id	sid	tid	token	lemma	pos
alkej-30	1	1	artificial	artificial	ADJ
alkej-30	1	2	neural	neural	ADJ
alkej-30	1	3	networks	network	NOUN
alkej-30	1	4	(	(	PUNCT
alkej-30	1	5	anns	anns	PROPN
alkej-30	1	6	)	)	PUNCT
alkej-30	1	7	are	be	AUX
alkej-30	1	8	a	a	DET
alkej-30	1	9	form	form	NOUN
alkej-30	1	10	of	of	ADP
alkej-30	1	11	artificial	artificial	ADJ
alkej-30	1	12	intelligence	intelligence	NOUN
alkej-30	1	13	,	,	PUNCT
alkej-30	1	14	which	which	PRON
alkej-30	1	15	have	have	AUX
alkej-30	1	16	proven	prove	VERB
alkej-30	1	17	useful	useful	ADJ
alkej-30	1	18	in	in	ADP
alkej-30	1	19	different	different	ADJ
alkej-30	1	20	areas	area	NOUN
alkej-30	1	21	of	of	ADP
alkej-30	1	22	application	application	NOUN
alkej-30	1	23	,	,	PUNCT
alkej-30	1	24	such	such	ADJ
alkej-30	1	25	as	as	ADP
alkej-30	1	26	pattern	pattern	NOUN
alkej-30	1	27	recognition	recognition	NOUN
alkej-30	2	1	[	[	X
alkej-30	2	2	1	1	X
alkej-30	2	3	]	]	PUNCT
alkej-30	2	4	and	and	CCONJ
alkej-30	2	5	function	function	VERB
alkej-30	2	6	approximation/	approximation/	NUM
alkej-30	2	7	prediction	prediction	NOUN
alkej-30	3	1	[	[	X
alkej-30	3	2	2	2	NUM
alkej-30	3	3	]	]	PUNCT
alkej-30	3	4	ammar	ammar	PROPN
alkej-30	3	5	a.	a.	PROPN
alkej-30	3	6	hassan	hassan	PROPN
alkej-30	3	7	/al	/al	PROPN
alkej-30	3	8	-	-	PUNCT
alkej-30	3	9	khwarizmi	khwarizmi	PROPN
alkej-30	3	10	engineering	engineering	NOUN
alkej-30	3	11	journal	journal	PROPN
alkej-30	3	12	,	,	PUNCT
alkej-30	3	13	vol.2	vol.2	PROPN
alkej-30	3	14	,	,	PUNCT
alkej-30	3	15	no	no	INTJ
alkej-30	3	16	.	.	NOUN
alkej-30	3	17	2	2	NUM
alkej-30	3	18	pp	pp	ADP
alkej-30	3	19	32	32	NUM
alkej-30	3	20	-	-	SYM
alkej-30	3	21	41	41	NUM
alkej-30	3	22	(	(	PUNCT
alkej-30	3	23	2006	2006	NUM
alkej-30	3	24	)	)	PUNCT
alkej-30	3	25	23	23	NUM
alkej-30	3	26	low	low	ADJ
alkej-30	3	27	cost	cost	NOUN
alkej-30	3	28	hardware	hardware	NOUN
alkej-30	3	29	back	back	NOUN
alkej-30	3	30	propagation	propagation	NOUN
alkej-30	3	31	algorithm	algorithm	NOUN
alkej-30	3	32	ammar	ammar	PROPN
alkej-30	3	33	a.	a.	PROPN
alkej-30	3	34	hassan	hassan	PROPN
alkej-30	3	35	computer	computer	PROPN
alkej-30	3	36	engineering	engineering	PROPN
alkej-30	3	37	department	department	PROPN
alkej-30	3	38	/	/	SYM
alkej-30	3	39	college	college	PROPN
alkej-30	3	40	of	of	ADP
alkej-30	3	41	engineering	engineering	PROPN
alkej-30	3	42	university	university	PROPN
alkej-30	3	43	of	of	ADP
alkej-30	3	44	baghdad	baghdad	PROPN
alkej-30	3	45	(	(	PUNCT
alkej-30	3	46	received	receive	VERB
alkej-30	3	47	14	14	NUM
alkej-30	3	48	november	november	PROPN
alkej-30	3	49	2005	2005	NUM
alkej-30	3	50	;	;	PUNCT
alkej-30	3	51	accepted	accept	VERB
alkej-30	3	52	4	4	NUM
alkej-30	3	53	april	april	PROPN
alkej-30	3	54	2006	2006	NUM
alkej-30	3	55	)	)	PUNCT
alkej-30	4	1	abstract	abstract	NOUN
alkej-30	4	2	:	:	PUNCT
alkej-30	4	3	the	the	DET
alkej-30	4	4	first	first	ADJ
alkej-30	4	5	successful	successful	ADJ
alkej-30	4	6	implementation	implementation	NOUN
alkej-30	4	7	of	of	ADP
alkej-30	4	8	artificial	artificial	ADJ
alkej-30	4	9	neural	neural	ADJ
alkej-30	4	10	networks	network	NOUN
alkej-30	4	11	(	(	PUNCT
alkej-30	4	12	anns	anns	PROPN
alkej-30	4	13	)	)	PUNCT
alkej-30	4	14	was	be	AUX
alkej-30	4	15	published	publish	VERB
alkej-30	4	16	a	a	DET
alkej-30	4	17	little	little	ADJ
alkej-30	4	18	over	over	ADP
alkej-30	4	19	a	a	DET
alkej-30	4	20	decade	decade	NOUN
alkej-30	4	21	ago	ago	ADV
alkej-30	4	22	.	.	PUNCT
alkej-30	5	1	it	it	PRON
alkej-30	5	2	is	be	AUX
alkej-30	5	3	time	time	NOUN
alkej-30	5	4	to	to	PART
alkej-30	5	5	review	review	VERB
alkej-30	5	6	the	the	DET
alkej-30	5	7	progress	progress	NOUN
alkej-30	5	8	that	that	PRON
alkej-30	5	9	has	have	AUX
alkej-30	5	10	been	be	AUX
alkej-30	5	11	made	make	VERB
alkej-30	5	12	in	in	ADP
alkej-30	5	13	this	this	DET
alkej-30	5	14	research	research	NOUN
alkej-30	5	15	area	area	NOUN
alkej-30	5	16	.	.	PUNCT
alkej-30	6	1	this	this	DET
alkej-30	6	2	paper	paper	NOUN
alkej-30	6	3	provides	provide	VERB
alkej-30	6	4	taxonomy	taxonomy	NOUN
