id	sid	tid	token	lemma	pos
alkej-6	1	1	default	default	VERB
alkej-6	1	2	normal	normal	ADJ
alkej-6	1	3	template	template	NOUN
alkej-6	1	4	n.	n.	PROPN
alkej-6	1	5	h.	h.	PROPN
alkej-6	1	6	abbas	abbas	PROPN
alkej-6	1	7	/al	/al	PROPN
alkej-6	1	8	-	-	PUNCT
alkej-6	1	9	khwarizmi	khwarizmi	PROPN
alkej-6	1	10	engineering	engineering	NOUN
alkej-6	1	11	journal	journal	NOUN
alkej-6	1	12	,	,	PUNCT
alkej-6	1	13	vol.2	vol.2	PROPN
alkej-6	1	14	,	,	PUNCT
alkej-6	1	15	no	no	INTJ
alkej-6	1	16	.	.	PUNCT
alkej-6	2	1	1,pp	1,pp	NUM
alkej-6	2	2	70	70	NUM
alkej-6	2	3	-	-	SYM
alkej-6	2	4	77	77	NUM
alkej-6	2	5	(	(	PUNCT
alkej-6	2	6	2006	2006	NUM
alkej-6	2	7	)	)	PUNCT
alkej-6	2	8	70	70	NUM
alkej-6	2	9	al	al	PROPN
alkej-6	2	10	-	-	PUNCT
alkej-6	2	11	khwarizmi	khwarizmi	PROPN
alkej-6	2	12	engineering	engineering	PROPN
alkej-6	2	13	journal	journal	PROPN
alkej-6	2	14	al	al	PROPN
alkej-6	2	15	-	-	PUNCT
alkej-6	2	16	khwarizmi	khwarizmi	PROPN
alkej-6	2	17	engineering	engineering	NOUN
alkej-6	2	18	journal	journal	PROPN
alkej-6	2	19	,	,	PUNCT
alkej-6	2	20	vol.2	vol.2	PROPN
alkej-6	2	21	,	,	PUNCT
alkej-6	2	22	no.1,pp	no.1,pp	ADJ
alkej-6	2	23	70	70	NUM
alkej-6	2	24	-	-	SYM
alkej-6	2	25	77	77	NUM
alkej-6	2	26	,	,	PUNCT
alkej-6	2	27	(	(	PUNCT
alkej-6	2	28	2006	2006	NUM
alkej-6	2	29	)	)	PUNCT
alkej-6	2	30	direction	direction	NOUN
alkej-6	2	31	finding	finding	NOUN
alkej-6	2	32	using	use	VERB
alkej-6	2	33	gha	gha	NOUN
alkej-6	2	34	neural	neural	PROPN
alkej-6	2	35	networks	network	NOUN
alkej-6	2	36	n.	n.	PROPN
alkej-6	2	37	h.	h.	PROPN
alkej-6	2	38	abbas	abbas	PROPN
alkej-6	2	39	electrical	electrical	PROPN
alkej-6	2	40	eng	eng	PROPN
alkej-6	2	41	.	.	PROPN
alkej-6	2	42	dept	dept	PROPN
alkej-6	2	43	.	.	PROPN
alkej-6	2	44	,	,	PUNCT
alkej-6	2	45	college	college	NOUN
alkej-6	2	46	of	of	ADP
alkej-6	2	47	eng./	eng./	PROPN
alkej-6	2	48	university	university	PROPN
alkej-6	2	49	of	of	ADP
alkej-6	2	50	baghdad	baghdad	PROPN
alkej-6	2	51	(	(	PUNCT
alkej-6	2	52	received	receive	VERB
alkej-6	2	53	4	4	NUM
alkej-6	2	54	september	september	PROPN
alkej-6	2	55	2005	2005	NUM
alkej-6	2	56	;	;	PUNCT
alkej-6	2	57	accepted	accept	VERB
alkej-6	2	58	4	4	NUM
alkej-6	2	59	april	april	PROPN
alkej-6	2	60	2006	2006	NUM
alkej-6	2	61	)	)	PUNCT
alkej-6	3	1	abstract	abstract	NOUN
alkej-6	3	2	:	:	PUNCT
alkej-6	3	3	this	this	DET
alkej-6	3	4	paper	paper	NOUN
alkej-6	3	5	adapted	adapt	VERB
alkej-6	3	6	the	the	DET
alkej-6	3	7	neural	neural	ADJ
alkej-6	3	8	network	network	NOUN
alkej-6	3	9	for	for	ADP
alkej-6	3	10	the	the	DET
alkej-6	3	11	estimating	estimating	NOUN
alkej-6	3	12	of	of	ADP
alkej-6	3	13	the	the	DET
alkej-6	3	14	direction	direction	NOUN
alkej-6	3	15	of	of	ADP
alkej-6	3	16	arrival	arrival	NOUN
alkej-6	3	17	(	(	PUNCT
alkej-6	3	18	doa	doa	PROPN
alkej-6	3	19	)	)	PUNCT
alkej-6	3	20	.	.	PUNCT
alkej-6	4	1	it	it	PRON
alkej-6	4	2	uses	use	VERB
alkej-6	4	3	an	an	DET
alkej-6	4	4	unsupervised	unsupervised	ADJ
alkej-6	4	5	adaptive	adaptive	ADJ
alkej-6	4	6	neural	neural	ADJ
alkej-6	4	7	network	network	NOUN
alkej-6	4	8	with	with	ADP
alkej-6	4	9	gha	gha	PROPN
alkej-6	4	10	algorithm	algorithm	NOUN
alkej-6	4	11	to	to	PART
alkej-6	4	12	extract	extract	VERB
alkej-6	4	13	the	the	DET
alkej-6	4	14	principal	principal	ADJ
alkej-6	4	15	components	component	NOUN
alkej-6	4	16	that	that	SCONJ
alkej-6	4	17	in	in	ADP
alkej-6	4	18	turn	turn	NOUN
alkej-6	4	19	,	,	PUNCT
alkej-6	4	20	are	be	AUX
alkej-6	4	21	used	use	VERB
alkej-6	4	22	by	by	ADP
alkej-6	4	23	capon	capon	NOUN
alkej-6	4	24	method	method	NOUN
alkej-6	4	25	to	to	PART
alkej-6	4	26	estimate	estimate	VERB
alkej-6	4	27	the	the	DET
alkej-6	4	28	doa	doa	NOUN
alkej-6	4	29	,	,	PUNCT
alkej-6	4	30	where	where	SCONJ
alkej-6	4	31	by	by	ADP
alkej-6	4	32	the	the	DET
alkej-6	4	33	pca	pca	PROPN
alkej-6	4	34	neural	neural	ADJ
alkej-6	4	35	network	network	NOUN
alkej-6	4	36	we	we	PRON
alkej-6	4	37	take	take	VERB
alkej-6	4	38	signal	signal	NOUN
alkej-6	4	39	subspace	subspace	NOUN
alkej-6	4	40	only	only	ADV
alkej-6	4	41	and	and	CCONJ
alkej-6	4	42	use	use	VERB
alkej-6	4	43	it	it	PRON
alkej-6	4	44	in	in	ADP
alkej-6	4	45	capon	capon	NOUN
alkej-6	4	46	(	(	PUNCT
alkej-6	4	47	i.e.	i.e.	X
alkej-6	4	48	we	we	PRON
alkej-6	4	49	will	will	AUX
alkej-6	4	50	ignore	ignore	VERB
alkej-6	4	51	the	the	DET
alkej-6	4	52	noise	noise	NOUN
alkej-6	4	53	subspace	subspace	NOUN
alkej-6	4	54	,	,	PUNCT
alkej-6	4	55	and	and	CCONJ
alkej-6	4	56	take	take	VERB
alkej-6	4	57	the	the	DET
alkej-6	4	58	signal	signal	NOUN
alkej-6	4	59	subspace	subspace	NOUN
alkej-6	4	60	only	only	ADV
alkej-6	4	61	)	)	PUNCT
alkej-6	4	62	.	.	PUNCT
alkej-6	5	1	keywords	keyword	NOUN
alkej-6	5	2	:	:	PUNCT
alkej-6	5	3	direction	direction	NOUN
alkej-6	5	4	of	of	ADP
alkej-6	5	5	arrival	arrival	NOUN
alkej-6	5	6	(	(	PUNCT
alkej-6	5	7	doa	doa	PROPN
alkej-6	5	8	)	)	PUNCT
alkej-6	5	9	,	,	PUNCT
alkej-6	5	10	generalized	generalize	VERB
alkej-6	5	11	hebbian	hebbian	ADJ
alkej-6	5	12	algorithm	algorithm	NOUN
alkej-6	5	13	(	(	PUNCT
alkej-6	5	14	gha	gha	PROPN
alkej-6	5	15	)	)	PUNCT
alkej-6	5	16	,	,	PUNCT
alkej-6	5	17	principal	principal	ADJ
alkej-6	5	18	component	component	NOUN
alkej-6	5	19	analysis	analysis	NOUN
alkej-6	5	20	(	(	PUNCT
alkej-6	5	21	pca	pca	NOUN
alkej-6	5	22	)	)	PUNCT
alkej-6	5	23	,	,	PUNCT
alkej-6	5	24	capon	capon	NOUN
alkej-6	5	25	.	.	PUNCT
alkej-6	6	1	1.introduction	1.introduction	NUM
alkej-6	6	2	estimating	estimate	VERB
alkej-6	6	3	the	the	DET
alkej-6	6	4	doa	doa	NOUN
alkej-6	6	5	of	of	ADP
alkej-6	6	6	the	the	DET
alkej-6	6	7	source	source	NOUN
alkej-6	6	8	is	be	AUX
alkej-6	6	9	a	a	DET
alkej-6	6	10	central	central	ADJ
alkej-6	6	11	problem	problem	NOUN
alkej-6	6	12	in	in	ADP
alkej-6	6	13	the	the	DET
alkej-6	6	14	array	array	NOUN
alkej-6	6	15	signal	signal	NOUN
alkej-6	6	16	processing	processing	NOUN
alkej-6	6	17	.	.	PUNCT
alkej-6	7	1	many	many	ADJ
alkej-6	7	2	methods	method	NOUN
alkej-6	7	3	for	for	ADP
alkej-6	7	4	estimation	estimation	NOUN
alkej-6	7	5	the	the	DET
alkej-6	7	6	doa	doa	NOUN
alkej-6	7	7	have	have	AUX
alkej-6	7	8	been	be	AUX
alkej-6	7	9	proposed	propose	VERB
alkej-6	7	10	,	,	PUNCT
alkej-6	7	11	including	include	VERB
alkej-6	7	12	the	the	DET
alkej-6	7	13	maximum	maximum	ADJ
alkej-6	7	14	likelihood	likelihood	NOUN
alkej-6	7	15	(	(	PUNCT
alkej-6	7	16	ml	ml	NOUN
alkej-6	7	17	)	)	PUNCT
alkej-6	7	18	technique	technique	NOUN
alkej-6	7	19	[	[	X
alkej-6	7	20	1	1	NUM
alkej-6	7	21	]	]	PUNCT
alkej-6	7	22	,	,	PUNCT
alkej-6	7	23	the	the	DET
alkej-6	7	24	minimum	minimum	ADJ
alkej-6	7	25	variance	variance	NOUN
alkej-6	7	26	method	method	NOUN
alkej-6	7	27	of	of	ADP
alkej-6	7	28	capon	capon	NOUN
alkej-6	7	29	[	[	X
alkej-6	7	30	2	2	NUM
alkej-6	7	31	]	]	PUNCT
alkej-6	7	32	,	,	PUNCT
alkej-6	7	33	and	and	CCONJ
alkej-6	7	34	the	the	DET
alkej-6	7	35	music	music	NOUN
alkej-6	7	36	method	method	NOUN
alkej-6	7	37	of	of	ADP
alkej-6	7	38	schmidt	schmidt	NOUN
alkej-6	7	39	[	[	X
alkej-6	7	40	9	9	NUM
alkej-6	7	41	]	]	PUNCT
alkej-6	7	42	.	.	PUNCT
alkej-6	8	1	the	the	DET
alkej-6	8	2	ml	ml	PROPN
alkej-6	8	3	method	method	NOUN
alkej-6	8	4	has	have	VERB
alkej-6	8	5	the	the	DET
alkej-6	8	6	best	good	ADJ
alkej-6	8	7	performance	performance	NOUN
alkej-6	8	8	.	.	PUNCT
alkej-6	9	1	because	because	SCONJ
alkej-6	9	2	of	of	ADP
alkej-6	9	3	high	high	ADJ
alkej-6	9	4	computational	computational	ADJ
alkej-6	9	5	load	load	NOUN
alkej-6	9	6	of	of	ADP
alkej-6	9	7	the	the	DET
alkej-6	9	8	multivariate	multivariate	NOUN
alkej-6	9	9	nonlinear	nonlinear	PROPN
alkej-6	9	10	maximization	maximization	NOUN
alkej-6	9	11	problem	problem	NOUN
alkej-6	9	12	involved	involve	VERB
alkej-6	9	13	,	,	PUNCT
alkej-6	9	14	the	the	DET
alkej-6	9	15	ml	ml	X
alkej-6	9	16	technique	technique	NOUN
alkej-6	9	17	did	do	AUX
alkej-6	9	18	not	not	PART
alkej-6	9	19	becomes	become	VERB
alkej-6	9	20	popular	popular	ADJ
alkej-6	9	21	.	.	PUNCT
alkej-6	10	1	suboptimal	suboptimal	ADJ
alkej-6	10	2	methods	method	NOUN
alkej-6	10	3	are	be	AUX
alkej-6	10	4	more	more	ADV
alkej-6	10	5	prevalent	prevalent	ADJ
alkej-6	10	6	than	than	ADP
alkej-6	10	7	the	the	DET
alkej-6	10	8	ml	ml	NOUN
alkej-6	10	9	technique	technique	NOUN
alkej-6	10	10	when	when	SCONJ
alkej-6	10	11	the	the	DET
alkej-6	10	12	signal_to_noise	signal_to_noise	PROPN
alkej-6	10	13	ratio	ratio	NOUN
alkej-6	10	14	and	and	CCONJ
alkej-6	10	15	number	number	NOUN
alkej-6	10	16	of	of	ADP
alkej-6	10	17	samples	sample	NOUN
alkej-6	10	18	are	be	AUX
alkej-6	10	19	both	both	PRON
alkej-6	10	20	not	not	PART
alkej-6	10	21	too	too	ADV
alkej-6	10	22	small	small	ADJ
alkej-6	10	23	,	,	PUNCT
alkej-6	10	24	because	because	SCONJ
alkej-6	10	25	the	the	DET
alkej-6	10	26	suboptimal	suboptimal	ADJ
alkej-6	10	27	methods	method	NOUN
alkej-6	10	28	involve	involve	VERB
alkej-6	10	29	solving	solve	VERB
alkej-6	10	30	only	only	ADV
alkej-6	10	31	a	a	DET
alkej-6	10	32	one	one	NUM
alkej-6	10	33	-	-	PUNCT
alkej-6	10	34	dimensional	dimensional	ADJ
alkej-6	10	35	maximization	maximization	NOUN
alkej-6	10	36	problem	problem	NOUN
