijassa-135	188	15	a	a	PRON
ijassa-135	188	16	,	,	PUNCT
ijassa-135	188	17	and	and	CCONJ
ijassa-135	188	18	e	e	X
ijassa-135	188	19	[	[	X
ijassa-135	188	20	6	6	NUM
ijassa-135	188	21	]	]	PUNCT
ijassa-135	188	22	,	,	PUNCT
ijassa-135	188	23	and	and	CCONJ
ijassa-135	188	24	the	the	DET
ijassa-135	188	25	law	law	NOUN
ijassa-135	188	26	of	of	ADP
ijassa-135	188	27	error	error	NOUN
ijassa-135	188	28	synthesis	synthesis	NOUN
ijassa-135	188	29	,	,	PUNCT
ijassa-135	188	30	we	we	PRON
ijassa-135	188	31	can	can	AUX
ijassa-135	188	32	obtain	obtain	VERB
ijassa-135	188	33	the	the	DET
ijassa-135	188	34	main	main	ADJ
ijassa-135	188	35	errors	error	NOUN
ijassa-135	188	36	in	in	ADP
ijassa-135	188	37	radar	radar	NOUN
ijassa-135	188	38	measured	measure	VERB
ijassa-135	188	39	ranges	range	NOUN
ijassa-135	188	40	and	and	CCONJ
ijassa-135	188	41	angles	angle	NOUN
ijassa-135	188	42	as	as	SCONJ
ijassa-135	188	43	follows	follow	VERB
ijassa-135	188	44	:	:	PUNCT
ijassa-135	188	45	u2	u2	NOUN
ijassa-135	188	46	angle	angle	NOUN
ijassa-135	188	47	=	=	SYM
ijassa-135	188	48	△	△	PROPN
ijassa-135	188	49	2	2	NUM
ijassa-135	188	50	rader	rader	NOUN
ijassa-135	188	51	+	+	PROPN
ijassa-135	188	52	△	△	X
ijassa-135	188	53	2	2	NUM
ijassa-135	188	54	target	target	NOUN
ijassa-135	188	55	+	+	NOUN
ijassa-135	188	56	△	△	X
ijassa-135	188	57	2	2	NUM
ijassa-135	188	58	enviroment	enviroment	NOUN
ijassa-135	188	59	+	+	X
ijassa-135	188	60	...	...	PUNCT
ijassa-135	189	1	=	=	SYM
ijassa-135	189	2	△	△	X
ijassa-135	189	3	2	2	NUM
ijassa-135	189	4	thermanoise	thermanoise	NOUN
ijassa-135	189	5	+	+	NOUN
ijassa-135	189	6	△	△	X
ijassa-135	189	7	2	2	NUM
ijassa-135	189	8	phaseunbalance	phaseunbalance	NOUN
ijassa-135	189	9	+	+	NOUN
ijassa-135	189	10	△	△	X
ijassa-135	189	11	2	2	NUM
ijassa-135	189	12	angularglint+	angularglint+	X
ijassa-135	189	13	△	△	PROPN
ijassa-135	189	14	2	2	NUM
ijassa-135	189	15	dynamiclag	dynamiclag	NOUN
ijassa-135	189	16	+	+	NOUN
ijassa-135	189	17	△	△	X
ijassa-135	189	18	2	2	NUM
ijassa-135	189	19	clutterinterference	clutterinterference	NOUN
ijassa-135	189	20	+	+	X
ijassa-135	189	21	...	...	PUNCT
ijassa-135	189	22	u2	u2	NOUN
ijassa-135	189	23	distance	distance	NOUN
ijassa-135	189	24	=	=	SYM
ijassa-135	189	25	△	△	PROPN
ijassa-135	189	26	2	2	NUM
ijassa-135	189	27	rader	rader	NOUN
ijassa-135	189	28	+	+	PROPN
ijassa-135	189	29	△	△	X
ijassa-135	189	30	2	2	NUM
ijassa-135	189	31	target	target	NOUN
ijassa-135	189	32	+	+	NOUN
ijassa-135	189	33	△	△	X
ijassa-135	189	34	2	2	NUM
ijassa-135	189	35	enviroment	enviroment	NOUN
ijassa-135	189	36	+	+	X
ijassa-135	189	37	...	...	PUNCT
ijassa-135	190	1	=	=	SYM
ijassa-135	190	2	△	△	X
ijassa-135	190	3	2	2	NUM
ijassa-135	190	4	thermanoise	thermanoise	NOUN
ijassa-135	190	5	+	+	NOUN
ijassa-135	190	6	△	△	X
ijassa-135	190	7	2	2	NUM
ijassa-135	190	8	angularglint	angularglint	NOUN
ijassa-135	190	9	+	+	NOUN
ijassa-135	190	10	△	△	X
ijassa-135	190	11	2	2	NUM
ijassa-135	190	12	dynamiclag+	dynamiclag+	ADP
ijassa-135	190	13	△	△	NOUN
ijassa-135	190	14	2	2	NUM
ijassa-135	190	15	clutterinterference	clutterinterference	NOUN
ijassa-135	190	16	+	+	X
ijassa-135	190	17	...	...	PUNCT
ijassa-135	190	18	if	if	SCONJ
ijassa-135	190	19	we	we	PRON
ijassa-135	190	20	look	look	VERB
ijassa-135	190	21	at	at	ADP
ijassa-135	190	22	radar	radar	NOUN
ijassa-135	190	23	measured	measure	VERB
ijassa-135	190	24	ranges	range	NOUN
ijassa-135	190	25	,	,	PUNCT
ijassa-135	190	26	we	we	PRON
ijassa-135	190	27	see	see	VERB
ijassa-135	190	28	that	that	SCONJ
ijassa-135	190	29	the	the	DET
ijassa-135	190	30	systematic	systematic	ADJ
ijassa-135	190	31	error	error	NOUN
ijassa-135	190	32	is	be	AUX
ijassa-135	190	33	mainly	mainly	ADV
ijassa-135	190	34	the	the	DET
ijassa-135	190	35	dynamic	dynamic	ADJ
ijassa-135	190	36	lag	lag	NOUN
ijassa-135	190	37	error	error	NOUN
ijassa-135	190	38	.	.	PUNCT
ijassa-135	191	1	the	the	DET
ijassa-135	191	2	time	time	NOUN
ijassa-135	191	3	-	-	PUNCT
ijassa-135	191	4	dependent	dependent	ADJ
ijassa-135	191	5	random	random	ADJ
ijassa-135	191	6	error	error	NOUN
ijassa-135	191	7	mainly	mainly	ADV
ijassa-135	191	8	includes	include	VERB
ijassa-135	191	9	the	the	DET
ijassa-135	191	10	error	error	NOUN
ijassa-135	191	11	of	of	ADP
ijassa-135	191	12	clutter	clutter	NOUN
ijassa-135	191	13	interference	interference	NOUN
ijassa-135	191	14	,	,	PUNCT
ijassa-135	191	15	thermal	thermal	ADJ
ijassa-135	191	16	noise	noise	NOUN
ijassa-135	191	17	,	,	PUNCT
ijassa-135	191	18	and	and	CCONJ
ijassa-135	191	19	distance	distance	NOUN
ijassa-135	191	20	glint	glint	NOUN
ijassa-135	191	21	.	.	PUNCT
ijassa-135	192	1	now	now	ADV
ijassa-135	192	2	,	,	PUNCT
ijassa-135	192	3	let	let	VERB
ijassa-135	192	4	us	we	PRON
ijassa-135	192	5	consider	consider	VERB
ijassa-135	192	6	the	the	DET
ijassa-135	192	7	methods	method	NOUN
ijassa-135	192	8	of	of	ADP
ijassa-135	192	9	computation	computation	NOUN
ijassa-135	192	10	for	for	ADP
ijassa-135	192	11	the	the	DET
ijassa-135	192	12	impact	impact	NOUN
ijassa-135	192	13	errors	error	NOUN
ijassa-135	192	14	of	of	ADP
ijassa-135	192	15	active	active	ADJ
ijassa-135	192	16	homing	home	VERB
ijassa-135	192	17	radar	radar	NOUN
ijassa-135	192	18	systems	system	NOUN
ijassa-135	192	19	,	,	PUNCT
ijassa-135	192	20	as	as	SCONJ
ijassa-135	192	21	mentioned	mention	VERB
ijassa-135	192	22	earlier	early	ADV
ijassa-135	192	23	,	,	PUNCT
ijassa-135	192	24	under	under	ADP
ijassa-135	192	25	two	two	NUM
ijassa-135	192	26	different	different	ADJ
ijassa-135	192	27	testing	testing	NOUN
ijassa-135	192	28	states	state	NOUN
ijassa-135	192	29	:	:	PUNCT
ijassa-135	192	30	one	one	NUM
ijassa-135	192	31	is	be	AUX
ijassa-135	192	32	to	to	PART
ijassa-135	192	33	fuse	fuse	VERB
ijassa-135	192	34	different	different	ADJ
ijassa-135	192	35	observational	observational	ADJ
ijassa-135	192	36	information	information	NOUN
ijassa-135	192	37	,	,	PUNCT
ijassa-135	192	38	including	include	VERB
ijassa-135	192	39	the	the	DET