alkej-30	6	5	for	for	ADP
alkej-30	6	6	classifying	classify	VERB
alkej-30	6	7	field	field	NOUN
alkej-30	6	8	programmable	programmable	ADJ
alkej-30	6	9	gate	gate	NOUN
alkej-30	6	10	arrays	array	NOUN
alkej-30	6	11	(	(	PUNCT
alkej-30	6	12	fpgas	fpgas	NOUN
alkej-30	6	13	)	)	PUNCT
alkej-30	6	14	implementation	implementation	NOUN
alkej-30	6	15	of	of	ADP
alkej-30	6	16	anns	ann	NOUN
alkej-30	6	17	.	.	PUNCT
alkej-30	7	1	different	different	ADJ
alkej-30	7	2	implementation	implementation	NOUN
alkej-30	7	3	techniques	technique	NOUN
alkej-30	7	4	and	and	CCONJ
alkej-30	7	5	design	design	NOUN
alkej-30	7	6	issues	issue	NOUN
alkej-30	7	7	are	be	AUX
alkej-30	7	8	discussed	discuss	VERB
alkej-30	7	9	,	,	PUNCT
alkej-30	7	10	such	such	ADJ
alkej-30	7	11	as	as	ADP
alkej-30	7	12	obtaining	obtain	VERB
alkej-30	7	13	a	a	DET
alkej-30	7	14	suitable	suitable	ADJ
alkej-30	7	15	activation	activation	NOUN
alkej-30	7	16	function	function	NOUN
alkej-30	7	17	and	and	CCONJ
alkej-30	7	18	numerical	numerical	ADJ
alkej-30	7	19	truncation	truncation	NOUN
alkej-30	7	20	technique	technique	NOUN
alkej-30	7	21	trade	trade	NOUN
alkej-30	7	22	-	-	PUNCT
alkej-30	7	23	off	off	NOUN
alkej-30	7	24	,	,	PUNCT
alkej-30	7	25	the	the	DET
alkej-30	7	26	improvement	improvement	NOUN
alkej-30	7	27	of	of	ADP
alkej-30	7	28	the	the	DET
alkej-30	7	29	learning	learn	VERB
alkej-30	7	30	algorithm	algorithm	NOUN
alkej-30	7	31	to	to	PART
alkej-30	7	32	reduce	reduce	VERB
alkej-30	7	33	the	the	DET
alkej-30	7	34	cost	cost	NOUN
alkej-30	7	35	of	of	ADP
alkej-30	7	36	neuron	neuron	NOUN
alkej-30	7	37	and	and	CCONJ
alkej-30	7	38	in	in	ADP
alkej-30	7	39	result	result	NOUN
alkej-30	7	40	the	the	DET
alkej-30	7	41	total	total	ADJ
alkej-30	7	42	cost	cost	NOUN
alkej-30	7	43	and	and	CCONJ
alkej-30	7	44	the	the	DET
alkej-30	7	45	total	total	ADJ
alkej-30	7	46	speed	speed	NOUN
alkej-30	7	47	of	of	ADP
alkej-30	7	48	the	the	DET
alkej-30	7	49	complete	complete	ADJ
alkej-30	7	50	ann	ann	PROPN
alkej-30	7	51	.	.	PUNCT
alkej-30	8	1	finally	finally	ADV
alkej-30	8	2	,	,	PUNCT
alkej-30	8	3	the	the	DET
alkej-30	8	4	implementation	implementation	NOUN
alkej-30	8	5	of	of	ADP
alkej-30	8	6	a	a	DET
alkej-30	8	7	complete	complete	ADJ
alkej-30	8	8	very	very	ADV
alkej-30	8	9	fast	fast	ADJ
alkej-30	8	10	circuit	circuit	NOUN
alkej-30	8	11	for	for	ADP
alkej-30	8	12	the	the	DET
alkej-30	8	13	pattern	pattern	NOUN
alkej-30	8	14	of	of	ADP
alkej-30	8	15	english	english	ADJ
alkej-30	8	16	digit	digit	NOUN
alkej-30	8	17	numbers	number	NOUN
alkej-30	8	18	nn	nn	PROPN
alkej-30	8	19	has	have	VERB
alkej-30	8	20	four	four	NUM
alkej-30	8	21	layers	layer	NOUN
alkej-30	8	22	of	of	ADP
alkej-30	8	23	70	70	NUM
alkej-30	8	24	nodes	node	NOUN
alkej-30	8	25	(	(	PUNCT
alkej-30	8	26	neurons	neuron	NOUN
alkej-30	8	27	)	)	PUNCT
alkej-30	8	28	on	on	ADP
alkej-30	8	29	single	single	ADJ
alkej-30	8	30	chip	chip	NOUN
alkej-30	8	31	using	use	VERB
alkej-30	8	32	xilinx	xilinx	PROPN
alkej-30	8	33	fpga	fpga	PROPN
alkej-30	8	34	technique	technique	NOUN
alkej-30	8	35	is	be	AUX
alkej-30	8	36	given	give	VERB
alkej-30	8	37	.	.	PUNCT
alkej-30	9	1	the	the	DET
alkej-30	9	2	main	main	ADJ
alkej-30	9	3	goal	goal	NOUN
alkej-30	9	4	of	of	ADP
alkej-30	9	5	this	this	DET
alkej-30	9	6	paper	paper	NOUN
alkej-30	9	7	is	be	AUX
alkej-30	9	8	how	how	SCONJ
alkej-30	9	9	to	to	PART
alkej-30	9	10	achieve	achieve	VERB
alkej-30	9	11	the	the	DET
alkej-30	9	12	suitable	suitable	ADJ
alkej-30	9	13	activation	activation	NOUN
alkej-30	9	14	function	function	NOUN
alkej-30	9	15	and	and	CCONJ
alkej-30	9	16	weights	weight	NOUN
alkej-30	9	17	for	for	ADP
alkej-30	9	18	this	this	DET
alkej-30	9	19	network	network	NOUN
alkej-30	9	20	that	that	PRON
alkej-30	9	21	gives	give	VERB
alkej-30	9	22	minimum	minimum	ADJ
alkej-30	9	23	hardware	hardware	NOUN
alkej-30	9	24	cost	cost	NOUN
alkej-30	9	25	when	when	SCONJ
alkej-30	9	26	all	all	DET
alkej-30	9	27	stages	stage	NOUN
alkej-30	9	28	of	of	ADP
alkej-30	9	29	this	this	DET
alkej-30	9	30	ann	ann	PROPN