alkej-6	10	37	and	and	CCONJ
alkej-6	10	38	subspace	subspace	NOUN
alkej-6	10	39	(	(	PUNCT
alkej-6	10	40	signal	signal	VERB
alkej-6	10	41	subspace	subspace	NOUN
alkej-6	10	42	or	or	CCONJ
alkej-6	10	43	noise	noise	NOUN
alkej-6	10	44	subspace	subspace	NOUN
alkej-6	10	45	)	)	PUNCT
alkej-6	10	46	.	.	PUNCT
alkej-6	11	1	this	this	DET
alkej-6	11	2	paper	paper	NOUN
alkej-6	11	3	uses	use	VERB
alkej-6	11	4	adaptive	adaptive	ADJ
alkej-6	11	5	algorithm	algorithm	NOUN
alkej-6	11	6	for	for	ADP
alkej-6	11	7	extracting	extract	VERB
alkej-6	11	8	the	the	DET
alkej-6	11	9	subspace	subspace	NOUN
alkej-6	11	10	information	information	NOUN
alkej-6	11	11	based	base	VERB
alkej-6	11	12	on	on	ADP
alkej-6	11	13	the	the	DET
alkej-6	11	14	pca	pca	PROPN
alkej-6	11	15	neural	neural	ADJ
alkej-6	11	16	network	network	NOUN
alkej-6	11	17	.	.	PUNCT
alkej-6	12	1	where	where	SCONJ
alkej-6	12	2	we	we	PRON
alkej-6	12	3	extract	extract	VERB
alkej-6	12	4	the	the	DET
alkej-6	12	5	principal	principal	ADJ
alkej-6	12	6	component	component	NOUN
alkej-6	12	7	(	(	PUNCT
alkej-6	12	8	i.e.	i.e.	X
alkej-6	12	9	the	the	DET
alkej-6	12	10	signal	signal	ADJ
alkej-6	12	11	subspace	subspace	NOUN
alkej-6	12	12	only	only	ADV
alkej-6	12	13	)	)	PUNCT
alkej-6	12	14	by	by	ADP
alkej-6	12	15	using	use	VERB
alkej-6	12	16	of	of	ADP
alkej-6	12	17	gha	gha	NOUN
alkej-6	12	18	algorithm	algorithm	NOUN
alkej-6	12	19	with	with	ADP
alkej-6	12	20	adaptive	adaptive	ADJ
alkej-6	12	21	learning	learning	NOUN
alkej-6	12	22	rate	rate	NOUN
alkej-6	12	23	,	,	PUNCT
alkej-6	12	24	which	which	PRON
alkej-6	12	25	then	then	ADV
alkej-6	12	26	used	use	VERB
alkej-6	12	27	by	by	ADP
alkej-6	12	28	a	a	DET
alkej-6	12	29	capon	capon	NOUN
alkej-6	12	30	to	to	PART
alkej-6	12	31	find	find	VERB
alkej-6	12	32	the	the	DET
alkej-6	12	33	doa	doa	NOUN
alkej-6	12	34	.	.	PUNCT
alkej-6	13	1	the	the	DET
alkej-6	13	2	mapping	mapping	NOUN
alkej-6	13	3	of	of	ADP
alkej-6	13	4	this	this	DET
alkej-6	13	5	paper	paper	NOUN
alkej-6	13	6	is	be	AUX
alkej-6	13	7	as	as	SCONJ
alkej-6	13	8	follows	follow	VERB
alkej-6	13	9	:	:	PUNCT
alkej-6	13	10	section	section	NOUN
alkej-6	13	11	two	two	NUM
alkej-6	13	12	provides	provide	VERB
alkej-6	13	13	some	some	DET
alkej-6	13	14	background	background	NOUN
alkej-6	13	15	information	information	NOUN
alkej-6	13	16	.	.	PUNCT
alkej-6	14	1	where	where	SCONJ
alkej-6	14	2	the	the	DET
alkej-6	14	3	data	data	NOUN
alkej-6	14	4	model	model	NOUN
alkej-6	14	5	and	and	CCONJ
alkej-6	14	6	the	the	DET
alkej-6	14	7	subspaces	subspace	NOUN
alkej-6	14	8	are	be	AUX
alkej-6	14	9	present	present	ADJ
alkej-6	14	10	.	.	PUNCT
alkej-6	15	1	in	in	ADP
alkej-6	15	2	section	section	NOUN
alkej-6	15	3	three	three	NUM
alkej-6	15	4	an	an	DET
alkej-6	15	5	expression	expression	NOUN
alkej-6	15	6	for	for	ADP
alkej-6	15	7	the	the	DET
alkej-6	15	8	capon	capon	NOUN
alkej-6	15	9	method	method	NOUN
alkej-6	15	10	is	be	AUX
alkej-6	15	11	presented	present	VERB
alkej-6	15	12	.	.	PUNCT
alkej-6	16	1	in	in	ADP
alkej-6	16	2	section	section	NOUN
alkej-6	16	3	four	four	NUM
alkej-6	16	4	an	an	DET
alkej-6	16	5	expression	expression	NOUN
alkej-6	16	6	for	for	ADP
alkej-6	16	7	neural	neural	ADJ
alkej-6	16	8	estimator	estimator	NOUN
alkej-6	16	9	is	be	AUX
alkej-6	16	10	presented	present	VERB
alkej-6	16	11	.	.	PUNCT
alkej-6	17	1	in	in	ADP
alkej-6	17	2	section	section	NOUN
alkej-6	17	3	five	five	NUM
alkej-6	17	4	a	a	DET
alkej-6	17	5	computer	computer	NOUN
alkej-6	17	6	simulation	simulation	NOUN
alkej-6	17	7	using	use	VERB
alkej-6	17	8	matlab	matlab	PROPN
alkej-6	17	9	6.0	6.0	NUM
alkej-6	17	10	is	be	AUX
alkej-6	17	11	provided	provide	VERB
alkej-6	17	12	to	to	PART
alkej-6	17	13	support	support	VERB
alkej-6	17	14	the	the	DET
alkej-6	17	15	theoretical	theoretical	ADJ
alkej-6	17	16	observations	observation	NOUN
alkej-6	17	17	.	.	PUNCT
alkej-6	18	1	2.general	2.general	NUM
alkej-6	18	2	consideration	consideration	NOUN
alkej-6	18	3	assume	assume	VERB
alkej-6	18	4	that	that	SCONJ
alkej-6	18	5	plane	plane	NOUN
alkej-6	18	6	waves	wave	NOUN
alkej-6	18	7	emitted	emit	VERB
alkej-6	18	8	by	by	ADP
alkej-6	18	9	d1	d1	PROPN
alkej-6	18	10	narrow	narrow	ADJ
alkej-6	18	11	band	band	NOUN
alkej-6	18	12	sources	source	NOUN
alkej-6	18	13	impinged	impinge	VERB
alkej-6	18	14	on	on	ADP
alkej-6	18	15	a	a	DET
alkej-6	18	16	uniform	uniform	ADJ
alkej-6	18	17	circular	circular	ADJ
alkej-6	18	18	array	array	NOUN
alkej-6	18	19	(	(	PUNCT
alkej-6	18	20	uca	uca	NOUN
alkej-6	18	21	)	)	PUNCT
alkej-6	18	22	consisting	consist	VERB
alkej-6	18	23	of	of	ADP
alkej-6	18	24	n.	n.	PROPN
alkej-6	18	25	h.	h.	PROPN
alkej-6	18	26	abbas	abbas	PROPN
alkej-6	18	27	/al	/al	PROPN
alkej-6	18	28	-	-	PUNCT
alkej-6	18	29	khwarizmi	khwarizmi	PROPN
alkej-6	18	30	engineering	engineering	NOUN
alkej-6	18	31	journal	journal	NOUN
alkej-6	18	32	,	,	PUNCT
alkej-6	18	33	vol.2	vol.2	PROPN
alkej-6	18	34	,	,	PUNCT
alkej-6	18	35	no	no	INTJ
alkej-6	18	36	.	.	PUNCT
alkej-6	19	1	1,pp	1,pp	NUM
alkej-6	19	2	70	70	NUM
alkej-6	19	3	-	-	SYM
alkej-6	19	4	77	77	NUM
alkej-6	19	5	(	(	PUNCT
alkej-6	19	6	2006	2006	NUM
alkej-6	19	7	)	)	PUNCT
alkej-6	19	8	71	71	NUM
alkej-6	19	9	m	m	NOUN
alkej-6	19	10	sensors	sensor	NOUN
alkej-6	19	11	,	,	PUNCT
alkej-6	19	12	and	and	CCONJ
alkej-6	19	13	the	the	DET
alkej-6	19	14	doas	doas	NOUN
alkej-6	19	15	of	of	ADP
alkej-6	19	16	these	these	DET
alkej-6	19	17	sources	source	NOUN
alkej-6	19	18	(	(	PUNCT
alkej-6	19	19	the	the	DET
alkej-6	19	20	azimuth	azimuth	PROPN
alkej-6	19	21	angle	angle	NOUN
alkej-6	19	22	is	be	AUX
alkej-6	19	23	measured	measure	VERB
alkej-6	19	24	with	with	ADP
alkej-6	19	25	respect	respect	NOUN
alkej-6	19	26	to	to	ADP
alkej-6	19	27	reference	reference	NOUN
alkej-6	19	28	sensor	sensor	NOUN
alkej-6	19	29	,	,	PUNCT
alkej-6	19	30	and	and	CCONJ
alkej-6	19	31	elevation	elevation	NOUN
alkej-6	19	32	is	be	AUX
alkej-6	19	33	measured	measure	VERB
alkej-6	19	34	with	with	ADP
alkej-6	19	35	respect	respect	NOUN
alkej-6	19	36	to	to	ADP
alkej-6	19	37	z	z	NOUN
alkej-6	19	38	-	-	PUNCT
alkej-6	19	39	axis	axis	NOUN
alkej-6	19	40	as	as	SCONJ
alkej-6	19	41	shown	show	VERB
alkej-6	19	42	in	in	ADP
alkej-6	19	43	figure	figure	NOUN
alkej-6	19	44	(	(	PUNCT
alkej-6	19	45	1	1	NUM
alkej-6	19	46	)	)	PUNCT
alkej-6	19	47	are	be	AUX
alkej-6	19	48	[	[	X
alkej-6	19	49	(	(	PUNCT
alkej-6	19	50	θ1	θ1	NOUN
alkej-6	19	51	,	,	PUNCT
alkej-6	19	52	φ1	φ1	PROPN
alkej-6	19	53	)	)	PUNCT
alkej-6	19	54	,	,	PUNCT
alkej-6	19	55	(	(	PUNCT
alkej-6	19	56	θ2	θ2	PROPN
alkej-6	19	57	,	,	PUNCT
alkej-6	19	58	φ2	φ2	PROPN
alkej-6	19	59	)	)	PUNCT
alkej-6	19	60	,	,	PUNCT
alkej-6	19	61	…	…	PUNCT
alkej-6	19	62	,	,	PUNCT
alkej-6	19	63	(	(	PUNCT
alkej-6	19	64	θd	θd	NOUN
alkej-6	19	65	,	,	PUNCT
alkej-6	19	66	φd)].the	φd)].the	DET
alkej-6	19	67	array	array	NOUN
alkej-6	19	68	output	output	NOUN
alkej-6	19	69	vector	vector	NOUN
alkej-6	19	70	at	at	ADP
alkej-6	19	71	the	the	DET
alkej-6	19	72	k_th	k_th	PROPN
alkej-6	19	73	snapshot	snapshot	NOUN
alkej-6	19	74	can	can	AUX
alkej-6	19	75	then	then	ADV
alkej-6	19	76	be	be	AUX
alkej-6	19	77	expressed	express	VERB
alkej-6	19	78	as	as	ADP
alkej-6	19	79	x(k	x(k	NOUN
alkej-6	19	80	)	)	PUNCT
alkej-6	19	81	=	=	SYM
alkej-6	19	82	as(k)+n(k	as(k)+n(k	NOUN
alkej-6	19	83	)	)	PUNCT
alkej-6	19	84	(	(	PUNCT
alkej-6	19	85	1	1	X
alkej-6	19	86	)	)	PUNCT
alkej-6	19	87	where	where	SCONJ
alkej-6	19	88	s(k	s(k	ADV
alkej-6	19	89	)	)	PUNCT
alkej-6	19	90	is	be	AUX
alkej-6	19	91	the	the	DET
alkej-6	19	92	d×1	d×1	PROPN
alkej-6	19	93	vector	vector	NOUN
alkej-6	19	94	of	of	ADP
alkej-6	19	95	incident	incident	NOUN
alkej-6	19	96	signals	signal	NOUN
alkej-6	19	97	which	which	PRON
alkej-6	19	98	are	be	AUX
alkej-6	19	99	assumed	assume	VERB
alkej-6	19	100	to	to	PART
alkej-6	19	101	be	be	AUX
alkej-6	19	102	zero	zero	NUM
alkej-6	19	103	mean	mean	NOUN
alkej-6	19	104	stationary	stationary	ADJ
alkej-6	19	105	,	,	PUNCT
alkej-6	19	106	complex	complex	ADJ
alkej-6	19	107	and	and	CCONJ
alkej-6	19	108	gaussian	gaussian	ADJ
alkej-6	19	109	random	random	ADJ
alkej-6	19	110	processes	process	NOUN
alkej-6	19	111	n(k	n(k	PROPN
alkej-6	19	112	)	)	PUNCT
alkej-6	19	113	is	be	AUX
alkej-6	19	114	m×1	m×1	NOUN
alkej-6	19	115	vector	vector	NOUN
alkej-6	19	116	of	of	ADP
alkej-6	19	117	additive	additive	ADJ
alkej-6	19	118	noises	noise	NOUN
alkej-6	19	119	which	which	PRON
alkej-6	19	120	assumed	assume	VERB
alkej-6	19	121	to	to	PART
alkej-6	19	122	be	be	AUX
alkej-6	19	123	zero	zero	NUM
alkej-6	19	124	mean	mean	NOUN
alkej-6	19	125	random	random	ADJ
alkej-6	19	126	processes	process	NOUN
alkej-6	19	127	that	that	PRON
alkej-6	19	128	are	be	AUX
alkej-6	19	129	uncorrelated	uncorrelate	VERB
alkej-6	19	130	with	with	ADP
alkej-6	19	131	each	each	DET
alkej-6	19	132	other	other	ADJ
alkej-6	19	133	and	and	CCONJ
alkej-6	19	134	with	with	ADP
alkej-6	19	135	the	the	DET
alkej-6	19	136	signals	signal	NOUN
alkej-6	19	137	,	,	PUNCT
alkej-6	19	138	and	and	CCONJ
alkej-6	19	139	a	a	PRON
alkej-6	19	140	is	be	AUX
alkej-6	19	141	the	the	DET