ijassa-135	192	40	direct	direct	ADJ
ijassa-135	192	41	observational	observational	ADJ
ijassa-135	192	42	index	index	NOUN
ijassa-135	192	43	data	datum	NOUN
ijassa-135	192	44	and	and	CCONJ
ijassa-135	192	45	indirect	indirect	ADJ
ijassa-135	192	46	observational	observational	ADJ
ijassa-135	192	47	data(the	data(the	NOUN
ijassa-135	192	48	concrete	concrete	ADJ
ijassa-135	192	49	fusion	fusion	NOUN
ijassa-135	192	50	model	model	NOUN
ijassa-135	192	51	refers	refer	VERB
ijassa-135	192	52	to	to	PART
ijassa-135	192	53	subsection	subsection	VERB
ijassa-135	192	54	2.2	2.2	NUM
ijassa-135	192	55	and	and	CCONJ
ijassa-135	192	56	2.3	2.3	NUM
ijassa-135	192	57	)	)	PUNCT
ijassa-135	192	58	,	,	PUNCT
ijassa-135	192	59	and	and	CCONJ
ijassa-135	192	60	the	the	DET
ijassa-135	192	61	other	other	ADJ
ijassa-135	192	62	the	the	DET
ijassa-135	192	63	point	point	NOUN
ijassa-135	192	64	estimate	estimate	NOUN
ijassa-135	192	65	method	method	NOUN
ijassa-135	192	66	of	of	ADP
ijassa-135	192	67	impact	impact	NOUN
ijassa-135	192	68	errors	error	NOUN
ijassa-135	192	69	[	[	X
ijassa-135	192	70	7	7	NUM
ijassa-135	192	71	]	]	PUNCT
ijassa-135	192	72	.	.	PUNCT
ijassa-135	193	1	our	our	PRON
ijassa-135	193	2	simulated	simulated	ADJ
ijassa-135	193	3	radar	radar	NOUN
ijassa-135	193	4	measurements	measurement	NOUN
ijassa-135	193	5	are	be	AUX
ijassa-135	193	6	the	the	DET
ijassa-135	193	7	range	range	NOUN
ijassa-135	193	8	r	r	NOUN
ijassa-135	193	9	,	,	PUNCT
ijassa-135	193	10	azimuth	azimuth	PROPN
ijassa-135	193	11	angle	angle	NOUN
ijassa-135	193	12	a	a	PRON
ijassa-135	193	13	,	,	PUNCT
ijassa-135	193	14	and	and	CCONJ
ijassa-135	193	15	elevation	elevation	NOUN
ijassa-135	193	16	angle	angle	PROPN
ijassa-135	193	17	e.	e.	PROPN
ijassa-135	193	18	other	other	ADJ
ijassa-135	193	19	than	than	ADP
ijassa-135	193	20	analyzing	analyze	VERB
ijassa-135	193	21	the	the	DET
ijassa-135	193	22	single	single	ADJ
ijassa-135	193	23	point	point	NOUN
ijassa-135	193	24	measurements	measurement	NOUN
ijassa-135	193	25	at	at	ADP
ijassa-135	193	26	the	the	DET
ijassa-135	193	27	impact	impact	NOUN
ijassa-135	193	28	moments	moment	NOUN
ijassa-135	194	1	[	[	X
ijassa-135	194	2	7	7	NUM
ijassa-135	194	3	]	]	PUNCT
ijassa-135	194	4	,	,	PUNCT
ijassa-135	194	5	we	we	PRON
ijassa-135	194	6	also	also	ADV
ijassa-135	194	7	provide	provide	VERB
ijassa-135	194	8	a	a	DET
ijassa-135	194	9	method	method	NOUN
ijassa-135	194	10	on	on	ADP
ijassa-135	194	11	how	how	SCONJ
ijassa-135	194	12	to	to	PART
ijassa-135	194	13	combine	combine	VERB
ijassa-135	194	14	observed	observed	ADJ
ijassa-135	194	15	process	process	NOUN
ijassa-135	194	16	quantities	quantity	NOUN
ijassa-135	194	17	.	.	PUNCT
ijassa-135	195	1	we	we	PRON
ijassa-135	195	2	respectively	respectively	ADV
ijassa-135	195	3	model	model	VERB
ijassa-135	195	4	the	the	DET
ijassa-135	195	5	errors	error	NOUN
ijassa-135	195	6	in	in	ADP
ijassa-135	195	7	radar	radar	NOUN
ijassa-135	195	8	measured	measure	VERB
ijassa-135	195	9	range	range	NOUN
ijassa-135	195	10	and	and	CCONJ
ijassa-135	195	11	angle	angle	NOUN
ijassa-135	195	12	signals	signal	NOUN
ijassa-135	195	13	,	,	PUNCT
ijassa-135	195	14	and	and	CCONJ
ijassa-135	195	15	the	the	DET
ijassa-135	195	16	speed	speed	NOUN
ijassa-135	195	17	and	and	CCONJ
ijassa-135	195	18	acceleration	acceleration	NOUN
ijassa-135	195	19	of	of	ADP
ijassa-135	195	20	the	the	DET
ijassa-135	195	21	actual	actual	ADJ
ijassa-135	195	22	measured	measure	VERB
ijassa-135	195	23	ranges	range	NOUN
ijassa-135	195	24	and	and	CCONJ
ijassa-135	195	25	angles	angle	NOUN
ijassa-135	195	26	for	for	ADP
ijassa-135	195	27	the	the	DET
ijassa-135	195	28	two	two	NUM
ijassa-135	195	29	testing	testing	NOUN
ijassa-135	195	30	states	state	NOUN
ijassa-135	195	31	:	:	PUNCT
ijassa-135	195	32	the	the	DET
ijassa-135	195	33	simulated	simulate	VERB
ijassa-135	195	34	substitute	substitute	NOUN
ijassa-135	195	35	tests	test	NOUN
ijassa-135	195	36	and	and	CCONJ
ijassa-135	195	37	the	the	DET
ijassa-135	195	38	whole	whole	ADJ
ijassa-135	195	39	process	process	NOUN
ijassa-135	195	40	tests	test	NOUN
ijassa-135	195	41	.	.	PUNCT
ijassa-135	196	1	assume	assume	VERB
ijassa-135	196	2	that	that	SCONJ
ijassa-135	196	3	the	the	DET
ijassa-135	196	4	random	random	ADJ
ijassa-135	196	5	error	error	NOUN
ijassa-135	196	6	term	term	NOUN
ijassa-135	196	7	includes	include	VERB
ijassa-135	196	8	the	the	DET
ijassa-135	196	9	independent	independent	ADJ
ijassa-135	196	10	errors	error	NOUN
ijassa-135	196	11	of	of	ADP
ijassa-135	196	12	clutter	clutter	NOUN
ijassa-135	196	13	interference	interference	NOUN
ijassa-135	196	14	,	,	PUNCT
ijassa-135	196	15	thermal	thermal	ADJ
ijassa-135	196	16	noise	noise	NOUN
ijassa-135	196	17	,	,	PUNCT
ijassa-135	196	18	and	and	CCONJ
ijassa-135	196	19	distance	distance	NOUN
ijassa-135	196	20	glint	glint	NOUN
ijassa-135	196	21	.	.	PUNCT
ijassa-135	197	1	for	for	ADP
ijassa-135	197	2	the	the	DET
ijassa-135	197	3	systematic	systematic	ADJ
ijassa-135	197	4	deviation	deviation	NOUN
ijassa-135	197	5	,	,	PUNCT
ijassa-135	197	6	we	we	PRON
ijassa-135	197	7	mainly	mainly	ADV
ijassa-135	197	8	consider	consider	VERB
ijassa-135	197	9	the	the	DET
ijassa-135	197	10	error	error	NOUN
ijassa-135	197	11	caused	cause	VERB
ijassa-135	197	12	by	by	ADP
ijassa-135	197	13	dynamic	dynamic	ADJ
ijassa-135	197	14	lag	lag	NOUN
ijassa-135	197	15	.	.	PUNCT
ijassa-135	198	1	by	by	ADP
ijassa-135	198	2	comparing	compare	VERB
ijassa-135	198	3	the	the	DET
ijassa-135	198	4	point	point	NOUN
ijassa-135	198	5	estimate	estimate	NOUN
ijassa-135	198	6	method	method	NOUN
ijassa-135	198	7	of	of	ADP
ijassa-135	198	8	impact	impact	NOUN
ijassa-135	198	9	points	point	NOUN
ijassa-135	198	10	and	and	CCONJ
ijassa-135	198	11	that	that	PRON
ijassa-135	198	12	of	of	ADP
ijassa-135	198	13	combining	combine	VERB
ijassa-135	198	14	process	process	NOUN
ijassa-135	198	15	information	information	NOUN
ijassa-135	198	16	that	that	PRON
ijassa-135	198	17	is	be	AUX