alkej-30	9	31	algorithm	algorithm	NOUN
alkej-30	9	32	is	be	AUX
alkej-30	9	33	implemented	implement	VERB
alkej-30	9	34	on	on	ADP
alkej-30	9	35	fpga	fpga	PROPN
alkej-30	9	36	.	.	PUNCT
alkej-30	10	1	1.introduction	1.introduction	NUM
alkej-30	10	2	artificial	artificial	ADJ
alkej-30	10	3	neural	neural	ADJ
alkej-30	10	4	networks	network	NOUN
alkej-30	10	5	(	(	PUNCT
alkej-30	10	6	anns	anns	PROPN
alkej-30	10	7	)	)	PUNCT
alkej-30	10	8	are	be	AUX
alkej-30	10	9	a	a	DET
alkej-30	10	10	form	form	NOUN
alkej-30	10	11	of	of	ADP
alkej-30	10	12	artificial	artificial	ADJ
alkej-30	10	13	intelligence	intelligence	NOUN
alkej-30	10	14	,	,	PUNCT
alkej-30	10	15	which	which	PRON
alkej-30	10	16	have	have	AUX
alkej-30	10	17	proven	prove	VERB
alkej-30	10	18	useful	useful	ADJ
alkej-30	10	19	in	in	ADP
alkej-30	10	20	different	different	ADJ
alkej-30	10	21	areas	area	NOUN
alkej-30	10	22	of	of	ADP
alkej-30	10	23	application	application	NOUN
alkej-30	10	24	,	,	PUNCT
alkej-30	10	25	such	such	ADJ
alkej-30	10	26	as	as	ADP
alkej-30	10	27	pattern	pattern	NOUN
alkej-30	10	28	recognition	recognition	NOUN
alkej-30	11	1	[	[	X
alkej-30	11	2	1	1	X
alkej-30	11	3	]	]	PUNCT
alkej-30	11	4	and	and	CCONJ
alkej-30	11	5	function	function	VERB
alkej-30	11	6	approximation/	approximation/	NUM
alkej-30	11	7	prediction	prediction	NOUN
alkej-30	12	1	[	[	X
alkej-30	12	2	2	2	NUM
alkej-30	12	3	]	]	PUNCT
alkej-30	12	4	.	.	PUNCT
alkej-30	13	1	the	the	DET
alkej-30	13	2	most	most	ADV
alkej-30	13	3	popular	popular	ADJ
alkej-30	13	4	neural	neural	ADJ
alkej-30	13	5	network	network	NOUN
alkej-30	13	6	is	be	AUX
alkej-30	13	7	the	the	DET
alkej-30	13	8	multi	multi	ADJ
alkej-30	13	9	-	-	ADJ
alkej-30	13	10	layer	layer	ADJ
alkej-30	13	11	perceptron	perceptron	NOUN
alkej-30	13	12	trained	train	VERB
alkej-30	13	13	using	use	VERB
alkej-30	13	14	the	the	DET
alkej-30	13	15	error	error	NOUN
alkej-30	13	16	back	back	NOUN
alkej-30	13	17	propagation	propagation	NOUN
alkej-30	13	18	algorithm	algorithm	NOUN
alkej-30	13	19	[	[	X
alkej-30	13	20	3	3	NUM
alkej-30	13	21	]	]	PUNCT
alkej-30	13	22	.	.	PUNCT
alkej-30	14	1	however	however	ADV
alkej-30	14	2	,	,	PUNCT
alkej-30	14	3	an	an	DET
alkej-30	14	4	important	important	ADJ
alkej-30	14	5	obstacle	obstacle	NOUN
alkej-30	14	6	in	in	ADP
alkej-30	14	7	using	use	VERB
alkej-30	14	8	this	this	DET
alkej-30	14	9	network	network	NOUN
alkej-30	14	10	in	in	ADP
alkej-30	14	11	many	many	ADJ
alkej-30	14	12	applications	application	NOUN
alkej-30	14	13	is	be	AUX
alkej-30	14	14	the	the	DET
alkej-30	14	15	slow	slow	ADJ
alkej-30	14	16	training	training	NOUN
alkej-30	14	17	and	and	CCONJ
alkej-30	14	18	the	the	DET
alkej-30	14	19	lack	lack	NOUN
alkej-30	14	20	of	of	ADP
alkej-30	14	21	clear	clear	ADJ
alkej-30	14	22	methodology	methodology	NOUN
alkej-30	14	23	to	to	PART
alkej-30	14	24	determine	determine	VERB
alkej-30	14	25	the	the	DET
alkej-30	14	26	network	network	NOUN
alkej-30	14	27	topology	topology	NOUN
alkej-30	14	28	before	before	SCONJ
alkej-30	14	29	training	training	NOUN
alkej-30	14	30	starts	start	NOUN
alkej-30	14	31	.	.	PUNCT
alkej-30	15	1	it	it	PRON
alkej-30	15	2	is	be	AUX
alkej-30	15	3	then	then	ADV
alkej-30	15	4	desirable	desirable	ADJ
alkej-30	15	5	to	to	PART
alkej-30	15	6	speedup	speedup	VERB
alkej-30	15	7	the	the	DET
alkej-30	15	8	training	training	NOUN
alkej-30	15	9	and	and	CCONJ
alkej-30	15	10	allow	allow	VERB
alkej-30	15	11	fast	fast	ADJ
alkej-30	15	12	experimentation	experimentation	NOUN
alkej-30	15	13	with	with	ADP
alkej-30	15	14	various	various	ADJ
alkej-30	15	15	topologies	topology	NOUN
alkej-30	15	16	.	.	PUNCT
alkej-30	16	1	one	one	NUM
alkej-30	16	2	possible	possible	ADJ
alkej-30	16	3	solution	solution	NOUN
alkej-30	16	4	is	be	AUX
alkej-30	16	5	an	an	DET
alkej-30	16	6	implementation	implementation	NOUN
alkej-30	16	7	on	on	ADP
alkej-30	16	8	a	a	DET
alkej-30	16	9	reconfigurable	reconfigurable	ADJ
alkej-30	16	10	computing	computing	NOUN
alkej-30	16	11	platform	platform	NOUN