alkej-6	19	142	steering	steering	NOUN
alkej-6	19	143	(	(	PUNCT
alkej-6	19	144	or	or	CCONJ
alkej-6	19	145	direction	direction	NOUN
alkej-6	19	146	)	)	PUNCT
alkej-6	19	147	matrix	matrix	NOUN
alkej-6	19	148	given	give	VERB
alkej-6	19	149	by	by	ADP
alkej-6	19	150	a=	a=	PROPN
alkej-6	19	151	[	[	X
alkej-6	19	152	a(θ1,φ1	a(θ1,φ1	NOUN
alkej-6	19	153	)	)	PUNCT
alkej-6	19	154	,	,	PUNCT
alkej-6	19	155	a(θ2,φ2	a(θ2,φ2	NOUN
alkej-6	19	156	)	)	PUNCT
alkej-6	19	157	,	,	PUNCT
alkej-6	19	158	.	.	PUNCT
alkej-6	19	159	.	.	PUNCT
alkej-6	19	160	.	.	PUNCT
alkej-6	20	1	a(θd	a(θd	NOUN
alkej-6	20	2	,	,	PUNCT
alkej-6	20	3	φd)].the	φd)].the	DET
alkej-6	20	4	steering	steering	NOUN
alkej-6	20	5	vector	vector	NOUN
alkej-6	20	6	corresponding	correspond	VERB
alkej-6	20	7	to	to	ADP
alkej-6	20	8	the	the	DET
alkej-6	20	9	i_th	i_th	PROPN
alkej-6	20	10	doa(θ	doa(θ	PROPN
alkej-6	20	11	,	,	PUNCT
alkej-6	20	12	φ	φ	NUM
alkej-6	20	13	)	)	PUNCT
alkej-6	20	14	is	be	AUX
alkej-6	20	15	given	give	VERB
alkej-6	20	16	by	by	ADP
alkej-6	20	17	a(θi	a(θi	NOUN
alkej-6	20	18	,	,	PUNCT
alkej-6	20	19	φi)=	φi)=	NUM
alkej-6	20	20	[	[	PUNCT
alkej-6	20	21	a1(θ1,φ1)e	a1(θ1,φ1)e	PROPN
alkej-6	20	22	-j*w	-j*w	PROPN
alkej-6	20	23	0	0	PUNCT
alkej-6	20	24	*	*	PUNCT
alkej-6	20	25	τ1(θi	τ1(θi	NUM
alkej-6	20	26	,	,	PUNCT
alkej-6	20	27	φi	φi	NOUN
alkej-6	20	28	)	)	PUNCT
alkej-6	20	29	,	,	PUNCT
alkej-6	20	30	.	.	PUNCT
alkej-6	20	31	.	.	PUNCT
alkej-6	21	1	.	.	PUNCT
alkej-6	21	2	,	,	PUNCT
alkej-6	21	3	am(θd	am(θd	PROPN
alkej-6	21	4	,	,	PUNCT
alkej-6	21	5	φd	φd	X
alkej-6	21	6	)	)	PUNCT
alkej-6	21	7	e	e	NOUN
alkej-6	21	8	-	-	NOUN
alkej-6	21	9	j*w	j*w	NOUN
alkej-6	21	10	0	0	PUNCT
alkej-6	21	11	*	*	PUNCT
alkej-6	21	12	τm(θi	τm(θi	PROPN
alkej-6	21	13	,	,	PUNCT
alkej-6	21	14	φi	φi	NOUN
alkej-6	21	15	)	)	PUNCT
alkej-6	21	16	]	]	PUNCT
alkej-6	22	1	(	(	PUNCT
alkej-6	22	2	2	2	X
alkej-6	22	3	)	)	PUNCT
alkej-6	22	4	where	where	SCONJ
alkej-6	22	5	am	be	AUX
alkej-6	22	6	(	(	PUNCT
alkej-6	22	7	θi	θi	X
alkej-6	22	8	,	,	PUNCT
alkej-6	22	9	φi	φi	ADJ
alkej-6	22	10	)	)	PUNCT
alkej-6	22	11	denotes	denote	VERB
alkej-6	22	12	the	the	DET
alkej-6	22	13	complex	complex	ADJ
alkej-6	22	14	gain	gain	NOUN
alkej-6	22	15	response	response	NOUN
alkej-6	22	16	of	of	ADP
alkej-6	22	17	m_th	m_th	PROPN
alkej-6	22	18	sensor	sensor	NOUN
alkej-6	22	19	to	to	ADP
alkej-6	22	20	a	a	DET
alkej-6	22	21	wave	wave	NOUN
alkej-6	22	22	front	front	NOUN
alkej-6	22	23	arriving	arrive	VERB
alkej-6	22	24	from	from	ADP
alkej-6	22	25	direction	direction	NOUN
alkej-6	22	26	(	(	PUNCT
alkej-6	22	27	θi	θi	X
alkej-6	22	28	,	,	PUNCT
alkej-6	22	29	φi),w0	φi),w0	PROPN
alkej-6	22	30	denotes	denote	VERB
alkej-6	22	31	the	the	DET
alkej-6	22	32	center	center	NOUN
alkej-6	22	33	frequency	frequency	NOUN
alkej-6	22	34	of	of	ADP
alkej-6	22	35	the	the	DET
alkej-6	22	36	signals	signal	NOUN
alkej-6	22	37	,	,	PUNCT
alkej-6	22	38	and	and	CCONJ
alkej-6	22	39	τm(θi	τm(θi	PROPN
alkej-6	22	40	,	,	PUNCT
alkej-6	22	41	φi	φi	NOUN
alkej-6	22	42	)	)	PUNCT
alkej-6	22	43	denote	denote	VERB
alkej-6	22	44	the	the	DET
alkej-6	22	45	propagation	propagation	NOUN
alkej-6	22	46	delay	delay	NOUN
alkej-6	22	47	between	between	ADP
alkej-6	22	48	the	the	DET
alkej-6	22	49	sensors	sensor	NOUN
alkej-6	22	50	for	for	ADP
alkej-6	22	51	a	a	DET
alkej-6	22	52	wave	wave	NOUN
alkej-6	22	53	front	front	NOUN
alkej-6	22	54	impinging	impinge	VERB
alkej-6	22	55	from	from	ADP
alkej-6	22	56	direction	direction	NOUN
alkej-6	22	57	(	(	PUNCT
alkej-6	22	58	θi	θi	X
alkej-6	22	59	,	,	PUNCT
alkej-6	22	60	φi	φi	NOUN
alkej-6	22	61	)	)	PUNCT
alkej-6	22	62	which	which	PRON
alkej-6	22	63	is	be	AUX
alkej-6	22	64	given	give	VERB
alkej-6	22	65	by	by	ADP
alkej-6	22	66	τi	τi	NOUN
alkej-6	22	67	=	=	NOUN
alkej-6	22	68	j2πr	j2πr	NOUN
alkej-6	22	69	/	/	SYM
alkej-6	22	70	λsin	λsin	NOUN
alkej-6	22	71	(	(	PUNCT
alkej-6	22	72	φi)cos	φi)co	NOUN
alkej-6	22	73	(	(	PUNCT
alkej-6	22	74	2πm	2πm	ADJ
alkej-6	22	75	/	/	SYM
alkej-6	22	76	mθi	mθi	NOUN
alkej-6	22	77	)	)	PUNCT
alkej-6	22	78	(	(	PUNCT
alkej-6	22	79	3	3	X
alkej-6	22	80	)	)	PUNCT
alkej-6	22	81	where	where	SCONJ
alkej-6	22	82	r	r	NOUN
alkej-6	22	83	is	be	AUX
alkej-6	22	84	the	the	DET
alkej-6	22	85	radius	radius	NOUN
alkej-6	22	86	of	of	ADP
alkej-6	22	87	the	the	DET
alkej-6	22	88	circular	circular	ADJ
alkej-6	22	89	array	array	NOUN
alkej-6	22	90	,	,	PUNCT
alkej-6	22	91	and	and	CCONJ
alkej-6	22	92	λ	λ	PROPN
alkej-6	22	93	is	be	AUX
alkej-6	22	94	the	the	DET
alkej-6	22	95	wavelength	wavelength	NOUN
alkej-6	22	96	.	.	PUNCT
alkej-6	23	1	the	the	DET
alkej-6	23	2	covariance	covariance	NOUN
alkej-6	23	3	matrix	matrix	NOUN
alkej-6	23	4	of	of	ADP
alkej-6	23	5	the	the	DET
alkej-6	23	6	array	array	NOUN
alkej-6	23	7	signal	signal	NOUN
alkej-6	23	8	vector	vector	NOUN
alkej-6	23	9	is	be	AUX
alkej-6	23	10	given	give	VERB
alkej-6	23	11	by	by	ADP
alkej-6	23	12	r	r	NOUN
alkej-6	23	13	=	=	SYM
alkej-6	23	14	e[x(k)x(k	e[x(k)x(k	PROPN
alkej-6	23	15	)	)	PUNCT
alkej-6	23	16	h	h	NOUN
alkej-6	23	17	]	]	X
alkej-6	23	18	=	=	X
alkej-6	23	19	asah	asah	ADP
alkej-6	23	20	+	+	NOUN
alkej-6	23	21	ỏn	ỏn	PROPN
alkej-6	23	22	2	2	NUM
alkej-6	23	23	i	i	NOUN
alkej-6	23	24	=	=	AUX
alkej-6	23	25	rs	rs	X
alkej-6	24	1	+	+	PROPN
alkej-6	24	2	rn	rn	PROPN
alkej-6	24	3	(	(	PUNCT
alkej-6	24	4	4	4	NUM
alkej-6	24	5	)	)	PUNCT
alkej-6	24	6	where	where	SCONJ
alkej-6	24	7	the	the	DET
alkej-6	24	8	superscript	superscript	PROPN
alkej-6	24	9	"	"	PUNCT
alkej-6	24	10	h	h	NOUN
alkej-6	24	11	"	"	PUNCT
alkej-6	24	12	denote	denote	VERB
alkej-6	24	13	the	the	DET
alkej-6	24	14	conjugate	conjugate	ADJ
alkej-6	24	15	transpose	transpose	NOUN
alkej-6	24	16	.s	.s	NOUN
alkej-6	25	1	=	=	SYM
alkej-6	25	2	e[s	e[s	X
alkej-6	25	3	(	(	PUNCT
alkej-6	25	4	k	k	NOUN
alkej-6	25	5	)	)	PUNCT
alkej-6	25	6	×s	×s	ADV
alkej-6	25	7	(	(	PUNCT
alkej-6	25	8	k	k	X
alkej-6	25	9	)	)	PUNCT
alkej-6	25	10	h	h	NOUN
alkej-6	25	11	]	]	PUNCT
alkej-6	25	12	and	and	CCONJ
alkej-6	25	13	ỏn	ỏn	NUM
alkej-6	25	14	2	2	NUM
alkej-6	25	15	is	be	AUX
alkej-6	25	16	the	the	DET
alkej-6	25	17	variance	variance	NOUN
alkej-6	25	18	of	of	ADP
alkej-6	25	19	the	the	DET
alkej-6	25	20	additive	additive	ADJ
alkej-6	25	21	noise	noise	NOUN
alkej-6	25	22	,	,	PUNCT
alkej-6	25	23	let	let	VERB
alkej-6	25	24	λ1≥	λ1≥	X
alkej-6	25	25	λ2≥	λ2≥	X
alkej-6	25	26	.	.	PUNCT
alkej-6	25	27	.	.	PUNCT
alkej-6	25	28	.	.	PUNCT
alkej-6	26	1	λd≥	λd≥	PROPN
alkej-6	26	2	λd+1=	λd+1=	PROPN
alkej-6	26	3	.	.	PUNCT
alkej-6	26	4	.	.	PUNCT
alkej-6	26	5	.	.	PUNCT
alkej-6	27	1	λm=	λm=	PROPN
alkej-6	27	2	ỏn	ỏn	ADP
alkej-6	27	3	2	2	NUM
alkej-6	27	4	,	,	PUNCT
alkej-6	27	5	denote	denote	VERB
alkej-6	27	6	the	the	DET
alkej-6	27	7	eigenvalues	eigenvalue	NOUN
alkej-6	27	8	of	of	ADP
alkej-6	27	9	r	r	NOUN
alkej-6	27	10	and	and	CCONJ
alkej-6	27	11	e1	e1	PROPN
alkej-6	27	12	,	,	PUNCT
alkej-6	27	13	e2	e2	PROPN
alkej-6	27	14	.	.	PUNCT
alkej-6	27	15	.	.	PUNCT
alkej-6	28	1	.em	.em	PUNCT
alkej-6	29	1	denotes	denote	VERB
alkej-6	29	2	the	the	DET
alkej-6	29	3	corresponding	corresponding	ADJ
alkej-6	29	4	eigenvectors	eigenvector	NOUN
alkej-6	29	5	.	.	PUNCT
alkej-6	30	1	if	if	SCONJ
alkej-6	30	2	the	the	DET
alkej-6	30	3	matrices	matrix	NOUN
alkej-6	30	4	es	es	VERB
alkej-6	30	5	and	and	CCONJ
alkej-6	30	6	en	en	PROPN
alkej-6	30	7	are	be	AUX
alkej-6	30	8	formed	form	VERB
alkej-6	30	9	as	as	ADP
alkej-6	30	10	es=	es=	PROPN
alkej-6	30	11	[	[	X
alkej-6	30	12	e1	e1	PROPN
alkej-6	30	13	,	,	PUNCT
alkej-6	30	14	e2	e2	PROPN
alkej-6	30	15	,	,	PUNCT
alkej-6	30	16	.	.	PUNCT
alkej-6	30	17	.	.	PUNCT
alkej-6	31	1	.	.	PUNCT
alkej-6	32	1	,	,	PUNCT
alkej-6	32	2	ed	ed	NOUN
alkej-6	32	3	]	]	X
alkej-6	32	4	(	(	PUNCT
alkej-6	32	5	5	5	NUM
alkej-6	32	6	)	)	PUNCT
alkej-6	32	7	and	and	CCONJ
alkej-6	32	8	en=[ed+1	en=[ed+1	PROPN
alkej-6	32	9	,	,	PUNCT
alkej-6	32	10	ed+2	ed+2	NUM
alkej-6	32	11	.	.	PUNCT
alkej-6	32	12	.	.	PUNCT
alkej-6	33	1	.em	.em	PUNCT
alkej-6	33	2	]	]	PUNCT
alkej-6	34	1	(	(	PUNCT
alkej-6	34	2	6	6	NUM
alkej-6	34	3	)	)	PUNCT
alkej-6	34	4	then	then	ADV
alkej-6	34	5	the	the	DET
alkej-6	34	6	linear	linear	ADJ
alkej-6	34	7	span	span	NOUN
alkej-6	34	8	of	of	ADP
alkej-6	34	9	es	es	NOUN
alkej-6	34	10	,	,	PUNCT
alkej-6	34	11	known	know	VERB
alkej-6	34	12	as	as	ADP
alkej-6	34	13	the	the	DET
alkej-6	34	14	signal	signal	ADJ
alkej-6	34	15	space	space	NOUN
alkej-6	34	16	,	,	PUNCT
alkej-6	34	17	is	be	AUX
alkej-6	34	18	same	same	ADJ
alkej-6	34	19	as	as	SCONJ
alkej-6	34	20	spanned	span	VERB
alkej-6	34	21	by	by	ADP
alkej-6	34	22	the	the	DET
alkej-6	34	23	columns	column	NOUN
alkej-6	34	24	of	of	ADP
alkej-6	34	25	a.	a.	NOUN
alkej-6	34	26	the	the	DET
alkej-6	34	27	linear	linear	ADJ
alkej-6	34	28	span	span	NOUN
alkej-6	34	29	of	of	ADP
alkej-6	34	30	en	en	X
alkej-6	34	31	,	,	PUNCT
alkej-6	34	32	known	know	VERB
alkej-6	34	33	as	as	ADP
alkej-6	34	34	the	the	DET
alkej-6	34	35	noise	noise	NOUN
alkej-6	34	36	subspace	subspace	NOUN
alkej-6	34	37	,	,	PUNCT
alkej-6	34	38	is	be	AUX
alkej-6	34	39	the	the	DET
alkej-6	34	40	orthogonal	orthogonal	ADJ