ijassa-135	198	18	used	use	VERB
ijassa-135	198	19	to	to	PART
ijassa-135	198	20	calculate	calculate	VERB
ijassa-135	198	21	the	the	DET
ijassa-135	198	22	impact	impact	NOUN
ijassa-135	198	23	point	point	NOUN
ijassa-135	198	24	error	error	NOUN
ijassa-135	198	25	caused	cause	VERB
ijassa-135	198	26	by	by	ADP
ijassa-135	198	27	radar	radar	NOUN
ijassa-135	198	28	errors	error	NOUN
ijassa-135	198	29	,	,	PUNCT
ijassa-135	198	30	the	the	DET
ijassa-135	198	31	outcomes	outcome	NOUN
ijassa-135	198	32	are	be	AUX
ijassa-135	198	33	listed	list	VERB
ijassa-135	198	34	in	in	ADP
ijassa-135	198	35	table	table	NOUN
ijassa-135	198	36	2	2	NUM
ijassa-135	198	37	.	.	PUNCT
ijassa-135	199	1	the	the	DET
ijassa-135	199	2	point	point	NOUN
ijassa-135	199	3	estimate	estimate	NOUN
ijassa-135	199	4	method	method	NOUN
ijassa-135	199	5	does	do	AUX
ijassa-135	199	6	not	not	PART
ijassa-135	199	7	employ	employ	VERB
ijassa-135	199	8	the	the	DET
ijassa-135	199	9	process	process	NOUN
ijassa-135	199	10	data	datum	NOUN
ijassa-135	199	11	of	of	ADP
ijassa-135	199	12	the	the	DET
ijassa-135	199	13	active	active	ADJ
ijassa-135	199	14	homing	homing	NOUN
ijassa-135	199	15	radar	radar	NOUN
ijassa-135	199	16	.	.	PUNCT
ijassa-135	200	1	instead	instead	ADV
ijassa-135	200	2	,	,	PUNCT
ijassa-135	200	3	it	it	PRON
ijassa-135	200	4	only	only	ADV
ijassa-135	200	5	applies	apply	VERB
ijassa-135	200	6	the	the	DET
ijassa-135	200	7	observational	observational	ADJ
ijassa-135	200	8	data	datum	NOUN
ijassa-135	200	9	of	of	ADP
ijassa-135	200	10	the	the	DET
ijassa-135	200	11	last	last	ADJ
ijassa-135	200	12	moments	moment	NOUN
ijassa-135	200	13	to	to	PART
ijassa-135	200	14	calculate	calculate	VERB
ijassa-135	200	15	the	the	DET
ijassa-135	200	16	impact	impact	NOUN
ijassa-135	200	17	point	point	NOUN
ijassa-135	200	18	deviation	deviation	NOUN
ijassa-135	200	19	caused	cause	VERB
ijassa-135	200	20	by	by	ADP
ijassa-135	200	21	radar	radar	NOUN
ijassa-135	200	22	errors	error	NOUN
ijassa-135	200	23	.	.	PUNCT
ijassa-135	201	1	when	when	SCONJ
ijassa-135	201	2	the	the	DET
ijassa-135	201	3	sample	sample	NOUN
ijassa-135	201	4	size	size	NOUN
ijassa-135	201	5	is	be	AUX
ijassa-135	201	6	small	small	ADJ
ijassa-135	201	7	,	,	PUNCT
ijassa-135	201	8	the	the	DET
ijassa-135	201	9	outcome	outcome	NOUN
ijassa-135	201	10	xiaojun	xiaojun	PROPN
ijassa-135	201	11	duan	duan	PROPN
ijassa-135	201	12	,	,	PUNCT
ijassa-135	201	13	yi	yi	PROPN
ijassa-135	201	14	lin	lin	PROPN
ijassa-135	201	15	:	:	PUNCT
ijassa-135	201	16	ways	way	NOUN
ijassa-135	201	17	of	of	ADP
ijassa-135	201	18	fusing	fuse	VERB
ijassa-135	201	19	different	different	ADJ
ijassa-135	201	20	types	type	NOUN
ijassa-135	201	21	of	of	ADP
ijassa-135	201	22	information	information	NOUN
ijassa-135	201	23	and	and	CCONJ
ijassa-135	201	24	how	how	SCONJ
ijassa-135	201	25	systemic	systemic	ADJ
ijassa-135	201	26	...	...	PUNCT
ijassa-135	201	27	246	246	NUM
ijassa-135	201	28	table	table	NOUN
ijassa-135	201	29	2	2	NUM
ijassa-135	201	30	the	the	DET
ijassa-135	201	31	impact	impact	NOUN
ijassa-135	201	32	error	error	NOUN
ijassa-135	201	33	estimate	estimate	NOUN
ijassa-135	201	34	comparisons	comparison	NOUN
ijassa-135	201	35	between	between	ADP
ijassa-135	201	36	the	the	DET
ijassa-135	201	37	two	two	NUM
ijassa-135	201	38	methods	method	NOUN
ijassa-135	201	39	considered	consider	VERB
ijassa-135	201	40	(	(	PUNCT
ijassa-135	201	41	significance	significance	NOUN
ijassa-135	201	42	level	level	NOUN
ijassa-135	201	43	α=	α=	NUM
ijassa-135	201	44	0.01	0.01	NUM
ijassa-135	201	45	)	)	PUNCT
ijassa-135	201	46	unit	unit	NOUN
ijassa-135	201	47	(	(	PUNCT
ijassa-135	201	48	meter	meter	NOUN
ijassa-135	201	49	)	)	PUNCT
ijassa-135	201	50	cross	cross	NOUN
ijassa-135	201	51	impact	impact	PROPN
ijassa-135	201	52	cross	cross	PROPN
ijassa-135	201	53	impact	impact	PROPN
ijassa-135	201	54	longitudinal	longitudinal	ADJ
ijassa-135	201	55	longitudinal	longitudinal	ADJ
ijassa-135	201	56	error	error	NOUN
ijassa-135	201	57	point	point	NOUN
ijassa-135	201	58	error	error	NOUN
ijassa-135	201	59	confidence	confidence	NOUN
ijassa-135	201	60	impact	impact	NOUN
ijassa-135	201	61	error	error	NOUN
ijassa-135	201	62	impact	impact	NOUN
ijassa-135	201	63	error	error	NOUN
ijassa-135	201	64	estimation	estimation	NOUN
ijassa-135	201	65	interval	interval	NOUN
ijassa-135	201	66	point	point	NOUN
ijassa-135	201	67	estimation	estimation	NOUN
ijassa-135	201	68	confidence	confidence	NOUN
ijassa-135	201	69	interval	interval	NOUN
ijassa-135	201	70	real	real	ADJ
ijassa-135	201	71	impact	impact	NOUN
ijassa-135	201	72	error	error	NOUN
ijassa-135	201	73	-12.93	-12.93	PROPN
ijassa-135	202	1	[	[	X
ijassa-135	202	2	-15.72,-10.13	-15.72,-10.13	X
ijassa-135	202	3	]	]	X
ijassa-135	202	4	18.78	18.78	NUM
ijassa-135	202	5	[	[	X
ijassa-135	202	6	18.09,19.47]for	18.09,19.47]for	ADP
ijassa-135	202	7	standard	standard	ADJ
ijassa-135	202	8	overall	overall	ADJ
ijassa-135	202	9	test	test	NOUN
ijassa-135	202	10	substitute	substitute	NOUN
ijassa-135	202	11	test	test	NOUN
ijassa-135	202	12	-13.96	-13.96	PUNCT
ijassa-135	203	1	[	[	X
ijassa-135	203	2	-49.43,21.51	-49.43,21.51	X
ijassa-135	203	3	]	]	X
ijassa-135	203	4	20.23	20.23	NUM
ijassa-135	203	5	[	[	X
ijassa-135	203	6	-29.56,70.02]point	-29.56,70.02]point	INTJ
ijassa-135	203	7	conversion	conversion	NOUN
ijassa-135	203	8	(	(	PUNCT
ijassa-135	203	9	traditional	traditional	ADJ
ijassa-135	203	10	method	method	NOUN
ijassa-135	203	11	)	)	PUNCT
ijassa-135	203	12	substitute	substitute	NOUN
ijassa-135	203	13	test	test	NOUN
ijassa-135	203	14	-12.56	-12.56	PUNCT
ijassa-135	204	1	[	[	X
ijassa-135	204	2	-15.33,-9.80	-15.33,-9.80	X
ijassa-135	204	3	]	]	X
ijassa-135	204	4	18.33	18.33	NUM
ijassa-135	204	5	[	[	X
ijassa-135	204	6	17.61,19.05	17.61,19.05	X
ijassa-135	204	7	]	]	PUNCT
ijassa-135	204	8	conversion	conversion	NOUN
ijassa-135	204	9	method	method	NOUN
ijassa-135	204	10	fusing	fuse	VERB
ijassa-135	204	11	with	with	ADP
ijassa-135	204	12	indirect	indirect	ADJ