alkej-30	16	12	(	(	PUNCT
alkej-30	16	13	e.g	e.g	X
alkej-30	16	14	field	field	NOUN
alkej-30	16	15	programmable	programmable	ADJ
alkej-30	16	16	gate	gate	NOUN
alkej-30	16	17	arrays	array	VERB
alkej-30	16	18	)	)	PUNCT
alkej-30	16	19	fpga	fpga	PROPN
alkej-30	16	20	.	.	PUNCT
alkej-30	17	1	reconfigurable	reconfigurable	ADJ
alkej-30	17	2	computing	computing	NOUN
alkej-30	17	3	is	be	AUX
alkej-30	17	4	a	a	DET
alkej-30	17	5	means	means	NOUN
alkej-30	17	6	of	of	ADP
alkej-30	17	7	increasing	increase	VERB
alkej-30	17	8	the	the	DET
alkej-30	17	9	processing	processing	NOUN
alkej-30	17	10	density	density	NOUN
alkej-30	17	11	(	(	PUNCT
alkej-30	17	12	i.e.	i.e.	X
alkej-30	17	13	greater	great	ADJ
alkej-30	17	14	performance	performance	NOUN
alkej-30	17	15	per	per	ADP
alkej-30	17	16	unit	unit	NOUN
alkej-30	17	17	of	of	ADP
alkej-30	17	18	silicon	silicon	PROPN
alkej-30	17	19	area	area	PROPN
alkej-30	17	20	)	)	PUNCT
alkej-30	17	21	above	above	ADV
alkej-30	17	22	and	and	CCONJ
alkej-30	17	23	beyond	beyond	ADP
alkej-30	17	24	that	that	PRON
alkej-30	17	25	provided	provide	VERB
alkej-30	17	26	by	by	ADP
alkej-30	17	27	general	general	ADJ
alkej-30	17	28	-	-	PUNCT
alkej-30	17	29	purpose	purpose	NOUN
alkej-30	17	30	computing	compute	VERB
alkej-30	17	31	platform	platform	NOUN
alkej-30	17	32	[	[	X
alkej-30	17	33	4	4	NUM
alkej-30	17	34	]	]	PUNCT
alkej-30	17	35	.	.	PUNCT
alkej-30	18	1	field	field	PROPN
alkej-30	18	2	programmable	programmable	ADJ
alkej-30	18	3	gate	gate	NOUN
alkej-30	18	4	arrays	array	NOUN
alkej-30	18	5	(	(	PUNCT
alkej-30	18	6	fpgas	fpgas	NOUN
alkej-30	18	7	)	)	PUNCT
alkej-30	18	8	are	be	AUX
alkej-30	18	9	a	a	DET
alkej-30	18	10	medium	medium	NOUN
alkej-30	18	11	that	that	PRON
alkej-30	18	12	can	can	AUX
alkej-30	18	13	be	be	AUX
alkej-30	18	14	used	use	VERB
alkej-30	18	15	for	for	ADP
alkej-30	18	16	reconfigurable	reconfigurable	ADJ
alkej-30	18	17	computing	computing	NOUN
alkej-30	18	18	,	,	PUNCT
alkej-30	18	19	since	since	SCONJ
alkej-30	18	20	they	they	PRON
alkej-30	18	21	allow	allow	VERB
alkej-30	18	22	for	for	ADP
alkej-30	18	23	custom	custom	NOUN
alkej-30	18	24	design	design	NOUN
alkej-30	18	25	of	of	ADP
alkej-30	18	26	fine	fine	ADJ
alkej-30	18	27	-	-	PUNCT
alkej-30	18	28	grain	grain	NOUN
alkej-30	18	29	logic	logic	NOUN
alkej-30	18	30	compared	compare	VERB
alkej-30	18	31	to	to	ADP
alkej-30	18	32	course	course	ADJ
alkej-30	18	33	-	-	PUNCT
alkej-30	18	34	grain	grain	NOUN
alkej-30	18	35	logic	logic	NOUN
alkej-30	18	36	found	find	VERB
alkej-30	18	37	in	in	ADP
alkej-30	18	38	general	general	ADJ
alkej-30	18	39	-	-	PUNCT
alkej-30	18	40	purpose	purpose	NOUN
alkej-30	18	41	computing	computing	NOUN
alkej-30	18	42	platforms	platform	NOUN
alkej-30	18	43	.	.	PUNCT
alkej-30	19	1	fpgas	fpga	NOUN
alkej-30	19	2	are	be	AUX
alkej-30	19	3	a	a	DET
alkej-30	19	4	form	form	NOUN
alkej-30	19	5	of	of	ADP
alkej-30	19	6	programmable	programmable	ADJ
alkej-30	19	7	logic	logic	NOUN
alkej-30	19	8	,	,	PUNCT
alkej-30	19	9	which	which	PRON
alkej-30	19	10	offer	offer	VERB
alkej-30	19	11	flexibility	flexibility	NOUN
alkej-30	19	12	in	in	ADP
alkej-30	19	13	design	design	NOUN
alkej-30	19	14	like	like	ADP
alkej-30	19	15	software	software	NOUN
alkej-30	19	16	,	,	PUNCT
alkej-30	19	17	but	but	CCONJ
alkej-30	19	18	with	with	ADP
alkej-30	19	19	performance	performance	NOUN
alkej-30	19	20	speeds	speed	NOUN
alkej-30	19	21	closer	close	ADV
alkej-30	19	22	to	to	AUX
alkej-30	19	23	application	application	VERB
alkej-30	19	24	specific	specific	ADJ
alkej-30	19	25	integrated	integrate	VERB
alkej-30	19	26	circuits	circuit	NOUN
alkej-30	19	27	(	(	PUNCT
alkej-30	19	28	asics	asic	NOUN
alkej-30	19	29	)	)	PUNCT
alkej-30	19	30	.	.	PUNCT
alkej-30	20	1	with	with	ADP
alkej-30	20	2	the	the	DET
alkej-30	20	3	ability	ability	NOUN
alkej-30	20	4	to	to	PART
alkej-30	20	5	be	be	AUX
alkej-30	20	6	reconfigured	reconfigure	VERB
alkej-30	20	7	an	an	DET
alkej-30	20	8	endless	endless	ADJ
alkej-30	20	9	amount	amount	NOUN
alkej-30	20	10	of	of	ADP