alkej-6	34	41	component	component	NOUN
alkej-6	34	42	of	of	ADP
alkej-6	34	43	the	the	DET
alkej-6	34	44	signal	signal	NOUN
alkej-6	34	45	subspace	subspace	NOUN
alkej-6	34	46	,	,	PUNCT
alkej-6	34	47	then	then	ADV
alkej-6	34	48	en	en	ADP
alkej-6	34	49	h×a(θk	h×a(θk	PROPN
alkej-6	34	50	,	,	PUNCT
alkej-6	34	51	φk)=0	φk)=0	ADV
alkej-6	34	52	,	,	PUNCT
alkej-6	34	53	k=1,2	k=1,2	PROPN
alkej-6	34	54	,	,	PUNCT
alkej-6	34	55	.	.	PUNCT
alkej-6	34	56	.	.	PUNCT
alkej-6	35	1	.,d	.,d	PUNCT
alkej-6	35	2	.	.	PUNCT
alkej-6	36	1	3.the	3.the	DET
alkej-6	36	2	capon	capon	NOUN
alkej-6	36	3	method	method	NOUN
alkej-6	36	4	the	the	DET
alkej-6	36	5	capon	capon	NOUN
alkej-6	36	6	method	method	NOUN
alkej-6	36	7	tries	try	VERB
alkej-6	36	8	to	to	PART
alkej-6	36	9	optimize	optimize	VERB
alkej-6	36	10	the	the	DET
alkej-6	36	11	beamforming	beamforming	NOUN
alkej-6	36	12	process	process	NOUN
alkej-6	36	13	according	accord	VERB
alkej-6	36	14	to	to	ADP
alkej-6	36	15	the	the	DET
alkej-6	36	16	time	time	NOUN
alkej-6	36	17	varying	vary	VERB
alkej-6	36	18	covariance	covariance	NOUN
alkej-6	36	19	matrix	matrix	NOUN
alkej-6	36	20	.the	.the	PUNCT
alkej-6	36	21	spectrum	spectrum	NOUN
alkej-6	36	22	is	be	AUX
alkej-6	36	23	given	give	VERB
alkej-6	36	24	by	by	ADP
alkej-6	36	25	pmv	pmv	PROPN
alkej-6	36	26	(	(	PUNCT
alkej-6	36	27	θ	θ	PROPN
alkej-6	36	28	,	,	PUNCT
alkej-6	36	29	φ	φ	NUM
alkej-6	36	30	)	)	PUNCT
alkej-6	37	1	=	=	NOUN
alkej-6	37	2	1/(ah	1/(ah	NUM
alkej-6	37	3	(	(	PUNCT
alkej-6	37	4	θ	θ	PROPN
alkej-6	37	5	,	,	PUNCT
alkej-6	37	6	φ)r-1	φ)r-1	VERB
alkej-6	37	7	a	a	DET
alkej-6	37	8	(	(	PUNCT
alkej-6	37	9	θ	θ	PROPN
alkej-6	37	10	,	,	PUNCT
alkej-6	37	11	φ	φ	NOUN
alkej-6	37	12	)	)	PUNCT
alkej-6	37	13	)	)	PUNCT
alkej-6	38	1	(	(	PUNCT
alkej-6	38	2	7	7	X
alkej-6	38	3	)	)	PUNCT
alkej-6	38	4	the	the	DET
alkej-6	38	5	method	method	NOUN
alkej-6	38	6	minimizes	minimize	VERB
alkej-6	38	7	the	the	DET
alkej-6	38	8	power	power	NOUN
alkej-6	38	9	contributed	contribute	VERB
alkej-6	38	10	by	by	ADP
alkej-6	38	11	the	the	DET
alkej-6	38	12	noise	noise	NOUN
alkej-6	38	13	and	and	CCONJ
alkej-6	38	14	signals	signal	NOUN
alkej-6	38	15	originating	originate	VERB
alkej-6	38	16	from	from	ADP
alkej-6	38	17	other	other	ADJ
alkej-6	38	18	direction	direction	NOUN
alkej-6	38	19	the	the	DET
alkej-6	38	20	current	current	ADJ
alkej-6	38	21	steering	steering	NOUN
alkej-6	38	22	direction	direction	NOUN
alkej-6	38	23	.	.	PUNCT
alkej-6	39	1	because	because	SCONJ
alkej-6	39	2	r	r	NOUN
alkej-6	39	3	is	be	AUX
alkej-6	39	4	consisting	consist	VERB
alkej-6	39	5	of	of	ADP
alkej-6	39	6	a	a	DET
alkej-6	39	7	signal	signal	ADJ
alkej-6	39	8	subspace	subspace	NOUN
alkej-6	39	9	and	and	CCONJ
alkej-6	39	10	noise	noise	NOUN
alkej-6	39	11	subspace	subspace	NOUN
alkej-6	39	12	,	,	PUNCT
alkej-6	39	13	then	then	ADV
alkej-6	39	14	we	we	PRON
alkej-6	39	15	will	will	AUX
alkej-6	39	16	take	take	VERB
alkej-6	39	17	only	only	ADV
alkej-6	39	18	the	the	DET
alkej-6	39	19	signal	signal	ADJ
alkej-6	39	20	subspace	subspace	NOUN
alkej-6	39	21	rs	rs	NOUN
alkej-6	39	22	,	,	PUNCT
alkej-6	39	23	which	which	PRON
alkej-6	39	24	is	be	AUX
alkej-6	39	25	equal	equal	ADJ
alkej-6	39	26	to	to	ADP
alkej-6	39	27	es	es	VERB
alkej-6	39	28	λs	λs	ADP
alkej-6	39	29	es	es	X
alkej-6	39	30	(	(	PUNCT
alkej-6	39	31	8)	8)	NUM
alkej-6	39	32	where	where	SCONJ
alkej-6	39	33	λs	λs	NOUN
alkej-6	39	34	is	be	AUX
alkej-6	39	35	a	a	DET
alkej-6	39	36	diagonal	diagonal	ADJ
alkej-6	39	37	matrix	matrix	NOUN
alkej-6	39	38	of	of	ADP
alkej-6	39	39	the	the	DET
alkej-6	39	40	signal	signal	NOUN
alkej-6	39	41	eigenvealues	eigenvealue	NOUN
alkej-6	39	42	,	,	PUNCT
alkej-6	39	43	and	and	CCONJ
alkej-6	39	44	es	es	PRON
alkej-6	39	45	is	be	AUX
alkej-6	39	46	the	the	DET
alkej-6	39	47	corresponding	corresponding	ADJ
alkej-6	39	48	eigenvectors	eigenvector	NOUN
alkej-6	39	49	as	as	SCONJ
alkej-6	39	50	stated	state	VERB
alkej-6	39	51	in	in	ADP
alkej-6	39	52	(	(	PUNCT
alkej-6	39	53	5).this	5).this	NUM
alkej-6	39	54	feature	feature	NOUN
alkej-6	39	55	of	of	ADP
alkej-6	39	56	selection	selection	NOUN
alkej-6	39	57	the	the	DET
alkej-6	39	58	signal	signal	NOUN
alkej-6	39	59	subspace	subspace	NOUN
alkej-6	39	60	can	can	AUX
alkej-6	39	61	be	be	AUX
alkej-6	39	62	obtained	obtain	VERB
alkej-6	39	63	by	by	ADP
alkej-6	39	64	applying	apply	VERB
alkej-6	39	65	the	the	DET
alkej-6	39	66	principal	principal	ADJ
alkej-6	39	67	component	component	NOUN
alkej-6	39	68	analysis	analysis	NOUN
alkej-6	39	69	(	(	PUNCT
alkej-6	39	70	pca	pca	NOUN
alkej-6	39	71	)	)	PUNCT
alkej-6	39	72	neural	neural	ADJ
alkej-6	39	73	network	network	NOUN
alkej-6	39	74	which	which	PRON
alkej-6	39	75	extract	extract	VERB
alkej-6	39	76	the	the	DET
alkej-6	39	77	principal	principal	ADJ
alkej-6	39	78	component	component	NOUN
alkej-6	39	79	i.e.	i.e.	X
alkej-6	39	80	λ1	λ1	ADJ
alkej-6	39	81	,	,	PUNCT
alkej-6	39	82	λ2	λ2	NOUN
alkej-6	39	83	,	,	PUNCT
alkej-6	39	84	.	.	PUNCT
alkej-6	39	85	.	.	PUNCT
alkej-6	39	86	.	.	PUNCT
alkej-6	40	1	,	,	PUNCT
alkej-6	40	2	λd	λd	NOUN
alkej-6	40	3	and	and	CCONJ
alkej-6	40	4	its	its	PRON
alkej-6	40	5	corresponding	corresponding	ADJ
alkej-6	40	6	eigenvectors	eigenvector	NOUN
alkej-6	40	7	e1,e2	e1,e2	PROPN
alkej-6	40	8	,	,	PUNCT
alkej-6	40	9	.	.	PUNCT
alkej-6	40	10	.	.	PUNCT
alkej-6	41	1	.	.	PUNCT
alkej-6	42	1	,	,	PUNCT
alkej-6	42	2	ed	ed	NOUN
alkej-6	42	3	as	as	SCONJ
alkej-6	42	4	illustrated	illustrate	VERB
alkej-6	42	5	in	in	ADP
alkej-6	42	6	the	the	DET
alkej-6	42	7	next	next	ADJ
alkej-6	42	8	section	section	NOUN
alkej-6	42	9	.	.	PUNCT
alkej-6	43	1	the	the	DET
alkej-6	43	2	number	number	NOUN
alkej-6	43	3	of	of	ADP
alkej-6	43	4	sources	source	NOUN
alkej-6	43	5	is	be	AUX
alkej-6	43	6	assumed	assume	VERB
alkej-6	43	7	known	know	VERB
alkej-6	43	8	or	or	CCONJ
alkej-6	43	9	we	we	PRON
alkej-6	43	10	can	can	AUX
alkej-6	43	11	find	find	VERB
alkej-6	43	12	it	it	PRON
alkej-6	43	13	by	by	ADP
alkej-6	43	14	aic	aic	PROPN
alkej-6	43	15	,	,	PUNCT
alkej-6	43	16	or	or	CCONJ
alkej-6	43	17	mdl	mdl	NOUN
alkej-6	44	1	[	[	X
alkej-6	44	2	10	10	NUM
alkej-6	44	3	]	]	PUNCT
alkej-6	44	4	.	.	PUNCT
alkej-6	45	1	4.the	4.the	DET
alkej-6	45	2	neural	neural	ADJ
alkej-6	45	3	estimator	estimator	NOUN
alkej-6	45	4	in	in	ADP
alkej-6	45	5	the	the	DET
alkej-6	45	6	last	last	ADJ
alkej-6	45	7	years	year	NOUN
alkej-6	45	8	several	several	ADJ
alkej-6	45	9	papers	paper	NOUN
alkej-6	45	10	dealing	deal	VERB
alkej-6	45	11	with	with	ADP
alkej-6	45	12	pca	pca	PROPN
alkej-6	45	13	neural	neural	ADJ
alkej-6	45	14	networks	network	NOUN
alkej-6	46	1	[	[	X
alkej-6	46	2	3],[4],[5],[6],[7],[8],[11]and	3],[4],[5],[6],[7],[8],[11]and	NOUN
alkej-6	47	1	[	[	X
alkej-6	47	2	12	12	NUM
alkej-6	47	3	]	]	PUNCT
alkej-6	47	4	have	have	AUX
alkej-6	47	5	discussed	discuss	VERB
alkej-6	47	6	the	the	DET
alkej-6	47	7	advantages	advantage	NOUN
alkej-6	47	8	,	,	PUNCT
alkej-6	47	9	problems	problem	NOUN
alkej-6	47	10	,	,	PUNCT
alkej-6	47	11	and	and	CCONJ
alkej-6	47	12	difficulties	difficulty	NOUN
alkej-6	47	13	of	of	ADP
alkej-6	47	14	such	such	ADJ
alkej-6	47	15	neural	neural	ADJ
alkej-6	47	16	network	network	NOUN
alkej-6	47	17	(	(	PUNCT
alkej-6	47	18	which	which	PRON
alkej-6	47	19	is	be	AUX
alkej-6	47	20	shown	show	VERB
alkej-6	47	21	in	in	ADP
alkej-6	47	22	figure	figure	NOUN
alkej-6	47	23	2	2	NUM
alkej-6	47	24	)	)	PUNCT
alkej-6	47	25	.in	.in	PUNCT
alkej-6	48	1	what	what	PRON
alkej-6	48	2	follow	follow	VERB
alkej-6	48	3	we	we	PRON
alkej-6	48	4	make	make	VERB
alkej-6	48	5	use	use	NOUN
alkej-6	48	6	of	of	ADP
alkej-6	48	7	an	an	DET
alkej-6	48	8	gha	gha	NOUN
alkej-6	48	9	algorithm	algorithm	NOUN
alkej-6	48	10	with	with	ADP
alkej-6	48	11	adaptive	adaptive	ADJ
alkej-6	48	12	learning	learning	NOUN
alkej-6	48	13	rate	rate	NOUN
alkej-6	48	14	.	.	PUNCT
alkej-6	49	1	our	our	PRON
alkej-6	49	2	neural	neural	ADJ
alkej-6	49	3	estimator	estimator	NOUN
alkej-6	49	4	can	can	AUX
alkej-6	49	5	be	be	AUX
alkej-6	49	6	summarized	summarize	VERB
alkej-6	49	7	in	in	ADP
alkej-6	49	8	the	the	DET
alkej-6	49	9	following	follow	VERB
alkej-6	49	10	steps	step	NOUN
alkej-6	49	11	:	:	PUNCT
alkej-6	49	12	n.	n.	PROPN
alkej-6	49	13	h.	h.	PROPN
alkej-6	49	14	abbas	abbas	PROPN
alkej-6	49	15	/al	/al	PROPN
alkej-6	49	16	-	-	PUNCT
alkej-6	49	17	khwarizmi	khwarizmi	PROPN
alkej-6	49	18	engineering	engineering	NOUN
alkej-6	49	19	journal	journal	NOUN
alkej-6	49	20	,	,	PUNCT
alkej-6	49	21	vol.2	vol.2	PROPN
alkej-6	49	22	,	,	PUNCT
alkej-6	49	23	no	no	INTJ
alkej-6	49	24	.	.	PUNCT
alkej-6	50	1	1,pp	1,pp	NUM
alkej-6	50	2	70	70	NUM
alkej-6	50	3	-	-	SYM
alkej-6	50	4	77	77	NUM
alkej-6	50	5	(	(	PUNCT
alkej-6	50	6	2006	2006	NUM
alkej-6	50	7	)	)	PUNCT
alkej-6	50	8	72	72	NUM
alkej-6	50	9	1	1	NUM
alkej-6	50	10	)	)	PUNCT
alkej-6	50	11	the	the	DET
alkej-6	50	12	gha	gha	NOUN
alkej-6	50	13	algorithms	algorithm	NOUN
alkej-6	50	14	for	for	ADP
alkej-6	50	15	signal	signal	ADJ
alkej-6	50	16	samples	sample	NOUN
alkej-6	50	17	x(n	x(n	NOUN
alkej-6	50	18	):	):	PUNCT
alkej-6	50	19	ferom	ferom	ADJ