ijassa-135	204	13	observational	observational	ADJ
ijassa-135	204	14	information	information	NOUN
ijassa-135	204	15	of	of	ADP
ijassa-135	204	16	this	this	DET
ijassa-135	204	17	method	method	NOUN
ijassa-135	204	18	is	be	AUX
ijassa-135	204	19	greatly	greatly	ADV
ijassa-135	204	20	affected	affect	VERB
ijassa-135	204	21	by	by	ADP
ijassa-135	204	22	random	random	ADJ
ijassa-135	204	23	factors	factor	NOUN
ijassa-135	204	24	.	.	PUNCT
ijassa-135	205	1	on	on	ADP
ijassa-135	205	2	the	the	DET
ijassa-135	205	3	other	other	ADJ
ijassa-135	205	4	hand	hand	NOUN
ijassa-135	205	5	,	,	PUNCT
ijassa-135	205	6	the	the	DET
ijassa-135	205	7	method	method	NOUN
ijassa-135	205	8	developed	develop	VERB
ijassa-135	205	9	in	in	ADP
ijassa-135	205	10	this	this	DET
ijassa-135	205	11	research	research	NOUN
ijassa-135	205	12	righteously	righteously	ADV
ijassa-135	205	13	employs	employ	VERB
ijassa-135	205	14	the	the	DET
ijassa-135	205	15	physical	physical	ADJ
ijassa-135	205	16	background	background	NOUN
ijassa-135	205	17	information	information	NOUN
ijassa-135	205	18	and	and	CCONJ
ijassa-135	205	19	observed	observed	ADJ
ijassa-135	205	20	process	process	NOUN
ijassa-135	205	21	data	datum	NOUN
ijassa-135	205	22	so	so	SCONJ
ijassa-135	205	23	that	that	SCONJ
ijassa-135	205	24	interval	interval	NOUN
ijassa-135	205	25	estimates	estimate	NOUN
ijassa-135	205	26	can	can	AUX
ijassa-135	205	27	be	be	AUX
ijassa-135	205	28	directly	directly	ADV
ijassa-135	205	29	produced	produce	VERB
ijassa-135	205	30	from	from	ADP
ijassa-135	205	31	the	the	DET
ijassa-135	205	32	estimation	estimation	NOUN
ijassa-135	205	33	of	of	ADP
ijassa-135	205	34	the	the	DET
ijassa-135	205	35	parameters	parameter	NOUN
ijassa-135	205	36	.	.	PUNCT
ijassa-135	206	1	comparing	compare	VERB
ijassa-135	206	2	to	to	ADP
ijassa-135	206	3	the	the	DET
ijassa-135	206	4	point	point	NOUN
ijassa-135	206	5	estimate	estimate	NOUN
ijassa-135	206	6	method	method	NOUN
ijassa-135	206	7	,	,	PUNCT
ijassa-135	206	8	our	our	PRON
ijassa-135	206	9	method	method	NOUN
ijassa-135	206	10	reduces	reduce	VERB
ijassa-135	206	11	the	the	DET
ijassa-135	206	12	effect	effect	NOUN
ijassa-135	206	13	of	of	ADP
ijassa-135	206	14	random	random	ADJ
ijassa-135	206	15	errors	error	NOUN
ijassa-135	206	16	and	and	CCONJ
ijassa-135	206	17	makes	make	VERB
ijassa-135	206	18	the	the	DET
ijassa-135	206	19	system	system	NOUN
ijassa-135	206	20	evaluation	evaluation	NOUN
ijassa-135	206	21	and	and	CCONJ
ijassa-135	206	22	estimation	estimation	NOUN
ijassa-135	206	23	process	process	NOUN
ijassa-135	206	24	converge	converge	VERB
ijassa-135	206	25	more	more	ADV
ijassa-135	206	26	quickly	quickly	ADV
ijassa-135	206	27	.	.	PUNCT
ijassa-135	207	1	example3	example3	PROPN
ijassa-135	207	2	.	.	PUNCT
ijassa-135	208	1	let	let	VERB
ijassa-135	208	2	us	we	PRON
ijassa-135	208	3	now	now	ADV
ijassa-135	208	4	look	look	VERB
ijassa-135	208	5	at	at	ADP
ijassa-135	208	6	how	how	SCONJ
ijassa-135	208	7	to	to	PART
ijassa-135	208	8	place	place	VERB
ijassa-135	208	9	optimal	optimal	ADJ
ijassa-135	208	10	weights	weight	NOUN
ijassa-135	208	11	for	for	ADP
ijassa-135	208	12	nonlinear	nonlinear	ADJ
ijassa-135	208	13	models	model	NOUN
ijassa-135	208	14	.	.	PUNCT
ijassa-135	209	1	assume	assume	VERB
ijassa-135	209	2	f(t	f(t	PROPN
ijassa-135	209	3	,	,	PUNCT
ijassa-135	209	4	β	β	X
ijassa-135	209	5	)	)	PUNCT
ijassa-135	209	6	=	=	SYM
ijassa-135	210	1	1	1	NUM
ijassa-135	210	2	+	+	CCONJ
ijassa-135	210	3	(	(	PUNCT
ijassa-135	210	4	5	5	NUM
ijassa-135	210	5	+	+	SYM
ijassa-135	210	6	tβ)0.1	tβ)0.1	ADJ
ijassa-135	210	7	,	,	PUNCT
ijassa-135	210	8	y(t	y(t	NUM
ijassa-135	210	9	)	)	PUNCT
ijassa-135	211	1	=	=	PUNCT
ijassa-135	211	2	f(t	f(t	NOUN
ijassa-135	211	3	,	,	PUNCT
ijassa-135	211	4	β	β	X
ijassa-135	211	5	+	+	NUM
ijassa-135	211	6	ε(t	ε(t	NOUN
ijassa-135	211	7	)	)	PUNCT
ijassa-135	211	8	,	,	PUNCT
ijassa-135	211	9	ε(t	ε(t	PROPN
ijassa-135	211	10	)	)	PUNCT
ijassa-135	211	11	iid∼n(0	iid∼n(0	NOUN
ijassa-135	211	12	,	,	PUNCT
ijassa-135	211	13	0.012	0.012	NUM
ijassa-135	211	14	)	)	PUNCT
ijassa-135	211	15	,	,	PUNCT
ijassa-135	211	16	β̃	β̃	PROPN
ijassa-135	211	17	=	=	SYM
ijassa-135	211	18	β	β	PROPN
ijassa-135	211	19	+	+	CCONJ
ijassa-135	211	20	η	η	PROPN
ijassa-135	211	21	,	,	PUNCT
ijassa-135	211	22	η	η	PROPN
ijassa-135	211	23	∼	∼	NOUN
ijassa-135	211	24	n(0	n(0	PROPN
ijassa-135	211	25	,	,	PUNCT
ijassa-135	211	26	0.052	0.052	NUM
ijassa-135	211	27	)	)	PUNCT
ijassa-135	211	28	let	let	VERB
ijassa-135	211	29	t	t	NOUN
ijassa-135	211	30	=	=	PUNCT
ijassa-135	211	31	0.01	0.01	NUM
ijassa-135	211	32	∗	∗	PROPN
ijassa-135	211	33	j	j	PROPN
ijassa-135	211	34	,	,	PUNCT
ijassa-135	211	35	j	j	PROPN
ijassa-135	211	36	=	=	SYM
ijassa-135	211	37	1	1	NUM
ijassa-135	211	38	,	,	PUNCT
ijassa-135	211	39	...	...	PUNCT
ijassa-135	211	40	,	,	PUNCT
ijassa-135	211	41	100	100	NUM
ijassa-135	211	42	,	,	PUNCT
ijassa-135	211	43	and	and	CCONJ
ijassa-135	211	44	the	the	DET
ijassa-135	211	45	true	true	ADJ
ijassa-135	211	46	value	value	NOUN
ijassa-135	211	47	of	of	ADP
ijassa-135	211	48	β	β	PROPN
ijassa-135	211	49	is	be	AUX
ijassa-135	211	50	8	8	NUM
ijassa-135	211	51	.	.	PUNCT
ijassa-135	212	1	let	let	VERB
ijassa-135	212	2	us	we	PRON
ijassa-135	212	3	generate	generate	VERB
ijassa-135	212	4	50	50	NUM
ijassa-135	212	5	observational	observational	ADJ
ijassa-135	212	6	data	datum	NOUN
ijassa-135	212	7	{	{	PUNCT
ijassa-135	212	8	yi(t)}1001	yi(t)}1001	PROPN
ijassa-135	212	9	,	,	PUNCT
ijassa-135	212	10	β̃i	β̃i	NOUN
ijassa-135	212	11	,	,	PUNCT
ijassa-135	212	12	i=1,	i=1,	PROPN
ijassa-135	212	13	...	...	PUNCT
ijassa-135	212	14	,50	,50	PROPN
ijassa-135	212	15	.	.	PUNCT
ijassa-135	213	1	then	then	ADV
ijassa-135	213	2	,	,	PUNCT
ijassa-135	213	3	when	when	SCONJ
ijassa-135	213	4	ρ	ρ	PROPN
ijassa-135	213	5	=	=	SYM
ijassa-135	213	6	0.012/0.052	0.012/0.052	PROPN
ijassa-135	213	7	,	,	PUNCT
ijassa-135	213	8	let	let	VERB
ijassa-135	213	9	us	we	PRON
ijassa-135	213	10	solve	solve	VERB