alkej-30	20	11	al	al	PROPN
alkej-30	20	12	-	-	PUNCT
alkej-30	20	13	khwarizmi	khwarizmi	PROPN
alkej-30	20	14	engineering	engineering	PROPN
alkej-30	20	15	journal	journal	PROPN
alkej-30	20	16	al	al	PROPN
alkej-30	20	17	-	-	PUNCT
alkej-30	20	18	khwarizmi	khwarizmi	PROPN
alkej-30	20	19	engineering	engineering	NOUN
alkej-30	20	20	journal	journal	PROPN
alkej-30	20	21	,	,	PUNCT
alkej-30	20	22	vol.2,no.2,pp	vol.2,no.2,pp	NOUN
alkej-30	20	23	32	32	NUM
alkej-30	20	24	-	-	SYM
alkej-30	20	25	41	41	NUM
alkej-30	20	26	(	(	PUNCT
alkej-30	20	27	2006	2006	NUM
alkej-30	20	28	)	)	PUNCT
alkej-30	20	29	ammar	ammar	PROPN
alkej-30	20	30	a.	a.	PROPN
alkej-30	20	31	hassan	hassan	PROPN
alkej-30	20	32	/al	/al	PROPN
alkej-30	20	33	-	-	PUNCT
alkej-30	20	34	khwarizmi	khwarizmi	PROPN
alkej-30	20	35	engineering	engineering	NOUN
alkej-30	20	36	journal	journal	PROPN
alkej-30	20	37	,	,	PUNCT
alkej-30	20	38	vol.2	vol.2	PROPN
alkej-30	20	39	,	,	PUNCT
alkej-30	20	40	no	no	INTJ
alkej-30	20	41	.	.	NOUN
alkej-30	20	42	2	2	NUM
alkej-30	20	43	pp	pp	ADP
alkej-30	20	44	32	32	NUM
alkej-30	20	45	-	-	SYM
alkej-30	20	46	41	41	NUM
alkej-30	20	47	(	(	PUNCT
alkej-30	20	48	2006	2006	NUM
alkej-30	20	49	)	)	PUNCT
alkej-30	20	50	22	22	NUM
alkej-30	20	51	times	time	NOUN
alkej-30	20	52	after	after	SCONJ
alkej-30	20	53	it	it	PRON
alkej-30	20	54	has	have	AUX
alkej-30	20	55	already	already	ADV
alkej-30	20	56	been	be	AUX
alkej-30	20	57	manufactured	manufacture	VERB
alkej-30	20	58	,	,	PUNCT
alkej-30	20	59	fpgas	fpga	NOUN
alkej-30	20	60	have	have	AUX
alkej-30	20	61	traditionally	traditionally	ADV
alkej-30	20	62	been	be	AUX
alkej-30	20	63	used	use	VERB
alkej-30	20	64	as	as	ADP
alkej-30	20	65	a	a	DET
alkej-30	20	66	prototyping	prototype	VERB
alkej-30	20	67	tool	tool	NOUN
alkej-30	20	68	for	for	ADP
alkej-30	20	69	hardware	hardware	NOUN
alkej-30	20	70	designers	designer	NOUN
alkej-30	20	71	.	.	PUNCT
alkej-30	21	1	however	however	ADV
alkej-30	21	2	,	,	PUNCT
alkej-30	21	3	as	as	SCONJ
alkej-30	21	4	growing	grow	VERB
alkej-30	21	5	die	die	NOUN
alkej-30	21	6	capacities	capacity	NOUN
alkej-30	21	7	of	of	ADP
alkej-30	21	8	fpgas	fpgas	NOUN
alkej-30	21	9	have	have	AUX
alkej-30	21	10	increased	increase	VERB
alkej-30	21	11	over	over	ADP
alkej-30	21	12	the	the	DET
alkej-30	21	13	years	year	NOUN
alkej-30	21	14	,	,	PUNCT
alkej-30	21	15	so	so	ADV
alkej-30	21	16	has	have	VERB
alkej-30	21	17	their	their	PRON
alkej-30	21	18	use	use	NOUN
alkej-30	21	19	in	in	ADP
alkej-30	21	20	reconfigurable	reconfigurable	ADJ
alkej-30	21	21	computing	computing	NOUN
alkej-30	21	22	applications	application	NOUN
alkej-30	21	23	too	too	ADV
alkej-30	21	24	[	[	X
alkej-30	21	25	2	2	NUM
alkej-30	21	26	,	,	PUNCT
alkej-30	21	27	4	4	NUM
alkej-30	21	28	]	]	PUNCT
alkej-30	21	29	.	.	PUNCT
alkej-30	22	1	2.problem	2.problem	NUM
alkej-30	22	2	formulation	formulation	NOUN
alkej-30	22	3	the	the	DET
alkej-30	22	4	design	design	NOUN
alkej-30	22	5	problem	problem	NOUN
alkej-30	22	6	in	in	ADP
alkej-30	22	7	ann	ann	PROPN
alkej-30	22	8	using	use	VERB
alkej-30	22	9	fpga	fpga	PROPN
alkej-30	22	10	is	be	AUX
alkej-30	22	11	a	a	DET
alkej-30	22	12	precision	precision	NOUN
alkej-30	22	13	vs.	vs.	ADP
alkej-30	22	14	area	area	NOUN
alkej-30	22	15	trade	trade	NOUN
alkej-30	22	16	-	-	PUNCT
alkej-30	22	17	off	off	NOUN
alkej-30	22	18	.	.	PUNCT
alkej-30	23	1	one	one	NUM
alkej-30	23	2	way	way	NOUN
alkej-30	23	3	to	to	PART
alkej-30	23	4	help	help	VERB
alkej-30	23	5	achieve	achieve	VERB
alkej-30	23	6	the	the	DET
alkej-30	23	7	density	density	NOUN
alkej-30	23	8	advantage	advantage	NOUN
alkej-30	23	9	of	of	ADP
alkej-30	23	10	reconfigurable	reconfigurable	ADJ
alkej-30	23	11	computing	computing	NOUN
alkej-30	23	12	over	over	ADP
alkej-30	23	13	general	general	ADJ
alkej-30	23	14	-	-	PUNCT
alkej-30	23	15	purpose	purpose	NOUN
alkej-30	23	16	computing	computing	NOUN
alkej-30	23	17	is	be	AUX
alkej-30	23	18	to	to	PART
alkej-30	23	19	make	make	VERB
alkej-30	23	20	the	the	DET
alkej-30	23	21	most	most	ADV