alkej-6	50	20	n=1	n=1	PROPN
alkej-6	50	21	to	to	ADP
alkej-6	50	22	n	n	PRON
alkej-6	50	23	(	(	PUNCT
alkej-6	50	24	i	i	NOUN
alkej-6	50	25	)	)	PUNCT
alkej-6	50	26	set	set	VERB
alkej-6	50	27	error	error	NOUN
alkej-6	50	28	signal	signal	NOUN
alkej-6	50	29	e0(n)=x(n	e0(n)=x(n	NOUN
alkej-6	50	30	)	)	PUNCT
alkej-6	50	31	for	for	ADP
alkej-6	50	32	every	every	DET
alkej-6	50	33	neuron	neuron	NOUN
alkej-6	50	34	:	:	PUNCT
alkej-6	50	35	from	from	ADP
alkej-6	50	36	j=1	j=1	PROPN
alkej-6	50	37	to	to	ADP
alkej-6	50	38	d	d	PROPN
alkej-6	50	39	(	(	PUNCT
alkej-6	50	40	2	2	NUM
alkej-6	50	41	)	)	PUNCT
alkej-6	50	42	set	set	VERB
alkej-6	50	43	wj(0	wj(0	PROPN
alkej-6	50	44	)	)	PUNCT
alkej-6	50	45	randomly	randomly	ADV
alkej-6	50	46	(	(	PUNCT
alkej-6	50	47	3	3	X
alkej-6	50	48	)	)	PUNCT
alkej-6	50	49	set	set	VERB
alkej-6	50	50	ηj	ηj	NOUN
alkej-6	50	51	in	in	ADP
alkej-6	50	52	accordance	accordance	NOUN
alkej-6	50	53	with	with	ADP
alkej-6	50	54	input	input	NOUN
alkej-6	50	55	variance	variance	NOUN
alkej-6	50	56	for	for	ADP
alkej-6	50	57	input	input	NOUN
alkej-6	50	58	samples	sample	NOUN
alkej-6	50	59	:	:	PUNCT
alkej-6	50	60	from	from	ADP
alkej-6	50	61	n=1	n=1	PROPN
alkej-6	50	62	to	to	ADP
alkej-6	50	63	n	n	PRON
alkej-6	50	64	(	(	PUNCT
alkej-6	50	65	4	4	NUM
alkej-6	50	66	)	)	PUNCT
alkej-6	50	67	yj(n)=x(n)h×wj(n-1	yj(n)=x(n)h×wj(n-1	NOUN
alkej-6	50	68	)	)	PUNCT
alkej-6	50	69	(	(	PUNCT
alkej-6	50	70	5	5	X
alkej-6	50	71	)	)	PUNCT
alkej-6	50	72	wj(n)=	wj(n)=	ADV
alkej-6	50	73	wj(n-1)+ηj	wj(n-1)+ηj	PROPN
alkej-6	50	74	yj(n)[ej-1(n)-wj(n-1	yj(n)[ej-1(n)-wj(n-1	ADJ
alkej-6	50	75	)	)	PUNCT
alkej-6	50	76	×	×	NOUN
alkej-6	50	77	yj(n	yj(n	NUM
alkej-6	50	78	)	)	PUNCT
alkej-6	50	79	]	]	PUNCT
alkej-6	51	1	if	if	SCONJ
alkej-6	51	2	│	│	X
alkej-6	51	3	wj(k)wj(k-1	wj(k)wj(k-1	NUM
alkej-6	51	4	)	)	PUNCT
alkej-6	51	5	│	│	X
alkej-6	51	6	<	<	X
alkej-6	51	7	є	є	PROPN
alkej-6	51	8	(	(	PUNCT
alkej-6	51	9	where	where	SCONJ
alkej-6	51	10	є	є	PROPN
alkej-6	51	11	is	be	AUX
alkej-6	51	12	very	very	ADV
alkej-6	51	13	small	small	ADJ
alkej-6	51	14	value	value	NOUN
alkej-6	51	15	)	)	PUNCT
alkej-6	51	16	then	then	ADV
alkej-6	51	17	(	(	PUNCT
alkej-6	51	18	6	6	X
alkej-6	51	19	)	)	PUNCT
alkej-6	51	20	wj	wj	NOUN
alkej-6	51	21	=	=	NOUN
alkej-6	51	22	wj(n	wj(n	NUM
alkej-6	51	23	)	)	PUNCT
alkej-6	51	24	;	;	PUNCT
alkej-6	51	25	go	go	VERB
alkej-6	51	26	to	to	ADP
alkej-6	51	27	stable	stable	ADJ
alkej-6	51	28	(	(	PUNCT
alkej-6	51	29	7	7	NUM
alkej-6	51	30	)	)	PUNCT
alkej-6	51	31	decrease	decrease	NOUN
alkej-6	51	32	ηj	ηj	ADP
alkej-6	51	33	exponentially	exponentially	ADV
alkej-6	51	34	stable	stable	ADJ
alkej-6	51	35	:	:	PUNCT
alkej-6	51	36	for	for	ADP
alkej-6	51	37	input	input	NOUN
alkej-6	51	38	samples	sample	NOUN
alkej-6	51	39	:	:	PUNCT
alkej-6	51	40	from	from	ADP
alkej-6	51	41	n=1	n=1	PROPN
alkej-6	51	42	to	to	ADP
alkej-6	51	43	n	n	PROPN
alkej-6	51	44	(	(	PUNCT
alkej-6	51	45	8)	8)	NUM
alkej-6	51	46	set	set	ADJ
alkej-6	51	47	yj(n)=x(n)h×wj	yj(n)=x(n)h×wj	NOUN
alkej-6	51	48	(	(	PUNCT
alkej-6	51	49	9	9	NUM
alkej-6	51	50	)	)	PUNCT
alkej-6	51	51	set	set	NOUN
alkej-6	51	52	error	error	NOUN
alkej-6	51	53	ej(n)=ej-1(n)-yj(n)wj	ej(n)=ej-1(n)-yj(n)wj	NOUN
alkej-6	51	54	2	2	NUM
alkej-6	51	55	)	)	PUNCT
alkej-6	51	56	wj	wj	PROPN
alkej-6	51	57	qj	qj	PROPN
alkej-6	51	58	,	,	PUNCT
alkej-6	51	59	and	and	CCONJ
alkej-6	51	60	yj	yj	PROPN
alkej-6	51	61	jv	jv	PROPN
alkej-6	51	62	where	where	SCONJ
alkej-6	51	63	qj	qj	PROPN
alkej-6	51	64	are	be	AUX
alkej-6	51	65	the	the	DET
alkej-6	51	66	eigenvectors	eigenvector	NOUN
alkej-6	51	67	corresponding	correspond	VERB
alkej-6	51	68	to	to	PART
alkej-6	51	69	eigenvalues	eigenvalue	VERB
alkej-6	51	70	vj	vj	PROPN
alkej-6	51	71	.	.	PROPN
alkej-6	51	72	3	3	NUM
alkej-6	51	73	)	)	PUNCT
alkej-6	51	74	doa	doa	NOUN
alkej-6	51	75	estimator	estimator	NOUN
alkej-6	51	76	,	,	PUNCT
alkej-6	51	77	we	we	PRON
alkej-6	51	78	use	use	VERB
alkej-6	51	79	the	the	DET
alkej-6	51	80	modified	modify	VERB
alkej-6	51	81	capon	capon	NOUN
alkej-6	51	82	method	method	NOUN
alkej-6	51	83	where	where	SCONJ
alkej-6	51	84	we	we	PRON
alkej-6	51	85	take	take	VERB
alkej-6	51	86	the	the	DET
alkej-6	51	87	synaptic	synaptic	ADJ
alkej-6	51	88	weight	weight	NOUN
alkej-6	51	89	as	as	ADP
alkej-6	51	90	the	the	DET
alkej-6	51	91	eigenvector	eigenvector	NOUN
alkej-6	51	92	of	of	ADP
alkej-6	51	93	the	the	DET
alkej-6	51	94	signalsubspace	signalsubspace	NOUN
alkej-6	51	95	and	and	CCONJ
alkej-6	51	96	the	the	DET
alkej-6	51	97	output	output	NOUN
alkej-6	51	98	of	of	ADP
alkej-6	51	99	the	the	DET
alkej-6	51	100	pca	pca	PROPN
alkej-6	51	101	neural	neural	ADJ
alkej-6	51	102	network	network	NOUN
alkej-6	51	103	as	as	ADP
alkej-6	51	104	the	the	DET
alkej-6	51	105	squire	squire	NOUN
alkej-6	51	106	roots	root	NOUN
alkej-6	51	107	of	of	ADP
alkej-6	51	108	the	the	DET
alkej-6	51	109	output	output	NOUN
alkej-6	51	110	[	[	X
alkej-6	51	111	7	7	NUM
alkej-6	51	112	]	]	PUNCT
alkej-6	51	113	.	.	PUNCT
alkej-6	52	1	then	then	ADV
alkej-6	52	2	doa	doa	PROPN
alkej-6	52	3	are	be	AUX
alkej-6	52	4	obtained	obtain	VERB
alkej-6	52	5	as	as	ADP
alkej-6	52	6	the	the	DET
alkej-6	52	7	peak	peak	NOUN
alkej-6	52	8	location	location	NOUN
alkej-6	52	9	of	of	ADP
alkej-6	52	10	the	the	DET
alkej-6	52	11	function	function	NOUN
alkej-6	52	12	according	accord	VERB
alkej-6	52	13	to	to	ADP
alkej-6	52	14	the	the	DET
alkej-6	52	15	equation	equation	NOUN
alkej-6	52	16	pmcapon	pmcapon	NOUN
alkej-6	52	17	(	(	PUNCT
alkej-6	52	18	θ	θ	PROPN
alkej-6	52	19	,	,	PUNCT
alkej-6	52	20	φ	φ	NUM
alkej-6	52	21	)	)	PUNCT
alkej-6	53	1	=	=	NOUN
alkej-6	53	2	1/(ah	1/(ah	NUM
alkej-6	53	3	(	(	PUNCT
alkej-6	53	4	θ	θ	PROPN
alkej-6	53	5	,	,	PUNCT
alkej-6	53	6	φ)řs	φ)řs	PROPN
alkej-6	53	7	-1	-1	PUNCT
alkej-6	53	8	a	a	DET
alkej-6	53	9	(	(	PUNCT
alkej-6	53	10	θ	θ	PROPN
alkej-6	53	11	,	,	PUNCT
alkej-6	53	12	φ	φ	NOUN
alkej-6	53	13	)	)	PUNCT
alkej-6	53	14	)	)	PUNCT
alkej-6	53	15	.	.	PUNCT
alkej-6	54	1	(	(	PUNCT
alkej-6	54	2	9	9	X
alkej-6	54	3	)	)	PUNCT
alkej-6	54	4	where	where	SCONJ
alkej-6	54	5	řs	řs	AUX
alkej-6	54	6	-1	-1	NOUN
alkej-6	54	7	=	=	NOUN
alkej-6	54	8	inverse	inverse	NOUN
alkej-6	54	9	of	of	ADP
alkej-6	54	10	řs	řs	NOUN
alkej-6	54	11	,	,	PUNCT
alkej-6	54	12	and	and	CCONJ
alkej-6	54	13	řs=∑	řs=∑	NUM
alkej-6	54	14	d	d	X
alkej-6	54	15	i=1	i=1	PROPN
alkej-6	54	16	(	(	PUNCT
alkej-6	54	17	yj	yj	PROPN
alkej-6	54	18	)	)	PUNCT
alkej-6	54	19	2	2	NUM
alkej-6	54	20	wi	wi	PROPN
alkej-6	54	21	wi	wi	PROPN
alkej-6	54	22	h	h	PROPN
alkej-6	54	23	.	.	PUNCT
alkej-6	55	1	5.simulation	5.simulation	NUM
alkej-6	55	2	in	in	ADP
alkej-6	55	3	our	our	PRON
alkej-6	55	4	simulation	simulation	NOUN
alkej-6	55	5	we	we	PRON
alkej-6	55	6	will	will	AUX
alkej-6	55	7	use	use	VERB
alkej-6	55	8	a	a	DET
alkej-6	55	9	uniform	uniform	ADJ
alkej-6	55	10	circular	circular	ADJ
alkej-6	55	11	array	array	NOUN
alkej-6	55	12	consisting	consist	VERB
alkej-6	55	13	of	of	ADP
alkej-6	55	14	eight	eight	NUM
alkej-6	55	15	sensors	sensor	NOUN
alkej-6	55	16	of	of	ADP
alkej-6	55	17	radius	radius	NOUN
alkej-6	55	18	5λ	5λ	NUM
alkej-6	55	19	/	/	SYM
alkej-6	55	20	π	π	PROPN
alkej-6	55	21	as	as	SCONJ
alkej-6	55	22	shown	show	VERB
alkej-6	55	23	in	in	ADP
alkej-6	55	24	figure	figure	NOUN
alkej-6	55	25	1	1	NUM
alkej-6	55	26	.	.	PUNCT
alkej-6	55	27	assuming	assume	VERB
alkej-6	55	28	two	two	NUM
alkej-6	55	29	noncoherent	noncoherent	NOUN
alkej-6	55	30	signals	signal	NOUN
alkej-6	55	31	with	with	ADP
alkej-6	55	32	the	the	DET
alkej-6	55	33	signal	signal	NOUN
alkej-6	55	34	to	to	PART
alkej-6	55	35	noise	noise	VERB
alkej-6	55	36	ratio	ratio	NOUN
alkej-6	55	37	equal	equal	ADJ
alkej-6	55	38	to	to	ADP
alkej-6	55	39	one	one	NUM
alkej-6	55	40	are	be	AUX
alkej-6	55	41	impinging	impinge	VERB
alkej-6	55	42	on	on	ADP
alkej-6	55	43	the	the	DET
alkej-6	55	44	array	array	NOUN
alkej-6	55	45	and	and	CCONJ
alkej-6	55	46	the	the	DET
alkej-6	55	47	first	first	ADJ
alkej-6	55	48	source	source	NOUN
alkej-6	55	49	have	have	VERB
alkej-6	55	50	elevation	elevation	NOUN
alkej-6	55	51	angle	angle	NOUN
alkej-6	55	52	θ1=50,and	θ1=50,and	NOUN
alkej-6	55	53	azimuth	azimuth	PROPN
alkej-6	55	54	angle	angle	PROPN
alkej-6	55	55	φ1=30	φ1=30	PROPN
alkej-6	55	56	,	,	PUNCT
alkej-6	55	57	while	while	SCONJ
alkej-6	55	58	the	the	DET
alkej-6	55	59	second	second	ADJ
alkej-6	55	60	source	source	NOUN
alkej-6	55	61	have	have	VERB
alkej-6	55	62	elevation	elevation	NOUN
alkej-6	55	63	angle	angle	NOUN
alkej-6	55	64	θ2=60	θ2=60	NOUN
alkej-6	55	65	,	,	PUNCT
alkej-6	55	66	and	and	CCONJ
alkej-6	55	67	azimuth	azimuth	PROPN
alkej-6	55	68	angle	angle	NOUN
alkej-6	55	69	φ2=40.then	φ2=40.then	ADV
alkej-6	55	70	by	by	ADP
alkej-6	55	71	the	the	DET
alkej-6	55	72	use	use	NOUN
alkej-6	55	73	of	of	ADP
alkej-6	55	74	the	the	DET
alkej-6	55	75	gha	gha	NOUN
alkej-6	55	76	algorithm	algorithm	NOUN
alkej-6	55	77	we	we	PRON
alkej-6	55	78	will	will	AUX
alkej-6	55	79	find	find	VERB
alkej-6	55	80	the	the	DET
alkej-6	55	81	signal	signal	ADJ
alkej-6	55	82	subspace	subspace	NOUN