ijassa-135	213	11	the	the	DET
ijassa-135	213	12	minimization	minimization	NOUN
ijassa-135	213	13	problem	problem	NOUN
ijassa-135	213	14	(	(	PUNCT
ijassa-135	213	15	6	6	NUM
ijassa-135	213	16	)	)	SYM
ijassa-135	213	17	50	50	NUM
ijassa-135	213	18	times	time	NOUN
ijassa-135	213	19	,	,	PUNCT
ijassa-135	213	20	producing	produce	VERB
ijassa-135	213	21	the	the	DET
ijassa-135	213	22	mean	mean	ADJ
ijassa-135	213	23	square	square	ADJ
ijassa-135	213	24	error	error	NOUN
ijassa-135	213	25	0.0394	0.0394	NUM
ijassa-135	213	26	.	.	PUNCT
ijassa-135	214	1	and	and	CCONJ
ijassa-135	214	2	when	when	SCONJ
ijassa-135	214	3	ρ	ρ	PROPN
ijassa-135	214	4	=	=	SYM
ijassa-135	214	5	2.33∗0.012/0.052	2.33∗0.012/0.052	PROPN
ijassa-135	214	6	,	,	PUNCT
ijassa-135	214	7	the	the	DET
ijassa-135	214	8	mean	mean	ADJ
ijassa-135	214	9	square	square	ADJ
ijassa-135	214	10	error	error	NOUN
ijassa-135	214	11	reaches	reach	VERB
ijassa-135	214	12	the	the	DET
ijassa-135	214	13	minimum	minimum	ADJ
ijassa-135	214	14	value	value	NOUN
ijassa-135	214	15	0.0372	0.0372	NUM
ijassa-135	214	16	.	.	PUNCT
ijassa-135	215	1	however	however	ADV
ijassa-135	215	2	,	,	PUNCT
ijassa-135	215	3	in	in	ADP
ijassa-135	215	4	theory	theory	NOUN
ijassa-135	215	5	,	,	PUNCT
ijassa-135	215	6	the	the	DET
ijassa-135	215	7	mean	mean	ADJ
ijassa-135	215	8	square	square	ADJ
ijassa-135	215	9	error	error	NOUN
ijassa-135	215	10	is	be	AUX
ijassa-135	215	11	0.0361	0.0361	NUM
ijassa-135	215	12	.	.	PUNCT
ijassa-135	216	1	this	this	DET
ijassa-135	216	2	end	end	NOUN
ijassa-135	216	3	indicates	indicate	VERB
ijassa-135	216	4	that	that	SCONJ
ijassa-135	216	5	for	for	ADP
ijassa-135	216	6	a	a	DET
ijassa-135	216	7	nonlinear	nonlinear	ADJ
ijassa-135	216	8	system	system	NOUN
ijassa-135	216	9	,	,	PUNCT
ijassa-135	216	10	the	the	DET
ijassa-135	216	11	optimal	optimal	ADJ
ijassa-135	216	12	choice	choice	NOUN
ijassa-135	216	13	of	of	ADP
ijassa-135	216	14	weights	weight	NOUN
ijassa-135	216	15	for	for	ADP
ijassa-135	216	16	fusing	fuse	VERB
ijassa-135	216	17	information	information	NOUN
ijassa-135	216	18	not	not	PART
ijassa-135	216	19	only	only	ADV
ijassa-135	216	20	depends	depend	VERB
ijassa-135	216	21	on	on	ADP
ijassa-135	216	22	observational	observational	ADJ
ijassa-135	216	23	precisions	precision	NOUN
ijassa-135	216	24	but	but	CCONJ
ijassa-135	216	25	also	also	ADV
ijassa-135	216	26	the	the	DET
ijassa-135	216	27	model	model	NOUN
ijassa-135	216	28	curvature	curvature	NOUN
ijassa-135	216	29	involved	involve	VERB
ijassa-135	216	30	.	.	PUNCT
ijassa-135	217	1	all	all	DET
ijassa-135	217	2	the	the	DET
ijassa-135	217	3	three	three	NUM
ijassa-135	217	4	examples	example	NOUN
ijassa-135	217	5	above	above	ADP
ijassa-135	217	6	verify	verify	VERB
ijassa-135	217	7	the	the	DET
ijassa-135	217	8	transformational	transformational	ADJ
ijassa-135	217	9	relationship	relationship	NOUN
ijassa-135	217	10	of	of	ADP
ijassa-135	217	11	system	system	NOUN
ijassa-135	217	12	model	model	NOUN
ijassa-135	217	13	information	information	NOUN
ijassa-135	217	14	,	,	PUNCT
ijassa-135	217	15	prior	prior	ADJ
ijassa-135	217	16	knowledge	knowledge	NOUN
ijassa-135	217	17	,	,	PUNCT
ijassa-135	217	18	and	and	CCONJ
ijassa-135	217	19	observational	observational	ADJ
ijassa-135	217	20	data	datum	NOUN
ijassa-135	217	21	in	in	ADP
ijassa-135	217	22	the	the	DET
ijassa-135	217	23	recognition	recognition	NOUN
ijassa-135	217	24	process	process	NOUN
ijassa-135	217	25	of	of	ADP
ijassa-135	217	26	the	the	DET
ijassa-135	217	27	underlying	underlie	VERB
ijassa-135	217	28	system	system	NOUN
ijassa-135	217	29	,	,	PUNCT
ijassa-135	217	30	where	where	SCONJ
ijassa-135	217	31	the	the	DET
ijassa-135	217	32	model	model	NOUN
ijassa-135	217	33	information	information	NOUN
ijassa-135	217	34	can	can	AUX
ijassa-135	217	35	be	be	AUX
ijassa-135	217	36	247	247	NUM
ijassa-135	217	37	advances	advance	NOUN
ijassa-135	217	38	in	in	ADP
ijassa-135	217	39	systems	system	NOUN
ijassa-135	217	40	science	science	NOUN
ijassa-135	217	41	and	and	CCONJ
ijassa-135	217	42	applications	application	NOUN
ijassa-135	217	43	(	(	PUNCT
ijassa-135	217	44	2013	2013	NUM
ijassa-135	217	45	)	)	PUNCT
ijassa-135	217	46	vol.13	vol.13	NOUN
ijassa-135	217	47	no.3	no.3	PROPN
ijassa-135	217	48	strengthened	strengthen	VERB
ijassa-135	217	49	through	through	ADP
ijassa-135	217	50	the	the	DET
ijassa-135	217	51	usage	usage	NOUN
ijassa-135	217	52	of	of	ADP
ijassa-135	217	53	process	process	NOUN
ijassa-135	217	54	data	datum	NOUN
ijassa-135	217	55	,	,	PUNCT
ijassa-135	217	56	and	and	CCONJ
ijassa-135	217	57	when	when	SCONJ
ijassa-135	217	58	the	the	DET
ijassa-135	217	59	observational	observational	ADJ
ijassa-135	217	60	data	data	NOUN
ijassa-135	217	61	is	be	AUX
ijassa-135	217	62	insufficient	insufficient	ADJ
ijassa-135	217	63	,	,	PUNCT
ijassa-135	217	64	the	the	DET
ijassa-135	217	65	shortage	shortage	NOUN
ijassa-135	217	66	in	in	ADP
ijassa-135	217	67	information	information	NOUN
ijassa-135	217	68	can	can	AUX
ijassa-135	217	69	be	be	AUX
ijassa-135	217	70	made	make	VERB
ijassa-135	217	71	up	up	ADP
ijassa-135	217	72	by	by	ADP
ijassa-135	217	73	supplementing	supplement	VERB
ijassa-135	217	74	additional	additional	ADJ
ijassa-135	217	75	prior	prior	ADJ
ijassa-135	217	76	knowledge	knowledge	NOUN
ijassa-135	217	77	.	.	PUNCT
ijassa-135	218	1	4	4	NUM
ijassa-135	218	2	summary	summary	NOUN
ijassa-135	218	3	continuing	continue	VERB
ijassa-135	218	4	literature[1	literature[1	PROPN
ijassa-135	218	5	]	]	PUNCT
ijassa-135	218	6	,	,	PUNCT
ijassa-135	218	7	in	in	ADP
ijassa-135	218	8	this	this	DET
ijassa-135	218	9	paper	paper	NOUN
ijassa-135	218	10	we	we	PRON
ijassa-135	218	11	studied	study	VERB
ijassa-135	218	12	how	how	SCONJ
ijassa-135	218	13	to	to	PART
ijassa-135	218	14	fuse	fuse	VERB
ijassa-135	218	15	heterogeneous	heterogeneous	ADJ
ijassa-135	218	16	sets	set	NOUN
ijassa-135	218	17	of	of	ADP
ijassa-135	218	18	data	datum	NOUN
ijassa-135	218	19	together	together	ADV