alkej-30	23	22	efficient	efficient	ADJ
alkej-30	23	23	use	use	NOUN
alkej-30	23	24	of	of	ADP
alkej-30	23	25	the	the	DET
alkej-30	23	26	hardware	hardware	NOUN
alkej-30	23	27	area	area	NOUN
alkej-30	23	28	available	available	ADJ
alkej-30	23	29	.	.	PUNCT
alkej-30	24	1	in	in	ADP
alkej-30	24	2	terms	term	NOUN
alkej-30	24	3	of	of	ADP
alkej-30	24	4	an	an	DET
alkej-30	24	5	optimal	optimal	ADJ
alkej-30	24	6	precision	precision	NOUN
alkej-30	24	7	vs	vs	ADP
alkej-30	24	8	area	area	NOUN
alkej-30	24	9	trade	trade	NOUN
alkej-30	24	10	-	-	PUNCT
alkej-30	24	11	off	off	NOUN
alkej-30	24	12	,	,	PUNCT
alkej-30	24	13	this	this	PRON
alkej-30	24	14	can	can	AUX
alkej-30	24	15	be	be	AUX
alkej-30	24	16	achieved	achieve	VERB
alkej-30	24	17	by	by	ADP
alkej-30	24	18	determining	determine	VERB
alkej-30	24	19	the	the	DET
alkej-30	24	20	minimum	minimum	ADJ
alkej-30	24	21	allowable	allowable	ADJ
alkej-30	24	22	precision	precision	NOUN
alkej-30	24	23	,	,	PUNCT
alkej-30	24	24	whose	whose	DET
alkej-30	24	25	criterion	criterion	NOUN
alkej-30	24	26	is	be	AUX
alkej-30	24	27	to	to	PART
alkej-30	24	28	minimize	minimize	VERB
alkej-30	24	29	hardware	hardware	NOUN
alkej-30	24	30	area	area	NOUN
alkej-30	24	31	usage	usage	NOUN
alkej-30	24	32	without	without	ADP
alkej-30	24	33	sacrificing	sacrifice	VERB
alkej-30	24	34	quality	quality	NOUN
alkej-30	24	35	of	of	ADP
alkej-30	24	36	performance	performance	NOUN
alkej-30	24	37	.	.	PUNCT
alkej-30	25	1	because	because	SCONJ
alkej-30	25	2	a	a	DET
alkej-30	25	3	reduction	reduction	NOUN
alkej-30	25	4	in	in	ADP
alkej-30	25	5	precision	precision	NOUN
alkej-30	25	6	introduces	introduce	VERB
alkej-30	25	7	more	more	ADJ
alkej-30	25	8	error	error	NOUN
alkej-30	25	9	into	into	ADP
alkej-30	25	10	the	the	DET
alkej-30	25	11	system	system	NOUN
alkej-30	25	12	,	,	PUNCT
alkej-30	25	13	minimum	minimum	ADJ
alkej-30	25	14	allowable	allowable	ADJ
alkej-30	25	15	precision	precision	NOUN
alkej-30	25	16	is	be	AUX
alkej-30	25	17	actually	actually	ADV
alkej-30	25	18	a	a	DET
alkej-30	25	19	question	question	NOUN
alkej-30	25	20	of	of	ADP
alkej-30	25	21	determining	determine	VERB
alkej-30	25	22	the	the	DET
alkej-30	25	23	maximum	maximum	ADJ
alkej-30	25	24	amount	amount	NOUN
alkej-30	25	25	of	of	ADP
alkej-30	25	26	uncertainty	uncertainty	NOUN
alkej-30	25	27	(	(	PUNCT
alkej-30	25	28	i.e.	i.e.	X
alkej-30	25	29	quantization	quantization	NOUN
alkej-30	25	30	error	error	NOUN
alkej-30	25	31	due	due	ADP
alkej-30	25	32	to	to	ADP
alkej-30	25	33	limited	limited	ADJ
alkej-30	25	34	precision	precision	NOUN
alkej-30	25	35	)	)	PUNCT
alkej-30	25	36	that	that	SCONJ
alkej-30	25	37	an	an	DET
alkej-30	25	38	application	application	NOUN
alkej-30	25	39	can	can	AUX
alkej-30	25	40	withstand	withstand	VERB
alkej-30	25	41	before	before	SCONJ
alkej-30	25	42	performance	performance	NOUN
alkej-30	25	43	begins	begin	VERB
alkej-30	25	44	to	to	PART
alkej-30	25	45	degrade	degrade	VERB
alkej-30	25	46	.	.	PUNCT
alkej-30	26	1	hence	hence	ADV
alkej-30	26	2	,	,	PUNCT
alkej-30	26	3	determining	determine	VERB
alkej-30	26	4	a	a	DET
alkej-30	26	5	minimum	minimum	ADJ
alkej-30	26	6	allowable	allowable	ADJ
alkej-30	26	7	precision	precision	NOUN
alkej-30	26	8	and	and	CCONJ
alkej-30	26	9	suitable	suitable	ADJ
alkej-30	26	10	numeric	numeric	ADJ
alkej-30	26	11	representation	representation	NOUN
alkej-30	26	12	to	to	PART
alkej-30	26	13	use	use	VERB
alkej-30	26	14	in	in	ADP
alkej-30	26	15	hardware	hardware	NOUN
alkej-30	26	16	is	be	AUX
alkej-30	26	17	often	often	ADV
alkej-30	26	18	dependent	dependent	ADJ
alkej-30	26	19	upon	upon	SCONJ
alkej-30	26	20	the	the	DET
alkej-30	26	21	application	application	NOUN
alkej-30	26	22	at	at	ADP
alkej-30	26	23	hand	hand	NOUN
alkej-30	26	24	,	,	PUNCT
alkej-30	26	25	and	and	CCONJ
alkej-30	26	26	the	the	DET
alkej-30	26	27	algorithm	algorithm	NOUN
alkej-30	26	28	used	use	VERB
alkej-30	26	29	.	.	PUNCT
alkej-30	27	1	fortunately	fortunately	ADV
alkej-30	27	2	,	,	PUNCT