alkej-6	55	83	,	,	PUNCT
alkej-6	55	84	that	that	SCONJ
alkej-6	55	85	in	in	ADP
alkej-6	55	86	turn	turn	NOUN
alkej-6	55	87	are	be	AUX
alkej-6	55	88	used	use	VERB
alkej-6	55	89	by	by	ADP
alkej-6	55	90	capon	capon	NOUN
alkej-6	55	91	method	method	NOUN
alkej-6	55	92	to	to	PART
alkej-6	55	93	find	find	VERB
alkej-6	55	94	the	the	DET
alkej-6	55	95	doa	doa	NOUN
alkej-6	55	96	of	of	ADP
alkej-6	55	97	impending	impending	ADJ
alkej-6	55	98	sources	source	NOUN
alkej-6	55	99	as	as	SCONJ
alkej-6	55	100	shown	show	VERB
alkej-6	55	101	in	in	ADP
alkej-6	55	102	figure	figure	NOUN
alkej-6	55	103	3,4	3,4	NUM
alkej-6	55	104	,	,	PUNCT
alkej-6	55	105	and	and	CCONJ
alkej-6	55	106	5,where	5,where	NUM
alkej-6	55	107	figure	figure	NOUN
alkej-6	55	108	3	3	NUM
alkej-6	55	109	show	show	VERB
alkej-6	55	110	the	the	DET
alkej-6	55	111	doa(θi	doa(θi	NOUN
alkej-6	55	112	,	,	PUNCT
alkej-6	55	113	φi),figure	φi),figure	NOUN
alkej-6	55	114	4	4	NUM
alkej-6	55	115	,	,	PUNCT
alkej-6	55	116	show	show	VERB
alkej-6	55	117	the	the	DET
alkej-6	55	118	azimuth	azimuth	PROPN
alkej-6	55	119	angle	angle	NOUN
alkej-6	55	120	only	only	ADV
alkej-6	55	121	,	,	PUNCT
alkej-6	55	122	while	while	SCONJ
alkej-6	55	123	figure	figure	NOUN
alkej-6	55	124	5	5	NUM
alkej-6	55	125	show	show	VERB
alkej-6	55	126	the	the	DET
alkej-6	55	127	elevation	elevation	NOUN
alkej-6	55	128	angle	angle	NOUN
alkej-6	55	129	only	only	ADV
alkej-6	55	130	,	,	PUNCT
alkej-6	55	131	where	where	SCONJ
alkej-6	55	132	the	the	DET
alkej-6	55	133	angle	angle	NOUN
alkej-6	55	134	will	will	AUX
alkej-6	55	135	be	be	AUX
alkej-6	55	136	corresponding	correspond	VERB
alkej-6	55	137	to	to	ADP
alkej-6	55	138	the	the	DET
alkej-6	55	139	peak	peak	NOUN
alkej-6	55	140	locations	location	NOUN
alkej-6	55	141	in	in	ADP
alkej-6	55	142	the	the	DET
alkej-6	55	143	n.	n.	PROPN
alkej-6	55	144	h.	h.	PROPN
alkej-6	55	145	abbas	abbas	PROPN
alkej-6	55	146	/al	/al	PROPN
alkej-6	55	147	-	-	PUNCT
alkej-6	55	148	khwarizmi	khwarizmi	PROPN
alkej-6	55	149	engineering	engineering	NOUN
alkej-6	55	150	journal	journal	NOUN
alkej-6	55	151	,	,	PUNCT
alkej-6	55	152	vol.2	vol.2	PROPN
alkej-6	55	153	,	,	PUNCT
alkej-6	55	154	no	no	INTJ
alkej-6	55	155	.	.	PUNCT
alkej-6	56	1	1,pp	1,pp	NUM
alkej-6	56	2	70	70	NUM
alkej-6	56	3	-	-	SYM
alkej-6	56	4	77	77	NUM
alkej-6	56	5	(	(	PUNCT
alkej-6	56	6	2006	2006	NUM
alkej-6	56	7	)	)	PUNCT
alkej-6	56	8	73	73	NUM
alkej-6	56	9	spectrum	spectrum	NOUN
alkej-6	56	10	of	of	ADP
alkej-6	56	11	the	the	DET
alkej-6	56	12	capon	capon	NOUN
alkej-6	56	13	as	as	SCONJ
alkej-6	56	14	shown	show	VERB
alkej-6	56	15	in	in	ADP
alkej-6	56	16	previous	previous	ADJ
alkej-6	56	17	figures	figure	NOUN
alkej-6	56	18	.	.	PUNCT
alkej-6	57	1	6	6	X
alkej-6	57	2	.	.	X
alkej-6	57	3	discussion	discussion	NOUN
alkej-6	57	4	and	and	CCONJ
alkej-6	57	5	conclusions	conclusion	NOUN
alkej-6	57	6	this	this	DET
alkej-6	57	7	paper	paper	NOUN
alkej-6	57	8	described	describe	VERB
alkej-6	57	9	a	a	DET
alkej-6	57	10	simple	simple	ADJ
alkej-6	57	11	,	,	PUNCT
alkej-6	57	12	but	but	CCONJ
alkej-6	57	13	efficient	efficient	ADJ
alkej-6	57	14	methods	method	NOUN
alkej-6	57	15	based	base	VERB
alkej-6	57	16	on	on	ADP
alkej-6	57	17	pca	pca	PROPN
alkej-6	57	18	neural	neural	ADJ
alkej-6	57	19	network	network	NOUN
alkej-6	57	20	to	to	PART
alkej-6	57	21	find	find	VERB
alkej-6	57	22	the	the	DET
alkej-6	57	23	doa	doa	NOUN
alkej-6	57	24	,	,	PUNCT
alkej-6	57	25	where	where	SCONJ
alkej-6	57	26	by	by	ADP
alkej-6	57	27	use	use	NOUN
alkej-6	57	28	of	of	ADP
alkej-6	57	29	the	the	DET
alkej-6	57	30	pca	pca	PROPN
alkej-6	57	31	neural	neural	ADJ
alkej-6	57	32	network	network	NOUN
alkej-6	57	33	we	we	PRON
alkej-6	57	34	do	do	AUX
alkej-6	57	35	n’t	not	PART
alkej-6	57	36	need	need	VERB
alkej-6	57	37	to	to	PART
alkej-6	57	38	compute	compute	VERB
alkej-6	57	39	the	the	DET
alkej-6	57	40	correlation	correlation	NOUN
alkej-6	57	41	matrix	matrix	NOUN
alkej-6	57	42	r	r	NOUN
alkej-6	57	43	rather	rather	ADV
alkej-6	57	44	the	the	DET
alkej-6	57	45	first	first	ADJ
alkej-6	57	46	d	d	ADJ
alkej-6	57	47	eigenvectors	eigenvector	NOUN
alkej-6	57	48	of	of	ADP
alkej-6	57	49	r	r	NOUN
alkej-6	57	50	are	be	AUX
alkej-6	57	51	computed	compute	VERB
alkej-6	57	52	by	by	ADP
alkej-6	57	53	the	the	DET
alkej-6	57	54	algorithm	algorithm	NOUN
alkej-6	57	55	directly	directly	ADV
alkej-6	57	56	from	from	ADP
alkej-6	57	57	the	the	DET
alkej-6	57	58	input	input	NOUN
alkej-6	57	59	data	datum	NOUN
alkej-6	57	60	.the	.the	ADP
alkej-6	57	61	resulting	result	VERB
alkej-6	57	62	computational	computational	ADJ
alkej-6	57	63	saving	saving	NOUN
alkej-6	57	64	can	can	AUX
alkej-6	57	65	been	be	AUX
alkej-6	57	66	enormous	enormous	ADJ
alkej-6	57	67	especially	especially	ADV
alkej-6	57	68	if	if	SCONJ
alkej-6	57	69	the	the	DET
alkej-6	57	70	number	number	NOUN
alkej-6	57	71	of	of	ADP
alkej-6	57	72	element	element	NOUN
alkej-6	57	73	m	m	NOUN
alkej-6	57	74	in	in	ADP
alkej-6	57	75	the	the	DET
alkej-6	57	76	input	input	NOUN
alkej-6	57	77	vector	vector	NOUN
alkej-6	57	78	is	be	AUX
alkej-6	57	79	very	very	ADV
alkej-6	57	80	large	large	ADJ
alkej-6	57	81	,	,	PUNCT
alkej-6	57	82	and	and	CCONJ
alkej-6	57	83	the	the	DET
alkej-6	57	84	required	required	ADJ
alkej-6	57	85	number	number	NOUN
alkej-6	57	86	of	of	ADP
alkej-6	57	87	the	the	DET
alkej-6	57	88	eigenvectors	eigenvector	NOUN
alkej-6	57	89	associated	associate	VERB
alkej-6	57	90	with	with	ADP
alkej-6	57	91	the	the	DET
alkej-6	57	92	d	d	ADV
alkej-6	57	93	largest	large	ADJ
alkej-6	57	94	eigenvalues	eigenvalue	NOUN
alkej-6	57	95	of	of	ADP
alkej-6	57	96	the	the	DET
alkej-6	57	97	correlation	correlation	NOUN
alkej-6	57	98	matrix	matrix	NOUN
alkej-6	57	99	r	r	NOUN
alkej-6	57	100	is	be	AUX
alkej-6	57	101	small	small	ADJ
alkej-6	57	102	fraction	fraction	NOUN
alkej-6	57	103	of	of	ADP
alkej-6	57	104	m	m	PROPN
alkej-6	57	105	..	..	PUNCT
alkej-6	57	106	then	then	ADV
alkej-6	57	107	the	the	DET
alkej-6	57	108	doa	doa	NOUN
alkej-6	57	109	is	be	AUX
alkej-6	57	110	achieved	achieve	VERB
alkej-6	57	111	by	by	ADP
alkej-6	57	112	incorporating	incorporate	VERB
alkej-6	57	113	the	the	DET
alkej-6	57	114	neural	neural	ADJ
alkej-6	57	115	network	network	NOUN
alkej-6	57	116	with	with	ADP
alkej-6	57	117	capon	capon	NOUN
alkej-6	57	118	method	method	NOUN
alkej-6	57	119	,	,	PUNCT
alkej-6	57	120	with	with	ADP
alkej-6	57	121	use	use	NOUN
alkej-6	57	122	of	of	ADP
alkej-6	57	123	signal	signal	ADJ
alkej-6	57	124	subspace	subspace	NOUN
alkej-6	57	125	only	only	ADV
alkej-6	57	126	.	.	PUNCT
alkej-6	58	1	thus	thus	ADV
alkej-6	58	2	by	by	ADP
alkej-6	58	3	the	the	DET
alkej-6	58	4	use	use	NOUN
alkej-6	58	5	of	of	ADP
alkej-6	58	6	pca	pca	PROPN
alkej-6	58	7	neural	neural	ADJ
alkej-6	58	8	network	network	NOUN
alkej-6	58	9	we	we	PRON
alkej-6	58	10	neglect	neglect	VERB
alkej-6	58	11	part	part	NOUN
alkej-6	58	12	of	of	ADP
alkej-6	58	13	the	the	DET
alkej-6	58	14	noise	noise	NOUN
alkej-6	58	15	,	,	PUNCT
alkej-6	58	16	due	due	ADP
alkej-6	58	17	to	to	ADP
alkej-6	58	18	the	the	DET
alkej-6	58	19	neglecting	neglecting	NOUN
alkej-6	58	20	of	of	ADP
alkej-6	58	21	the	the	DET
alkej-6	58	22	noise	noise	NOUN
alkej-6	58	23	subspace	subspace	NOUN
alkej-6	58	24	.	.	PUNCT
alkej-6	59	1	7.refereneces	7.refereneces	NUM
alkej-6	60	1	[	[	X
alkej-6	60	2	1	1	NUM
alkej-6	60	3	]	]	X
alkej-6	60	4	blester	blester	NOUN
alkej-6	60	5	,	,	PUNCT
alkej-6	60	6	y	y	PROPN
alkej-6	60	7	and	and	CCONJ
alkej-6	60	8	macorski	macorski	PROPN
alkej-6	60	9	a.	a.	PROPN
alkej-6	60	10	,	,	PUNCT
alkej-6	60	11	1986	1986	NUM
alkej-6	60	12	"	"	PUNCT
alkej-6	60	13	exact	exact	ADJ
alkej-6	60	14	maximum	maximum	ADJ
alkej-6	60	15	likelihood	likelihood	NOUN
alkej-6	60	16	parameter	parameter	NOUN
alkej-6	60	17	estimation	estimation	NOUN
alkej-6	60	18	of	of	ADP
alkej-6	60	19	superimposed	superimpose	VERB
alkej-6	60	20	exponential	exponential	ADJ
alkej-6	60	21	signals	signal	NOUN
alkej-6	60	22	in	in	ADP
alkej-6	60	23	noise	noise	NOUN
alkej-6	60	24	"	"	PUNCT
alkej-6	60	25	,	,	PUNCT
alkej-6	60	26	ieee	ieee	NOUN
alkej-6	60	27	trans	tran	NOUN
alkej-6	60	28	.	.	PUNCT
alkej-6	61	1	on	on	ADP
alkej-6	61	2	acoustic	acoustic	ADJ
alkej-6	61	3	,	,	PUNCT
alkej-6	61	4	speech	speech	NOUN
alkej-6	61	5	,	,	PUNCT
alkej-6	61	6	and	and	CCONJ
alkej-6	61	7	signal	signal	NOUN
alkej-6	61	8	processing	processing	NOUN
alkej-6	61	9	,	,	PUNCT
alkej-6	61	10	vol	vol	NOUN
alkej-6	61	11	.	.	PROPN
alkej-6	61	12	34	34	NUM
alkej-6	61	13	,	,	PUNCT
alkej-6	61	14	pp	pp	ADJ
alkej-6	61	15	.	.	PUNCT
alkej-6	61	16	1081	1081	NUM
alkej-6	61	17	-	-	SYM
alkej-6	61	18	1089	1089	NUM
alkej-6	61	19	.	.	PUNCT
alkej-6	62	1	[	[	X
alkej-6	62	2	2	2	NUM
alkej-6	62	3	]	]	PUNCT
alkej-6	62	4	capon	capon	NOUN
alkej-6	62	5	,	,	PUNCT
alkej-6	62	6	j.	j.	PROPN
alkej-6	62	7	,	,	PUNCT
alkej-6	62	8	1969,"highresolution	1969,"highresolution	NOUN
alkej-6	62	9	frequency	frequency	NOUN
alkej-6	62	10	–	–	PUNCT
alkej-6	62	11	wavenumber	wavenumber	NOUN
alkej-6	62	12	spectrum	spectrum	NOUN