ijassa-135	218	20	consistently	consistently	ADV
ijassa-135	218	21	so	so	SCONJ
ijassa-135	218	22	that	that	SCONJ
ijassa-135	218	23	better	well	ADJ
ijassa-135	218	24	results	result	NOUN
ijassa-135	218	25	can	can	AUX
ijassa-135	218	26	be	be	AUX
ijassa-135	218	27	obtained	obtain	VERB
ijassa-135	218	28	for	for	ADP
ijassa-135	218	29	system	system	NOUN
ijassa-135	218	30	evaluations	evaluation	NOUN
ijassa-135	218	31	and	and	CCONJ
ijassa-135	218	32	estimations	estimation	NOUN
ijassa-135	218	33	.	.	PUNCT
ijassa-135	219	1	it	it	PRON
ijassa-135	219	2	is	be	AUX
ijassa-135	219	3	shown	show	VERB
ijassa-135	219	4	that	that	SCONJ
ijassa-135	219	5	if	if	SCONJ
ijassa-135	219	6	the	the	DET
ijassa-135	219	7	types	type	NOUN
ijassa-135	219	8	of	of	ADP
ijassa-135	219	9	data	datum	NOUN
ijassa-135	219	10	considered	consider	VERB
ijassa-135	219	11	are	be	AUX
ijassa-135	219	12	few	few	ADJ
ijassa-135	219	13	and	and	CCONJ
ijassa-135	219	14	the	the	DET
ijassa-135	219	15	available	available	ADJ
ijassa-135	219	16	observational	observational	ADJ
ijassa-135	219	17	data	datum	NOUN
ijassa-135	219	18	is	be	AUX
ijassa-135	219	19	insufficient	insufficient	ADJ
ijassa-135	219	20	,	,	PUNCT
ijassa-135	219	21	one	one	PRON
ijassa-135	219	22	can	can	AUX
ijassa-135	219	23	consider	consider	VERB
ijassa-135	219	24	obtaining	obtain	VERB
ijassa-135	219	25	process	process	NOUN
ijassa-135	219	26	information	information	NOUN
ijassa-135	219	27	and	and	CCONJ
ijassa-135	219	28	additional	additional	ADJ
ijassa-135	219	29	prior	prior	ADJ
ijassa-135	219	30	knowledge	knowledge	NOUN
ijassa-135	219	31	.	.	PUNCT
ijassa-135	220	1	it	it	PRON
ijassa-135	220	2	is	be	AUX
ijassa-135	220	3	because	because	SCONJ
ijassa-135	220	4	the	the	DET
ijassa-135	220	5	limited	limited	ADJ
ijassa-135	220	6	amount	amount	NOUN
ijassa-135	220	7	of	of	ADP
ijassa-135	220	8	observational	observational	ADJ
ijassa-135	220	9	data	datum	NOUN
ijassa-135	220	10	could	could	AUX
ijassa-135	220	11	make	make	VERB
ijassa-135	220	12	the	the	DET
ijassa-135	220	13	process	process	NOUN
ijassa-135	220	14	of	of	ADP
ijassa-135	220	15	system	system	NOUN
ijassa-135	220	16	evaluation	evaluation	NOUN
ijassa-135	220	17	and	and	CCONJ
ijassa-135	220	18	estimation	estimation	NOUN
ijassa-135	220	19	converge	converge	VERB
ijassa-135	220	20	extremely	extremely	ADV
ijassa-135	220	21	slowly	slowly	ADV
ijassa-135	220	22	or	or	CCONJ
ijassa-135	220	23	stop	stop	VERB
ijassa-135	220	24	converging	converge	VERB
ijassa-135	220	25	completely	completely	ADV
ijassa-135	220	26	after	after	ADP
ijassa-135	220	27	reaching	reach	VERB
ijassa-135	220	28	a	a	DET
ijassa-135	220	29	certain	certain	ADJ
ijassa-135	220	30	degree	degree	NOUN
ijassa-135	220	31	.	.	PUNCT
ijassa-135	221	1	with	with	ADP
ijassa-135	221	2	process	process	NOUN
ijassa-135	221	3	information	information	NOUN
ijassa-135	221	4	or	or	CCONJ
ijassa-135	221	5	additional	additional	ADJ
ijassa-135	221	6	prior	prior	ADJ
ijassa-135	221	7	knowledge	knowledge	NOUN
ijassa-135	221	8	added	added	AUX
ijassa-135	221	9	,	,	PUNCT
ijassa-135	221	10	the	the	DET
ijassa-135	221	11	convergence	convergence	NOUN
ijassa-135	221	12	will	will	AUX
ijassa-135	221	13	continue	continue	VERB
ijassa-135	221	14	.	.	PUNCT
ijassa-135	222	1	the	the	DET
ijassa-135	222	2	speed	speed	NOUN
ijassa-135	222	3	of	of	ADP
ijassa-135	222	4	the	the	DET
ijassa-135	222	5	resumed	resume	VERB
ijassa-135	222	6	convergence	convergence	NOUN
ijassa-135	222	7	is	be	AUX
ijassa-135	222	8	dependent	dependent	ADJ
ijassa-135	222	9	on	on	ADP
ijassa-135	222	10	how	how	SCONJ
ijassa-135	222	11	the	the	DET
ijassa-135	222	12	process	process	NOUN
ijassa-135	222	13	information	information	NOUN
ijassa-135	222	14	is	be	AUX
ijassa-135	222	15	applied	apply	VERB
ijassa-135	222	16	,	,	PUNCT
ijassa-135	222	17	how	how	SCONJ
ijassa-135	222	18	good	good	ADJ
ijassa-135	222	19	quality	quality	NOUN
ijassa-135	222	20	the	the	DET
ijassa-135	222	21	prior	prior	ADJ
ijassa-135	222	22	knowledge	knowledge	NOUN
ijassa-135	222	23	is	be	AUX
ijassa-135	222	24	and	and	CCONJ
ijassa-135	222	25	how	how	SCONJ
ijassa-135	222	26	consistent	consistent	ADJ
ijassa-135	222	27	the	the	DET
ijassa-135	222	28	newly	newly	ADV
ijassa-135	222	29	adopted	adopt	VERB
ijassa-135	222	30	prior	prior	ADJ
ijassa-135	222	31	information	information	NOUN
ijassa-135	222	32	is	be	AUX
ijassa-135	222	33	with	with	ADP
ijassa-135	222	34	the	the	DET
ijassa-135	222	35	available	available	ADJ
ijassa-135	222	36	observational	observational	ADJ
ijassa-135	222	37	data	datum	NOUN
ijassa-135	222	38	.	.	PUNCT
ijassa-135	223	1	this	this	DET
ijassa-135	223	2	end	end	NOUN
ijassa-135	223	3	has	have	AUX
ijassa-135	223	4	been	be	AUX
ijassa-135	223	5	well	well	ADV
ijassa-135	223	6	illustrated	illustrate	VERB
ijassa-135	223	7	by	by	ADP
ijassa-135	223	8	the	the	DET
ijassa-135	223	9	case	case	NOUN
ijassa-135	223	10	studies	study	NOUN
ijassa-135	223	11	considered	consider	VERB
ijassa-135	223	12	in	in	ADP
ijassa-135	223	13	section	section	NOUN
ijassa-135	223	14	3	3	NUM
ijassa-135	223	15	.	.	PUNCT
ijassa-135	224	1	when	when	SCONJ
ijassa-135	224	2	there	there	PRON
ijassa-135	224	3	is	be	VERB
ijassa-135	224	4	only	only	ADV
ijassa-135	224	5	a	a	DET
ijassa-135	224	6	small	small	ADJ
ijassa-135	224	7	sample	sample	NOUN
ijassa-135	224	8	available	available	ADJ
ijassa-135	224	9	for	for	ADP
ijassa-135	224	10	a	a	DET
ijassa-135	224	11	specific	specific	ADJ
ijassa-135	224	12	system	system	NOUN
ijassa-135	224	13	evaluation	evaluation	NOUN
ijassa-135	224	14	and	and	CCONJ
ijassa-135	224	15	estimation	estimation	NOUN
ijassa-135	224	16	,	,	PUNCT
ijassa-135	224	17	this	this	DET
ijassa-135	224	18	work	work	NOUN
ijassa-135	224	19	provides	provide	VERB
ijassa-135	224	20	the	the	DET
ijassa-135	224	21	theoretical	theoretical	ADJ
ijassa-135	224	22	guideline	guideline	NOUN
ijassa-135	224	23	for	for	ADP
ijassa-135	224	24	how	how	SCONJ
ijassa-135	224	25	to	to	PART