alkej-30	27	3	suitable	suitable	ADJ
alkej-30	27	4	precision	precision	NOUN
alkej-30	27	5	for	for	ADP
alkej-30	27	6	backpropagation	backpropagation	NOUN
alkej-30	27	7	-	-	PUNCT
alkej-30	27	8	based	base	VERB
alkej-30	27	9	anns	anns	NOUN
alkej-30	27	10	has	have	AUX
alkej-30	27	11	already	already	ADV
alkej-30	27	12	been	be	AUX
alkej-30	27	13	empirically	empirically	ADV
alkej-30	27	14	determined	determine	VERB
alkej-30	27	15	in	in	ADP
alkej-30	27	16	the	the	DET
alkej-30	27	17	past	past	NOUN
alkej-30	27	18	.	.	PUNCT
alkej-30	28	1	selecting	select	VERB
alkej-30	28	2	weight	weight	NOUN
alkej-30	28	3	precision	precision	NOUN
alkej-30	28	4	is	be	AUX
alkej-30	28	5	one	one	NUM
alkej-30	28	6	of	of	ADP
alkej-30	28	7	the	the	DET
alkej-30	28	8	important	important	ADJ
alkej-30	28	9	choices	choice	NOUN
alkej-30	28	10	when	when	SCONJ
alkej-30	28	11	implementing	implement	VERB
alkej-30	28	12	anns	ann	NOUN
alkej-30	28	13	on	on	ADP
alkej-30	28	14	fpgas	fpgas	NOUN
alkej-30	28	15	.	.	PUNCT
alkej-30	29	1	weight	weight	NOUN
alkej-30	29	2	precision	precision	NOUN
alkej-30	29	3	is	be	AUX
alkej-30	29	4	used	use	VERB
alkej-30	29	5	to	to	PART
alkej-30	29	6	tradeoff	tradeoff	VERB
alkej-30	29	7	the	the	DET
alkej-30	29	8	capabilities	capability	NOUN
alkej-30	29	9	of	of	ADP
alkej-30	29	10	the	the	DET
alkej-30	29	11	realized	realize	VERB
alkej-30	29	12	anns	anns	NOUN
alkej-30	29	13	against	against	ADP
alkej-30	29	14	the	the	DET
alkej-30	29	15	implementation	implementation	NOUN
alkej-30	29	16	cost	cost	NOUN
alkej-30	29	17	.	.	PUNCT
alkej-30	30	1	a	a	DET
alkej-30	30	2	higher	high	ADJ
alkej-30	30	3	weight	weight	NOUN
alkej-30	30	4	precision	precision	NOUN
alkej-30	30	5	means	mean	VERB
alkej-30	30	6	fewer	few	ADJ
alkej-30	30	7	quantization	quantization	NOUN
alkej-30	30	8	errors	error	NOUN
alkej-30	30	9	in	in	ADP
alkej-30	30	10	the	the	DET
alkej-30	30	11	final	final	ADJ
alkej-30	30	12	implementations	implementation	NOUN
alkej-30	30	13	,	,	PUNCT
alkej-30	30	14	while	while	SCONJ
alkej-30	30	15	a	a	DET
alkej-30	30	16	lower	low	ADJ
alkej-30	30	17	precision	precision	NOUN
alkej-30	30	18	leads	lead	VERB
alkej-30	30	19	to	to	ADP
alkej-30	30	20	simpler	simple	ADJ
alkej-30	30	21	designs	design	NOUN
alkej-30	30	22	,	,	PUNCT
alkej-30	30	23	greater	great	ADJ
alkej-30	30	24	speed	speed	NOUN
alkej-30	30	25	and	and	CCONJ
alkej-30	30	26	reductions	reduction	NOUN
alkej-30	30	27	in	in	ADP
alkej-30	30	28	area	area	NOUN
alkej-30	30	29	requirements	requirement	NOUN
alkej-30	30	30	and	and	CCONJ
alkej-30	30	31	power	power	NOUN
alkej-30	30	32	consumption	consumption	NOUN
alkej-30	30	33	.	.	PUNCT
alkej-30	31	1	one	one	NUM
alkej-30	31	2	way	way	NOUN
alkej-30	31	3	of	of	ADP
alkej-30	31	4	resolving	resolve	VERB
alkej-30	31	5	the	the	DET
alkej-30	31	6	tradeoff	tradeoff	NOUN
alkej-30	31	7	is	be	AUX
alkej-30	31	8	to	to	PART
alkej-30	31	9	determine	determine	VERB
alkej-30	31	10	the	the	DET
alkej-30	31	11	“	"	PUNCT
alkej-30	31	12	minimum	minimum	ADJ
alkej-30	31	13	precision	precision	NOUN
alkej-30	31	14	”	"	PUNCT
alkej-30	31	15	,	,	PUNCT
alkej-30	31	16	required	require	VERB
alkej-30	31	17	to	to	PART
alkej-30	31	18	solve	solve	VERB
alkej-30	31	19	a	a	DET
alkej-30	31	20	given	give	VERB
alkej-30	31	21	problem	problem	NOUN
alkej-30	31	22	.	.	PUNCT
alkej-30	32	1	traditionally	traditionally	ADV
alkej-30	32	2	,	,	PUNCT
alkej-30	32	3	the	the	DET
alkej-30	32	4	minimum	minimum	ADJ
alkej-30	32	5	precision	precision	NOUN
alkej-30	32	6	is	be	AUX
alkej-30	32	7	found	find	VERB
alkej-30	32	8	through	through	ADP
alkej-30	32	9	“	"	PUNCT
alkej-30	32	10	trial	trial	NOUN
alkej-30	32	11	and	and	CCONJ
alkej-30	32	12	error	error	NOUN
alkej-30	32	13	”	"	PUNCT
alkej-30	32	14	by	by	ADP
alkej-30	32	15	simulating	simulate	VERB
alkej-30	32	16	the	the	DET
alkej-30	32	17	solution	solution	NOUN
alkej-30	32	18	in	in	ADP
alkej-30	32	19	software	software	NOUN
alkej-30	32	20	before	before	ADP
alkej-30	32	21	implementation	implementation	NOUN
alkej-30	32	22	.	.	PUNCT