alkej-6	62	13	analysis	analysis	NOUN
alkej-6	62	14	"	"	PUNCT
alkej-6	62	15	,	,	PUNCT
alkej-6	62	16	proc	proc	PROPN
alkej-6	62	17	.	.	PUNCT
alkej-6	63	1	ieee	ieee	NOUN
alkej-6	63	2	,	,	PUNCT
alkej-6	63	3	vol	vol	NOUN
alkej-6	63	4	.	.	PROPN
alkej-6	63	5	57	57	NUM
alkej-6	63	6	,	,	PUNCT
alkej-6	63	7	no	no	INTJ
alkej-6	63	8	.	.	NOUN
alkej-6	63	9	8	8	NUM
alkej-6	63	10	,	,	PUNCT
alkej-6	63	11	august	august	PROPN
alkej-6	63	12	,	,	PUNCT
alkej-6	63	13	pp	pp	ADJ
alkej-6	63	14	.	.	PUNCT
alkej-6	63	15	1408	1408	NUM
alkej-6	63	16	–	–	PUNCT
alkej-6	63	17	18	18	NUM
alkej-6	63	18	.	.	PUNCT
alkej-6	64	1	[	[	X
alkej-6	64	2	3	3	NUM
alkej-6	64	3	]	]	X
alkej-6	64	4	chatterjee	chatterjee	NOUN
alkej-6	64	5	,	,	PUNCT
alkej-6	64	6	c.	c.	PROPN
alkej-6	64	7	,	,	PUNCT
alkej-6	64	8	kang	kang	PROPN
alkej-6	64	9	,	,	PUNCT
alkej-6	64	10	z.	z.	PROPN
alkej-6	64	11	,	,	PUNCT
alkej-6	64	12	and	and	CCONJ
alkej-6	64	13	roychowdhury	roychowdhury	NOUN
alkej-6	64	14	,	,	PUNCT
alkej-6	64	15	v.	v.	ADP
alkej-6	64	16	,	,	PUNCT
alkej-6	64	17	2000	2000	NUM
alkej-6	64	18	,	,	PUNCT
alkej-6	64	19	"	"	PUNCT
alkej-6	64	20	algorithm	algorithm	NOUN
alkej-6	64	21	for	for	ADP
alkej-6	64	22	accelerated	accelerated	ADJ
alkej-6	64	23	convergence	convergence	NOUN
alkej-6	64	24	of	of	ADP
alkej-6	64	25	adaptive	adaptive	ADJ
alkej-6	64	26	pca	pca	NOUN
alkej-6	64	27	"	"	PUNCT
alkej-6	64	28	,	,	PUNCT
alkej-6	64	29	ieee	ieee	PROPN
alkej-6	64	30	trans	tran	NOUN
alkej-6	64	31	.	.	PUNCT
alkej-6	65	1	on	on	ADP
alkej-6	65	2	neural	neural	ADJ
alkej-6	65	3	network	network	NOUN
alkej-6	65	4	,	,	PUNCT
alkej-6	65	5	vol.11	vol.11	PROPN
alkej-6	65	6	,	,	PUNCT
alkej-6	65	7	no.2	no.2	PROPN
alkej-6	65	8	.	.	PUNCT
alkej-6	66	1	[	[	X
alkej-6	66	2	4	4	NUM
alkej-6	66	3	]	]	X
alkej-6	66	4	chchocki	chchocki	ADJ
alkej-6	66	5	,	,	PUNCT
alkej-6	66	6	a.	a.	NOUN
alkej-6	66	7	,	,	PUNCT
alkej-6	66	8	kasprzak	kasprzak	PROPN
alkej-6	66	9	,	,	PUNCT
alkej-6	66	10	w.	w.	NOUN
alkej-6	66	11	,	,	PUNCT
alkej-6	66	12	and	and	CCONJ
alkej-6	66	13	skarbek	skarbek	NOUN
alkej-6	66	14	,	,	PUNCT
alkej-6	66	15	w.	w.	PROPN
alkej-6	66	16	,	,	PUNCT
alkej-6	66	17	1996,"adaptive	1996,"adaptive	NUM
alkej-6	66	18	learning	learn	VERB
alkej-6	66	19	algorithm	algorithm	NOUN
alkej-6	66	20	for	for	ADP
alkej-6	66	21	principal	principal	ADJ
alkej-6	66	22	component	component	NOUN
alkej-6	66	23	analysis	analysis	NOUN
alkej-6	66	24	with	with	ADP
alkej-6	66	25	partial	partial	ADJ
alkej-6	66	26	data	datum	NOUN
alkej-6	66	27	"	"	PUNCT
alkej-6	66	28	,	,	PUNCT
alkej-6	66	29	austrian	austrian	ADJ
alkej-6	66	30	society	society	NOUN
alkej-6	66	31	for	for	ADP
alkej-6	66	32	syberenetic	syberenetic	ADJ
alkej-6	66	33	studies	study	NOUN
alkej-6	66	34	,	,	PUNCT
alkej-6	66	35	vienna	vienna	PROPN
alkej-6	66	36	,	,	PUNCT
alkej-6	66	37	austria	austria	PROPN
alkej-6	66	38	.	.	PUNCT
alkej-6	67	1	[	[	X
alkej-6	67	2	5	5	NUM
alkej-6	67	3	]	]	X
alkej-6	67	4	chen	chen	PROPN
alkej-6	67	5	,	,	PUNCT
alkej-6	67	6	t.	t.	NOUN
alkej-6	67	7	,	,	PUNCT
alkej-6	67	8	and	and	CCONJ
alkej-6	67	9	yan	yan	PROPN
alkej-6	67	10	,	,	PUNCT
alkej-6	67	11	w.	w.	PROPN
alkej-6	67	12	,	,	PUNCT
alkej-6	67	13	1998	1998	NUM
alkej-6	67	14	,	,	PUNCT
alkej-6	67	15	"	"	PUNCT
alkej-6	67	16	global	global	ADJ
alkej-6	67	17	convergence	convergence	NOUN
alkej-6	67	18	of	of	ADP
alkej-6	67	19	oja׳s	oja׳s	ADJ
alkej-6	67	20	subspace	subspace	NOUN
alkej-6	67	21	algorithm	algorithm	NOUN
alkej-6	67	22	for	for	ADP
alkej-6	67	23	principal	principal	ADJ
alkej-6	67	24	component	component	NOUN
alkej-6	67	25	extractions",vol	extractions",vol	NOUN
alkej-6	67	26	.	.	PUNCT
alkej-6	68	1	9	9	NUM
alkej-6	68	2	,	,	PUNCT
alkej-6	68	3	no	no	INTJ
alkej-6	68	4	.	.	NOUN
alkej-6	68	5	1	1	NUM
alkej-6	68	6	.	.	PUNCT
alkej-6	69	1	[	[	X
alkej-6	69	2	6]chichoki	6]chichoki	NUM
alkej-6	69	3	,	,	PUNCT
alkej-6	69	4	a.	a.	NOUN
alkej-6	69	5	,	,	PUNCT
alkej-6	69	6	swiniarski	swiniarski	NOUN
alkej-6	69	7	,	,	PUNCT
alkej-6	69	8	r.	r.	PROPN
alkej-6	69	9	,	,	PUNCT
alkej-6	69	10	w.	w.	PROPN
alkej-6	69	11	,	,	PUNCT
alkej-6	69	12	and	and	CCONJ
alkej-6	69	13	bogner	bogner	PROPN
alkej-6	69	14	,	,	PUNCT
alkej-6	69	15	r.	r.	PROPN
alkej-6	69	16	,	,	PUNCT
alkej-6	69	17	e.	e.	PROPN
alkej-6	69	18	,1996	,1996	PROPN
alkej-6	69	19	,	,	PUNCT
alkej-6	69	20	"	"	PUNCT
alkej-6	69	21	hierchical	hierchical	ADJ
alkej-6	69	22	neural	neural	ADJ
alkej-6	69	23	networks	network	NOUN
alkej-6	69	24	for	for	ADP
alkej-6	69	25	robust	robust	ADJ
alkej-6	69	26	pca	pca	NOUN
alkej-6	69	27	computation	computation	NOUN
alkej-6	69	28	of	of	ADP
alkej-6	69	29	complex	complex	ADJ
alkej-6	69	30	valued	value	VERB
alkej-6	69	31	signals	signal	NOUN
alkej-6	69	32	"	"	PUNCT
alkej-6	69	33	.	.	PUNCT
alkej-6	70	1	[	[	X
alkej-6	70	2	7	7	X
alkej-6	70	3	]	]	X
alkej-6	70	4	haykin	haykin	PROPN
alkej-6	70	5	,	,	PUNCT
alkej-6	70	6	s.	s.	PROPN
alkej-6	70	7	,	,	PUNCT
alkej-6	70	8	1994	1994	NUM
alkej-6	70	9	,	,	PUNCT
alkej-6	70	10	"	"	PUNCT
alkej-6	70	11	neural	neural	ADJ
alkej-6	70	12	network	network	NOUN
alkej-6	70	13	,	,	PUNCT
alkej-6	70	14	a	a	DET
alkej-6	70	15	comprehensive	comprehensive	ADJ
alkej-6	70	16	foundation	foundation	NOUN
alkej-6	70	17	"	"	PUNCT
alkej-6	70	18	,	,	PUNCT
alkej-6	70	19	©	©	PROPN
alkej-6	70	20	by	by	ADP
alkej-6	70	21	macmillan	macmillan	PROPN
alkej-6	70	22	college	college	PROPN
alkej-6	70	23	publishing	publishing	PROPN
alkej-6	70	24	company	company	NOUN
alkej-6	70	25	.	.	PUNCT
alkej-6	70	26	inc	inc	PROPN
alkej-6	70	27	.	.	PUNCT
alkej-6	71	1	[	[	X
alkej-6	71	2	8	8	NUM
alkej-6	71	3	]	]	X
alkej-6	71	4	kung	kung	PROPN
alkej-6	71	5	,	,	PUNCT
alkej-6	71	6	s.	s.	PROPN
alkej-6	71	7	,	,	PUNCT
alkej-6	71	8	y.	y.	PROPN
alkej-6	71	9	,	,	PUNCT
alkej-6	71	10	1993	1993	NUM
alkej-6	71	11	,	,	PUNCT
alkej-6	71	12	"	"	PUNCT
alkej-6	71	13	digital	digital	ADJ
alkej-6	71	14	neural	neural	ADJ
alkej-6	71	15	network	network	NOUN
alkej-6	71	16	"	"	PUNCT
alkej-6	71	17	,	,	PUNCT
alkej-6	71	18	©	©	PROPN
alkej-6	71	19	by	by	ADP
alkej-6	71	20	ptr	ptr	PROPN
alkej-6	71	21	prentice	prentice	PROPN
alkej-6	71	22	hall	hall	PROPN
alkej-6	71	23	,	,	PUNCT
alkej-6	71	24	inc	inc	PROPN
alkej-6	71	25	.	.	PUNCT
alkej-6	72	1	[	[	X
alkej-6	72	2	9	9	NUM
alkej-6	72	3	]	]	PUNCT
alkej-6	72	4	schmidt	schmidt	PROPN
alkej-6	72	5	,	,	PUNCT
alkej-6	72	6	r.o	r.o	PROPN
alkej-6	72	7	.	.	PROPN
alkej-6	72	8	,	,	PUNCT
alkej-6	72	9	1986	1986	NUM
alkej-6	72	10	,	,	PUNCT
alkej-6	72	11	"	"	PUNCT
alkej-6	72	12	multiple	multiple	ADJ
alkej-6	72	13	emitter	emitter	NOUN
alkej-6	72	14	location	location	NOUN
alkej-6	72	15	and	and	CCONJ
alkej-6	72	16	signal	signal	NOUN
alkej-6	72	17	parameter	parameter	NOUN
alkej-6	72	18	estimation	estimation	NOUN
alkej-6	72	19	"	"	PUNCT
alkej-6	72	20	,	,	PUNCT
alkej-6	72	21	ieee	ieee	NOUN
alkej-6	72	22	trans.on	trans.on	NOUN
alkej-6	72	23	antenna	antenna	NOUN
alkej-6	72	24	and	and	CCONJ
alkej-6	72	25	propagation	propagation	NOUN
alkej-6	72	26	,	,	PUNCT
alkej-6	72	27	vol	vol	NOUN
alkej-6	72	28	.	.	PROPN
alkej-6	72	29	34	34	NUM
alkej-6	72	30	,	,	PUNCT
alkej-6	72	31	no	no	INTJ
alkej-6	72	32	.	.	NOUN
alkej-6	72	33	3	3	NUM
alkej-6	72	34	,	,	PUNCT
alkej-6	72	35	pp	pp	ADJ
alkej-6	72	36	.	.	PUNCT
alkej-6	72	37	276	276	NUM
alkej-6	72	38	–	–	PUNCT
alkej-6	72	39	80	80	NUM
alkej-6	72	40	.	.	PUNCT
alkej-6	73	1	[	[	X
alkej-6	73	2	10	10	NUM
alkej-6	73	3	]	]	X
alkej-6	73	4	wax	wax	NOUN
alkej-6	73	5	,	,	PUNCT
alkej-6	73	6	m.	m.	NOUN
alkej-6	73	7	,	,	PUNCT
alkej-6	73	8	.and	.and	PUNCT
alkej-6	73	9	kailath	kailath	PROPN
alkej-6	73	10	,	,	PUNCT
alkej-6	73	11	t.	t.	PROPN
alkej-6	73	12	,	,	PUNCT
alkej-6	73	13	1985	1985	NUM
alkej-6	73	14	,	,	PUNCT
alkej-6	73	15	"	"	PUNCT
alkej-6	73	16	detection	detection	NOUN
alkej-6	73	17	of	of	ADP
alkej-6	73	18	signals	signal	NOUN
alkej-6	73	19	by	by	ADP
alkej-6	73	20	information	information	NOUN
alkej-6	73	21	theoretic	theoretic	NOUN
alkej-6	73	22	criteria	criterion	NOUN
alkej-6	73	23	"	"	PUNCT
alkej-6	73	24	,	,	PUNCT
alkej-6	73	25	ieee	ieee	PROPN
alkej-6	73	26	trans	tran	NOUN
alkej-6	73	27	.	.	PUNCT
alkej-6	74	1	on	on	ADP
alkej-6	74	2	acoustic	acoustic	ADJ
alkej-6	74	3	,	,	PUNCT
alkej-6	74	4	speech	speech	NOUN
alkej-6	74	5	,	,	PUNCT
alkej-6	74	6	and	and	CCONJ
alkej-6	74	7	signal	signal	NOUN
alkej-6	74	8	processing	processing	NOUN
alkej-6	74	9	,	,	PUNCT
alkej-6	74	10	vol	vol	NOUN
alkej-6	74	11	.	.	PUNCT
alkej-6	74	12	assp-33	assp-33	PROPN
alkej-6	74	13	,	,	PUNCT
alkej-6	74	14	no.2	no.2	PROPN
alkej-6	74	15	.	.	PUNCT
alkej-6	75	1	[	[	X
alkej-6	75	2	11	11	NUM
alkej-6	75	3	]	]	X
alkej-6	75	4	weinglessel	weinglessel	NOUN
alkej-6	75	5	,	,	PUNCT
alkej-6	75	6	a.	a.	NOUN
alkej-6	75	7	,	,	PUNCT
alkej-6	75	8	and	and	CCONJ
alkej-6	75	9	hornik	hornik	X
alkej-6	75	10	,	,	PUNCT
alkej-6	75	11	k.	k.	PROPN
alkej-6	75	12	,	,	PUNCT
alkej-6	75	13	2000	2000	NUM
alkej-6	75	14	,	,	PUNCT
alkej-6	75	15	"	"	PUNCT
alkej-6	75	16	local	local	ADJ
alkej-6	75	17	pca	pca	NOUN
alkej-6	75	18	algorithms	algorithm	NOUN
alkej-6	75	19	"	"	PUNCT
alkej-6	75	20	,	,	PUNCT