ijassa-135	224	26	excavate	excavate	VERB
ijassa-135	224	27	other	other	ADJ
ijassa-135	224	28	sources	source	NOUN
ijassa-135	224	29	of	of	ADP
ijassa-135	224	30	information	information	NOUN
ijassa-135	224	31	and	and	CCONJ
ijassa-135	224	32	how	how	SCONJ
ijassa-135	224	33	newly	newly	ADV
ijassa-135	224	34	adopted	adopt	VERB
ijassa-135	224	35	information	information	NOUN
ijassa-135	224	36	should	should	AUX
ijassa-135	224	37	be	be	AUX
ijassa-135	224	38	fused	fuse	VERB
ijassa-135	224	39	with	with	ADP
ijassa-135	224	40	what	what	PRON
ijassa-135	224	41	is	be	AUX
ijassa-135	224	42	available	available	ADJ
ijassa-135	224	43	.	.	PUNCT
ijassa-135	225	1	acknowledgements	acknowledgement	NOUN
ijassa-135	225	2	this	this	DET
ijassa-135	225	3	work	work	NOUN
ijassa-135	225	4	is	be	AUX
ijassa-135	225	5	supported	support	VERB
ijassa-135	225	6	by	by	ADP
ijassa-135	225	7	the	the	DET
ijassa-135	225	8	natural	natural	ADJ
ijassa-135	225	9	science	science	PROPN
ijassa-135	225	10	foundation	foundation	PROPN
ijassa-135	225	11	of	of	ADP
ijassa-135	225	12	china	china	PROPN
ijassa-135	225	13	(	(	PUNCT
ijassa-135	225	14	60974124	60974124	NUM
ijassa-135	225	15	)	)	PUNCT
ijassa-135	225	16	,	,	PUNCT
ijassa-135	225	17	the	the	DET
ijassa-135	225	18	program	program	NOUN
ijassa-135	225	19	for	for	ADP
ijassa-135	225	20	new	new	ADJ
ijassa-135	225	21	century	century	NOUN
ijassa-135	225	22	excellent	excellent	ADJ
ijassa-135	225	23	talents	talent	NOUN
ijassa-135	225	24	in	in	ADP
ijassa-135	225	25	university	university	NOUN
ijassa-135	225	26	and	and	CCONJ
ijassa-135	225	27	the	the	DET
ijassa-135	225	28	projectsponsored	projectsponsore	VERB
ijassa-135	225	29	by	by	ADP
ijassa-135	225	30	srf	srf	PROPN
ijassa-135	225	31	for	for	ADP
ijassa-135	225	32	rocs	roc	NOUN
ijassa-135	225	33	,	,	PUNCT
ijassa-135	225	34	sem	sem	NOUN
ijassa-135	225	35	in	in	ADP
ijassa-135	225	36	china	china	PROPN
ijassa-135	225	37	,	,	PUNCT
ijassa-135	225	38	the	the	DET
ijassa-135	225	39	key	key	ADJ
ijassa-135	225	40	lab	lab	NOUN
ijassa-135	225	41	open	open	ADJ
ijassa-135	225	42	foundation	foundation	NOUN
ijassa-135	225	43	for	for	ADP
ijassa-135	225	44	space	space	NOUN
ijassa-135	225	45	flight	flight	NOUN
ijassa-135	225	46	dynamics	dynamic	NOUN
ijassa-135	225	47	technique	technique	NOUN
ijassa-135	225	48	(	(	PUNCT
ijassa-135	225	49	sfdlxz-2010	sfdlxz-2010	NOUN
ijassa-135	225	50	-	-	PUNCT
ijassa-135	225	51	004	004	NUM
ijassa-135	225	52	)	)	PUNCT
ijassa-135	225	53	.	.	PUNCT
ijassa-135	226	1	references	reference	NOUN
ijassa-135	226	2	[	[	X
ijassa-135	226	3	1	1	NUM
ijassa-135	226	4	]	]	PUNCT
ijassa-135	226	5	xj	xj	PROPN
ijassa-135	226	6	duan	duan	PROPN
ijassa-135	226	7	,	,	PUNCT
ijassa-135	226	8	y.	y.	PROPN
ijassa-135	226	9	lin	lin	PROPN
ijassa-135	226	10	.	.	PUNCT
ijassa-135	227	1	(	(	PUNCT
ijassa-135	227	2	2011	2011	NUM
ijassa-135	227	3	)	)	PUNCT
ijassa-135	227	4	,	,	PUNCT
ijassa-135	227	5	“	"	PUNCT
ijassa-135	227	6	conservation	conservation	NOUN
ijassa-135	227	7	law	law	NOUN
ijassa-135	227	8	of	of	ADP
ijassa-135	227	9	information	information	NOUN
ijassa-135	227	10	and	and	CCONJ
ijassa-135	227	11	its	its	PRON
ijassa-135	227	12	application	application	NOUN
ijassa-135	227	13	in	in	ADP
ijassa-135	227	14	evaluation	evaluation	NOUN
ijassa-135	227	15	and	and	CCONJ
ijassa-135	227	16	estimation	estimation	NOUN
ijassa-135	227	17	of	of	ADP
ijassa-135	227	18	complex	complex	ADJ
ijassa-135	227	19	systems	system	NOUN
ijassa-135	227	20	”	"	PUNCT
ijassa-135	227	21	,	,	PUNCT
ijassa-135	227	22	kybernetes	kybernete	NOUN
ijassa-135	227	23	:	:	PUNCT
ijassa-135	227	24	the	the	DET
ijassa-135	227	25	international	international	ADJ
ijassa-135	227	26	journal	journal	NOUN
ijassa-135	227	27	of	of	ADP
ijassa-135	227	28	cybernetics	cybernetic	NOUN
ijassa-135	227	29	,	,	PUNCT
ijassa-135	227	30	systems	system	NOUN
ijassa-135	227	31	,	,	PUNCT
ijassa-135	227	32	and	and	CCONJ
ijassa-135	227	33	management	management	NOUN
ijassa-135	227	34	science	science	NOUN
ijassa-135	227	35	,	,	PUNCT
ijassa-135	227	36	vol.40	vol.40	PROPN
ijassa-135	227	37	no.1/2	no.1/2	PROPN
ijassa-135	227	38	,	,	PUNCT
ijassa-135	227	39	pp.262	pp.262	PROPN
ijassa-135	227	40	-	-	NOUN
ijassa-135	227	41	274	274	NUM
ijassa-135	227	42	[	[	X
ijassa-135	227	43	2	2	NUM
ijassa-135	227	44	]	]	X
ijassa-135	227	45	y.	y.	PROPN
ijassa-135	227	46	lin	lin	PROPN
ijassa-135	227	47	.	.	PUNCT
ijassa-135	228	1	(	(	PUNCT
ijassa-135	228	2	2008	2008	NUM
ijassa-135	228	3	)	)	PUNCT
ijassa-135	228	4	,	,	PUNCT
ijassa-135	228	5	systemic	systemic	ADJ
ijassa-135	228	6	yoyos	yoyos	NOUN
ijassa-135	228	7	:	:	PUNCT
ijassa-135	228	8	some	some	DET
ijassa-135	228	9	impacts	impact	NOUN
ijassa-135	228	10	of	of	ADP
ijassa-135	228	11	the	the	DET
ijassa-135	228	12	second	second	ADJ
ijassa-135	228	13	dimension	dimension	NOUN
ijassa-135	228	14	,	,	PUNCT
ijassa-135	228	15	taylor	taylor	PROPN
ijassa-135	228	16	and	and	CCONJ
ijassa-135	228	17	francis	francis	PROPN
ijassa-135	228	18	,	,	PUNCT
ijassa-135	228	19	new	new	PROPN
ijassa-135	228	20	york	york	PROPN
ijassa-135	228	21	.	.	PUNCT
ijassa-135	229	1	[	[	X
ijassa-135	229	2	3	3	X
ijassa-135	229	3	]	]	PUNCT
ijassa-135	229	4	s.	s.	PROPN
ijassa-135	229	5	s.	s.	PROPN
ijassa-135	229	6	mao	mao	PROPN
ijassa-135	229	7	.	.	PUNCT
ijassa-135	230	1	(	(	PUNCT
ijassa-135	230	2	1999	1999	NUM
ijassa-135	230	3	)	)	PUNCT
ijassa-135	230	4	,	,	PUNCT
ijassa-135	230	5	bayesian	bayesian	NOUN
ijassa-135	230	6	statistics	statistic	NOUN
ijassa-135	230	7	.	.	PUNCT
ijassa-135	231	1	beijing	beijing	PROPN
ijassa-135	231	2	:	:	PUNCT
ijassa-135	232	1	china	china	PROPN
ijassa-135	232	2	statistics	statistics	PROPN
ijassa-135	232	3	publishing	publishing	PROPN
ijassa-135	232	4	house	house	PROPN
ijassa-135	232	5	.	.	PUNCT
ijassa-135	233	1	xiaojun	xiaojun	PROPN
ijassa-135	233	2	duan	duan	PROPN
ijassa-135	233	3	,	,	PUNCT
ijassa-135	233	4	yi	yi	PROPN
ijassa-135	233	5	lin	lin	PROPN
ijassa-135	233	6	:	:	PUNCT