alkej-6	75	21	ieee	ieee	PROPN
alkej-6	75	22	trans	tran	NOUN
alkej-6	75	23	.	.	PUNCT
alkej-6	76	1	on	on	ADP
alkej-6	76	2	neural	neural	ADJ
alkej-6	76	3	network	network	NOUN
alkej-6	76	4	,	,	PUNCT
alkej-6	76	5	vol	vol	NOUN
alkej-6	76	6	.	.	PROPN
alkej-6	76	7	11	11	NUM
alkej-6	76	8	,	,	PUNCT
alkej-6	76	9	no.6	no.6	PROPN
alkej-6	76	10	.	.	PUNCT
alkej-6	77	1	[	[	X
alkej-6	77	2	12	12	NUM
alkej-6	77	3	]	]	X
alkej-6	77	4	weinglessel	weinglessel	NOUN
alkej-6	77	5	,	,	PUNCT
alkej-6	77	6	a.	a.	NOUN
alkej-6	77	7	,	,	PUNCT
alkej-6	77	8	and	and	CCONJ
alkej-6	77	9	hornick	hornick	INTJ
alkej-6	77	10	,	,	PUNCT
alkej-6	77	11	k.	k.	PROPN
alkej-6	77	12	,	,	PUNCT
alkej-6	77	13	1996	1996	NUM
alkej-6	77	14	,	,	PUNCT
alkej-6	77	15	"	"	PUNCT
alkej-6	77	16	neural	neural	ADJ
alkej-6	77	17	network	network	NOUN
alkej-6	77	18	algorithms	algorithm	NOUN
alkej-6	77	19	for	for	ADP
alkej-6	77	20	online	online	ADJ
alkej-6	77	21	principal	principal	ADJ
alkej-6	77	22	component	component	NOUN
alkej-6	77	23	analysis	analysis	NOUN
alkej-6	77	24	and	and	CCONJ
alkej-6	77	25	singular	singular	NOUN
alkej-6	77	26	value	value	NOUN
alkej-6	77	27	decomposition	decomposition	NOUN
alkej-6	77	28	"	"	PUNCT
alkej-6	77	29	,	,	PUNCT
alkej-6	77	30	tuien	tuien	NOUN
alkej-6	77	31	-	-	PUNCT
alkej-6	77	32	central	central	ADJ
alkej-6	77	33	for	for	ADP
alkej-6	77	34	computational	computational	ADJ
alkej-6	77	35	intelligence	intelligence	NOUN
alkej-6	77	36	.	.	PUNCT
alkej-6	78	1	n.	n.	PROPN
alkej-6	78	2	h.	h.	PROPN
alkej-6	78	3	abbas	abbas	PROPN
alkej-6	78	4	/al	/al	PROPN
alkej-6	78	5	-	-	PUNCT
alkej-6	78	6	khwarizmi	khwarizmi	PROPN
alkej-6	78	7	engineering	engineering	NOUN
alkej-6	78	8	journal	journal	NOUN
alkej-6	78	9	,	,	PUNCT
alkej-6	78	10	vol.2	vol.2	PROPN
alkej-6	78	11	,	,	PUNCT
alkej-6	78	12	no	no	INTJ
alkej-6	78	13	.	.	PUNCT
alkej-6	79	1	1,pp	1,pp	NUM
alkej-6	79	2	70	70	NUM
alkej-6	79	3	-	-	SYM
alkej-6	79	4	77	77	NUM
alkej-6	79	5	(	(	PUNCT
alkej-6	79	6	2006	2006	NUM
alkej-6	79	7	)	)	PUNCT
alkej-6	79	8	74	74	NUM
alkej-6	79	9	x	x	SYM
alkej-6	79	10	z	z	NOUN
alkej-6	79	11	θi	θi	PROPN
alkej-6	79	12	φi	φi	ADP
alkej-6	79	13	ith	ith	PROPN
alkej-6	79	14	plane	plane	NOUN
alkej-6	79	15	wave	wave	NOUN
alkej-6	79	16	figure	figure	NOUN
alkej-6	79	17	1	1	NUM
alkej-6	79	18	:	:	PUNCT
alkej-6	79	19	uniform	uniform	ADJ
alkej-6	79	20	circular	circular	ADJ
alkej-6	79	21	array	array	NOUN
alkej-6	79	22	the	the	DET
alkej-6	79	23	reference	reference	NOUN
alkej-6	79	24	sensor	sensor	NOUN
alkej-6	79	25	xn	xn	PROPN
alkej-6	79	26	.	.	PUNCT
alkej-6	80	1	x2	x2	PROPN
alkej-6	80	2	y1	y1	NOUN
alkej-6	81	1	y2	y2	INTJ
alkej-6	81	2	ym	ym	INTJ
alkej-6	81	3			X
alkej-6	81	4			X
alkej-6	81	5			X
alkej-6	81	6	.	.	PUNCT
alkej-6	81	7	.	.	PUNCT
alkej-6	81	8	.	.	PUNCT
alkej-6	81	9	.	.	PUNCT
alkej-6	81	10	.	.	PUNCT
alkej-6	82	1	figure	figure	VERB
alkej-6	82	2	2	2	NUM
alkej-6	82	3	:	:	PUNCT
alkej-6	82	4	the	the	DET
alkej-6	82	5	pca	pca	PROPN
alkej-6	82	6	neural	neural	ADJ
alkej-6	82	7	network	network	NOUN
alkej-6	82	8	.	.	PUNCT
alkej-6	83	1	x1	x1	PROPN
alkej-6	83	2	n.	n.	PROPN
alkej-6	83	3	h.	h.	PROPN
alkej-6	83	4	abbas	abbas	PROPN
alkej-6	83	5	/al	/al	PROPN
alkej-6	83	6	-	-	PUNCT
alkej-6	83	7	khwarizmi	khwarizmi	PROPN
alkej-6	83	8	engineering	engineering	NOUN
alkej-6	83	9	journal	journal	NOUN
alkej-6	83	10	,	,	PUNCT
alkej-6	83	11	vol.2	vol.2	PROPN
alkej-6	83	12	,	,	PUNCT
alkej-6	83	13	no	no	INTJ
alkej-6	83	14	.	.	PUNCT
alkej-6	84	1	1,pp	1,pp	NUM
alkej-6	84	2	70	70	NUM
alkej-6	84	3	-	-	SYM
alkej-6	84	4	77	77	NUM
alkej-6	84	5	(	(	PUNCT
alkej-6	84	6	2006	2006	NUM
alkej-6	84	7	)	)	PUNCT
alkej-6	84	8	75	75	NUM
alkej-6	84	9	figure	figure	NOUN
alkej-6	84	10	4	4	NUM
alkej-6	84	11	:	:	PUNCT
alkej-6	84	12	the	the	DET
alkej-6	84	13	azimuth	azimuth	PROPN
alkej-6	84	14	angle	angle	NOUN
alkej-6	84	15	in	in	ADP
alkej-6	84	16	degree	degree	NOUN
alkej-6	84	17	the	the	DET
alkej-6	84	18	azimuth	azimuth	NOUN
alkej-6	84	19	angle	angle	NOUN
alkej-6	84	20	in	in	ADP
alkej-6	84	21	degree	degree	NOUN
alkej-6	84	22	t	t	PROPN
alkej-6	84	23	h	h	NOUN
alkej-6	84	24	e	e	PROPN
alkej-6	84	25	n	n	NUM
alkej-6	84	26	o	o	X
alkej-6	84	27	rm	rm	NOUN
alkej-6	85	1	al	al	PROPN
alkej-6	85	2	iz	iz	INTJ
alkej-6	86	1	ed	ed	PROPN
alkej-6	86	2	s	s	PROPN
alkej-6	86	3	p	p	X
alkej-6	86	4	ec	ec	PROPN
alkej-6	86	5	tr	tr	PROPN
alkej-6	86	6	u	u	PROPN
alkej-6	86	7	m	m	NOUN
alkej-6	86	8	figure	figure	NOUN
alkej-6	86	9	3	3	NUM
alkej-6	86	10	:	:	PUNCT
alkej-6	86	11	the	the	DET
alkej-6	86	12	doa(	doa(	NOUN
alkej-6	86	13	,	,	PUNCT
alkej-6	86	14			NOUN
alkej-6	86	15	)	)	PUNCT
alkej-6	86	16	.	.	PUNCT
alkej-6	87	1	n.	n.	PROPN
alkej-6	87	2	h.	h.	PROPN
alkej-6	87	3	abbas	abbas	PROPN
alkej-6	87	4	/al	/al	PROPN
alkej-6	87	5	-	-	PUNCT
alkej-6	87	6	khwarizmi	khwarizmi	PROPN
alkej-6	87	7	engineering	engineering	NOUN
alkej-6	87	8	journal	journal	NOUN
alkej-6	87	9	,	,	PUNCT
alkej-6	87	10	vol.2	vol.2	PROPN
alkej-6	87	11	,	,	PUNCT
alkej-6	87	12	no	no	INTJ
alkej-6	87	13	.	.	PUNCT
alkej-6	88	1	1,pp	1,pp	NUM
alkej-6	88	2	70	70	NUM
alkej-6	88	3	-	-	SYM
alkej-6	88	4	77	77	NUM
alkej-6	88	5	(	(	PUNCT
alkej-6	88	6	2006	2006	NUM
alkej-6	88	7	)	)	PUNCT
alkej-6	88	8	76	76	NUM
alkej-6	88	9	t	t	NOUN
alkej-6	88	10	h	h	NOUN
alkej-6	88	11	e	e	PROPN
alkej-6	88	12	n	n	NUM
alkej-6	88	13	o	o	X
alkej-6	88	14	rm	rm	NOUN
alkej-6	89	1	al	al	PROPN
alkej-6	89	2	iz	iz	INTJ
alkej-6	90	1	ed	ed	PROPN
alkej-6	90	2	s	s	PROPN
alkej-6	90	3	p	p	X
alkej-6	90	4	ec	ec	PROPN
alkej-6	90	5	tr	tr	PROPN
alkej-6	90	6	u	u	PROPN
alkej-6	90	7	m	m	NOUN
alkej-6	90	8	figure	figure	NOUN
alkej-6	90	9	5	5	NUM
alkej-6	90	10	:	:	PUNCT
alkej-6	90	11	the	the	DET
alkej-6	90	12	elevation	elevation	NOUN
alkej-6	90	13	angle	angle	NOUN
alkej-6	90	14	in	in	ADP
alkej-6	90	15	degree	degree	NOUN
alkej-6	90	16	n.	n.	PROPN
alkej-6	90	17	h.	h.	PROPN
alkej-6	90	18	abbas	abbas	PROPN
alkej-6	90	19	/al	/al	PROPN
alkej-6	90	20	-	-	PUNCT
alkej-6	90	21	khwarizmi	khwarizmi	PROPN
alkej-6	90	22	engineering	engineering	NOUN
alkej-6	90	23	journal	journal	NOUN
alkej-6	90	24	,	,	PUNCT
alkej-6	90	25	vol.2	vol.2	PROPN
alkej-6	90	26	,	,	PUNCT
alkej-6	90	27	no	no	INTJ
alkej-6	90	28	.	.	PUNCT
alkej-6	91	1	1,pp	1,pp	NUM
alkej-6	91	2	70	70	NUM
alkej-6	91	3	-	-	SYM
alkej-6	91	4	77	77	NUM
alkej-6	91	5	(	(	PUNCT
alkej-6	91	6	2006	2006	NUM
alkej-6	91	7	)	)	PUNCT
alkej-6	91	8	77	77	NUM
alkej-6	91	9	مع	مع	INTJ
alkej-6	91	10	الشبكات	الشبكات	PROPN
alkej-6	91	11	العصبية	العصبية	PROPN
alkej-6	91	12	ghaايجاد	ghaايجاد	PROPN
alkej-6	91	13	االتجاه	االتجاه	PROPN
alkej-6	91	14	باستخدام	باستخدام	NOUN
alkej-6	91	15	خوارزمية	خوارزمية	ADJ
alkej-6	91	16	نزار	نزار	PROPN
alkej-6	91	17	هادي	هادي	NOUN
alkej-6	91	18	عباس	عباس	VERB
alkej-6	91	19	ة	ة	ADP
alkej-6	91	20	/جامعة	/جامعة	NOUN
alkej-6	91	21	بغدادكلية	بغدادكلية	VERB
alkej-6	91	22	الهندس	الهندس	PRON
alkej-6	91	23	/قسم	/قسم	PUNCT
alkej-6	92	1	الهندسة	الهندسة	VERB
alkej-6	92	2	الكهربائية	الكهربائية	NOUN
alkej-6	92	3	:	:	PUNCT
alkej-6	92	4	الخالصة	الخالصة	NOUN
alkej-6	92	5	خوارزمياة	خوارزمياة	NOUN
alkej-6	92	6	ماع	ماع	PROPN
alkej-6	92	7	الاذاتي	الاذاتي	VERB
alkej-6	92	8	التعنايم	التعنايم	PROPN
alkej-6	92	9	ذات	ذات	PROPN
alkej-6	92	10	العصابية	العصابية	PROPN
alkej-6	92	11	الشابكة	الشابكة	PROPN
alkej-6	92	12	اساتعمننا	اساتعمننا	PROPN
alkej-6	92	13	حياث	حياث	PROPN
alkej-6	92	14	.	.	PUNCT
alkej-6	93	1	الوصاو	الوصاو	PROPN
alkej-6	93	2	زاوياة	زاوياة	PROPN
alkej-6	93	3	إليجااد	إليجااد	VERB
alkej-6	93	4	عصبية	عصبية	NOUN
alkej-6	93	5	شبكة	شبكة	PROPN
alkej-6	93	6	تصميم	تصميم	NOUN
alkej-6	93	7	تم	تم	PROPN
alkej-6	93	8	البحث	البحث	PROPN
alkej-6	93	9	هذا	هذا	PROPN
alkej-6	93	10	في	في	PRON
alkej-6	93	11	gha	gha	PROPN
alkej-6	93	12	كاابون	كاابون	PROPN
alkej-6	93	13	بطريقاة	بطريقاة	PROPN
alkej-6	93	14	تستخدم	تستخدم	PROPN
alkej-6	93	15	بدورها	بدورها	VERB
alkej-6	93	16	التيو	التيو	ADJ
alkej-6	93	17	الدائري	الدائري	PROPN
alkej-6	93	18	الترتيب	الترتيب	PROPN
alkej-6	93	19	ذات	ذات	NOUN
alkej-6	93	20	الهوائيات	الهوائيات	ADV
alkej-6	93	21	قب	قب	ADP
alkej-6	93	22	من	من	PRON
alkej-6	93	23	ةالمستنم	ةالمستنم	PROPN
alkej-6	93	24	لإلشارة	لإلشارة	PROPN
alkej-6	93	25	األساسية	األساسية	PROPN
alkej-6	93	26	المركبات	المركبات	PROPN
alkej-6	93	27	النتزاع	النتزاع	PROPN
alkej-6	93	28	(	(	PUNCT
alkej-6	93	29	كاابون	كاابون	PROPN
alkej-6	93	30	بطريقاة	بطريقاة	PROPN
alkej-6	93	31	يساتخدم	يساتخدم	PROPN
alkej-6	93	32	بادوره	بادوره	NOUN
alkej-6	93	33	الاذيتاخاذ	الاذيتاخاذ	NOUN
alkej-6	94	1	جازم	جازم	PROPN
alkej-6	94	2	مان	مان	PROPN
alkej-6	94	3	ف	ف	PRON
alkej-6	94	4	اام	اام	PROPN
alkej-6	94	5	االشاارة	االشاارة	PROPN
alkej-6	94	6	pca	pca	PROPN
alkej-6	94	7	أ	أ	PROPN
alkej-6	94	8	العصابية	العصابية	ADJ
alkej-6	94	9	الشبكةان	الشبكةان	ADJ
alkej-6	94	10	حيث	حيث	NOUN
alkej-6	94	11	.	.	PUNCT
alkej-6	95	1	الوصو	الوصو	PROPN
alkej-6	95	2	زاوية	زاوية	PROPN
alkej-6	95	3	يجادإل	يجادإل	PROPN
alkej-6	95	4	.ال	.ال	PUNCT
alkej-6	96	1	و	و	PRON
alkej-6	96	2	ام	ام	INTJ
alkej-6	97	1	ف	ف	INTJ
alkej-6	97	2	ام	ام	INTJ
alkej-6	97	3	هم	هم	INTJ
alkej-6	97	4	وت	وت	INTJ