ijassa-135	233	7	ways	way	NOUN
ijassa-135	233	8	of	of	ADP
ijassa-135	233	9	fusing	fuse	VERB
ijassa-135	233	10	different	different	ADJ
ijassa-135	233	11	types	type	NOUN
ijassa-135	233	12	of	of	ADP
ijassa-135	233	13	information	information	NOUN
ijassa-135	233	14	and	and	CCONJ
ijassa-135	233	15	how	how	SCONJ
ijassa-135	233	16	systemic	systemic	ADJ
ijassa-135	233	17	...	...	PUNCT
ijassa-135	233	18	248	248	NUM
ijassa-135	234	1	[	[	SYM
ijassa-135	234	2	4	4	NUM
ijassa-135	234	3	]	]	X
ijassa-135	234	4	d.	d.	PROPN
ijassa-135	234	5	m.	m.	PROPN
ijassa-135	234	6	bates	bates	PROPN
ijassa-135	234	7	and	and	CCONJ
ijassa-135	234	8	d.	d.	PROPN
ijassa-135	234	9	g.	g.	PROPN
ijassa-135	234	10	watts	watts	PROPN
ijassa-135	234	11	.	.	PUNCT
ijassa-135	235	1	(	(	PUNCT
ijassa-135	235	2	1997	1997	NUM
ijassa-135	235	3	)	)	PUNCT
ijassa-135	235	4	,	,	PUNCT
ijassa-135	235	5	nonlinear	nonlinear	ADJ
ijassa-135	235	6	regressive	regressive	ADJ
ijassa-135	235	7	analysis	analysis	NOUN
ijassa-135	235	8	and	and	CCONJ
ijassa-135	235	9	its	its	PRON
ijassa-135	235	10	application	application	NOUN
ijassa-135	235	11	,	,	PUNCT
ijassa-135	235	12	translator	translator	NOUN
ijassa-135	235	13	:	:	PUNCT
ijassa-135	235	14	bocheng	bocheng	PROPN
ijassa-135	235	15	wei	wei	PROPN
ijassa-135	235	16	.	.	PUNCT
ijassa-135	236	1	beijing	beijing	PROPN
ijassa-135	236	2	:	:	PUNCT
ijassa-135	237	1	china	china	PROPN
ijassa-135	237	2	statistics	statistics	PROPN
ijassa-135	237	3	publishing	publishing	PROPN
ijassa-135	237	4	house	house	PROPN
ijassa-135	237	5	.	.	PUNCT
ijassa-135	238	1	[	[	X
ijassa-135	238	2	5	5	NUM
ijassa-135	238	3	]	]	PUNCT
ijassa-135	238	4	x.	x.	NOUN
ijassa-135	239	1	p.	p.	PROPN
ijassa-135	239	2	zhang	zhang	PROPN
ijassa-135	239	3	,	,	PUNCT
ijassa-135	239	4	j.	j.	PROPN
ijassa-135	239	5	h.	h.	PROPN
ijassa-135	239	6	zhang	zhang	PROPN
ijassa-135	239	7	,	,	PUNCT
ijassa-135	239	8	and	and	CCONJ
ijassa-135	239	9	h.	h.	PROPN
ijassa-135	239	10	w.	w.	PROPN
ijassa-135	239	11	xie	xie	PROPN
ijassa-135	239	12	(	(	PUNCT
ijassa-135	239	13	2003	2003	NUM
ijassa-135	239	14	)	)	PUNCT
ijassa-135	239	15	,	,	PUNCT
ijassa-135	239	16	“	"	PUNCT
ijassa-135	239	17	a	a	DET
ijassa-135	239	18	few	few	ADJ
ijassa-135	239	19	discussion	discussion	NOUN
ijassa-135	239	20	of	of	ADP
ijassa-135	239	21	samples	sample	NOUN
ijassa-135	239	22	,	,	PUNCT
ijassa-135	239	23	a	a	DET
ijassa-135	239	24	prior	prior	ADJ
ijassa-135	239	25	information	information	NOUN
ijassa-135	239	26	and	and	CCONJ
ijassa-135	239	27	bayesian	bayesian	NOUN
ijassa-135	239	28	statistical	statistical	ADJ
ijassa-135	239	29	decision	decision	NOUN
ijassa-135	239	30	”	"	PUNCT
ijassa-135	239	31	,	,	PUNCT
ijassa-135	239	32	acta	acta	PROPN
ijassa-135	239	33	electronica	electronica	PROPN
ijassa-135	239	34	sinica	sinica	PROPN
ijassa-135	239	35	,	,	PUNCT
ijassa-135	239	36	vol.31	vol.31	NOUN
ijassa-135	239	37	no.4	no.4	PROPN
ijassa-135	239	38	,	,	PUNCT
ijassa-135	239	39	pp.536	pp.536	NOUN
ijassa-135	239	40	-	-	PUNCT
ijassa-135	239	41	538	538	NUM
ijassa-135	239	42	.	.	PUNCT
ijassa-135	240	1	[	[	X
ijassa-135	240	2	6	6	NUM
ijassa-135	240	3	]	]	X
ijassa-135	240	4	d.	d.	PROPN
ijassa-135	240	5	c.	c.	PROPN
ijassa-135	240	6	wang	wang	PROPN
ijassa-135	240	7	,	,	PUNCT
ijassa-135	240	8	j.	j.	PROPN
ijassa-135	240	9	h.	h.	PROPN
ijassa-135	240	10	ding	ding	PROPN
ijassa-135	240	11	,	,	PUNCT
ijassa-135	240	12	w.	w.	PROPN
ijassa-135	240	13	d.	d.	PROPN
ijassa-135	240	14	chen	chen	PROPN
ijassa-135	240	15	(	(	PUNCT
ijassa-135	240	16	2006	2006	NUM
ijassa-135	240	17	)	)	PUNCT
ijassa-135	240	18	,	,	PUNCT
ijassa-135	240	19	radar	radar	NOUN
ijassa-135	240	20	measurement	measurement	NOUN
ijassa-135	240	21	technique	technique	NOUN
ijassa-135	240	22	in	in	ADP
ijassa-135	240	23	precise	precise	ADJ
ijassa-135	240	24	tracking	tracking	NOUN
ijassa-135	240	25	,	,	PUNCT
ijassa-135	240	26	beijing	beijing	PROPN
ijassa-135	240	27	:	:	PUNCT
ijassa-135	240	28	publishing	publish	VERB
ijassa-135	240	29	house	house	NOUN
ijassa-135	240	30	of	of	ADP
ijassa-135	240	31	electronics	electronic	NOUN
ijassa-135	240	32	industry	industry	NOUN
ijassa-135	240	33	.	.	PUNCT
ijassa-135	241	1	[	[	X
ijassa-135	241	2	7	7	X
ijassa-135	241	3	]	]	X
ijassa-135	241	4	g.	g.	PROPN
ijassa-135	241	5	wang	wang	PROPN
ijassa-135	241	6	,	,	PUNCT
ijassa-135	241	7	x.	x.	PROPN
ijassa-135	241	8	j.	j.	PROPN
ijassa-135	241	9	duan	duan	PROPN
ijassa-135	241	10	,	,	PUNCT
ijassa-135	241	11	z.	z.	PROPN
ijassa-135	241	12	m.	m.	PROPN
ijassa-135	241	13	wang	wang	PROPN
ijassa-135	241	14	(	(	PUNCT
ijassa-135	241	15	2009	2009	NUM
ijassa-135	241	16	)	)	PUNCT
ijassa-135	241	17	,	,	PUNCT
ijassa-135	241	18	“	"	PUNCT
ijassa-135	241	19	conversion	conversion	NOUN
ijassa-135	241	20	method	method	NOUN
ijassa-135	241	21	of	of	ADP
ijassa-135	241	22	impact	impact	NOUN
ijassa-135	241	23	dispersion	dispersion	NOUN
ijassa-135	241	24	in	in	ADP
ijassa-135	241	25	substitute	substitute	NOUN
ijassa-135	241	26	equivalent	equivalent	ADJ
ijassa-135	241	27	tests	test	NOUN
ijassa-135	241	28	vased	vase	VERB
ijassa-135	241	29	on	on	ADP
ijassa-135	241	30	error	error	NOUN
ijassa-135	241	31	propagation	propagation	NOUN
ijassa-135	241	32	”	"	PUNCT
ijassa-135	241	33	,	,	PUNCT
ijassa-135	241	34	defence	defence	NOUN
ijassa-135	241	35	science	science	NOUN
ijassa-135	241	36	journal	journal	NOUN
ijassa-135	241	37	,	,	PUNCT
ijassa-135	241	38	vol.59	vol.59	NOUN
ijassa-135	241	39	no.1	no.1	NOUN
ijassa-135	241	40	,	,	PUNCT
ijassa-135	241	41	pp.15	pp.15	PROPN
ijassa-135	241	42	-	-	PROPN
ijassa-135	241	43	21	21	NUM
ijassa-135	241	44	.	.	PUNCT
ijassa-135	242	1	corresponding	correspond	VERB
ijassa-135	242	2	author	author	NOUN
ijassa-135	242	3	xiaojun	xiaojun	PROPN
ijassa-135	242	4	duan	duan	PROPN
ijassa-135	242	5	can	can	AUX
ijassa-135	242	6	be	be	AUX
ijassa-135	242	7	contracted	contract	VERB
ijassa-135	242	8	at	at	ADP
ijassa-135	242	9	:	:	PUNCT
ijassa-135	242	10	xjduan@nudt.edu.cn	xjduan@nudt.edu.cn	NOUN