alkej-30	33	1	holt	holt	PROPN
alkej-30	33	2	and	and	CCONJ
alkej-30	33	3	baker	baker	PROPN
alkej-30	34	1	[	[	X
alkej-30	34	2	5	5	NUM
alkej-30	34	3	]	]	PUNCT
alkej-30	34	4	studied	study	VERB
alkej-30	34	5	the	the	DET
alkej-30	34	6	minimum	minimum	ADJ
alkej-30	34	7	precision	precision	NOUN
alkej-30	34	8	required	require	VERB
alkej-30	34	9	for	for	ADP
alkej-30	34	10	a	a	DET
alkej-30	34	11	class	class	NOUN
alkej-30	34	12	of	of	ADP
alkej-30	34	13	benchmark	benchmark	NOUN
alkej-30	34	14	classification	classification	NOUN
alkej-30	34	15	problems	problem	NOUN
alkej-30	34	16	and	and	CCONJ
alkej-30	34	17	found	find	VERB
alkej-30	34	18	that	that	SCONJ
alkej-30	34	19	16	16	NUM
alkej-30	34	20	-	-	PUNCT
alkej-30	34	21	bit	bit	NOUN
alkej-30	34	22	fixed	fix	VERB
alkej-30	34	23	-	-	PUNCT
alkej-30	34	24	point	point	NOUN
alkej-30	34	25	is	be	AUX
alkej-30	34	26	the	the	DET
alkej-30	34	27	minimum	minimum	ADJ
alkej-30	34	28	allowable	allowable	ADJ
alkej-30	34	29	precision	precision	NOUN
alkej-30	34	30	without	without	ADP
alkej-30	34	31	diminishing	diminish	VERB
alkej-30	34	32	an	an	DET
alkej-30	34	33	ann	ann	PROPN
alkej-30	34	34	’s	’s	PART
alkej-30	34	35	capability	capability	NOUN
alkej-30	34	36	to	to	PART
alkej-30	34	37	learn	learn	VERB
alkej-30	34	38	these	these	DET
alkej-30	34	39	benchmark	benchmark	NOUN
alkej-30	34	40	problems	problem	NOUN
alkej-30	34	41	.	.	PUNCT
alkej-30	35	1	3.ann	3.ann	NUM
alkej-30	35	2	example	example	NOUN
alkej-30	36	1	3.1.structure	3.1.structure	NUM
alkej-30	36	2	of	of	ADP
alkej-30	36	3	the	the	DET
alkej-30	36	4	circuit	circuit	NOUN
alkej-30	36	5	following	follow	VERB
alkej-30	36	6	example	example	NOUN
alkej-30	36	7	[	[	X
alkej-30	36	8	6	6	NUM
alkej-30	36	9	]	]	PUNCT
alkej-30	36	10	present	present	ADJ
alkej-30	36	11	how	how	SCONJ
alkej-30	36	12	these	these	DET
alkej-30	36	13	two	two	NUM
alkej-30	36	14	parameters	parameter	NOUN
alkej-30	36	15	effect	effect	VERB
alkej-30	36	16	on	on	ADP
alkej-30	36	17	hardware	hardware	NOUN
alkej-30	36	18	resources	resource	NOUN
alkej-30	36	19	.	.	PUNCT
alkej-30	37	1	remember	remember	VERB
alkej-30	37	2	that	that	SCONJ
alkej-30	37	3	in	in	ADP
alkej-30	37	4	neural	neural	ADJ
alkej-30	37	5	network	network	NOUN
alkej-30	37	6	resources	resource	NOUN
alkej-30	37	7	capacity	capacity	NOUN
alkej-30	37	8	differ	differ	VERB
alkej-30	37	9	from	from	ADP
alkej-30	37	10	network	network	NOUN
alkej-30	37	11	to	to	ADP
alkej-30	37	12	other	other	ADJ
alkej-30	37	13	according	accord	VERB
alkej-30	37	14	to	to	ADP
alkej-30	37	15	number	number	NOUN
alkej-30	37	16	of	of	ADP
alkej-30	37	17	neurons	neuron	NOUN
alkej-30	37	18	in	in	ADP
alkej-30	37	19	each	each	DET
alkej-30	37	20	layer	layer	NOUN
alkej-30	37	21	.	.	PUNCT
alkej-30	38	1	the	the	DET
alkej-30	38	2	existence	existence	NOUN
alkej-30	38	3	of	of	ADP
alkej-30	38	4	hidden	hide	VERB
alkej-30	38	5	units	unit	NOUN
alkej-30	38	6	allows	allow	VERB
alkej-30	38	7	the	the	DET
alkej-30	38	8	network	network	NOUN
alkej-30	38	9	to	to	PART
alkej-30	38	10	develop	develop	VERB
alkej-30	38	11	complex	complex	ADJ
alkej-30	38	12	feature	feature	NOUN
alkej-30	38	13	detectors	detector	NOUN
alkej-30	38	14	,	,	PUNCT
alkej-30	38	15	or	or	CCONJ
alkej-30	38	16	internal	internal	ADJ
alkej-30	38	17	representations	representation	NOUN
alkej-30	38	18	.	.	PUNCT
alkej-30	39	1	fig.(1	fig.(1	X
alkej-30	39	2	)	)	PUNCT
alkej-30	39	3	shows	show	VERB
alkej-30	39	4	the	the	DET
alkej-30	39	5	application	application	NOUN
alkej-30	39	6	of	of	ADP
alkej-30	39	7	four	four	NUM
alkej-30	39	8	layers	layer	NOUN
alkej-30	39	9	network	network	NOUN
alkej-30	39	10	to	to	ADP
alkej-30	39	11	the	the	DET
alkej-30	39	12	problem	problem	NOUN
alkej-30	39	13	of	of	ADP
alkej-30	39	14	recognizing	recognize	VERB
alkej-30	39	15	english	english	ADJ
alkej-30	39	16	digit	digit	NOUN
alkej-30	39	17	numbers	number	NOUN
alkej-30	39	18	.	.	PUNCT
alkej-30	40	1	the	the	DET
alkej-30	40	2	two	two	NUM
alkej-30	40	3	dimensional	dimensional	ADJ
alkej-30	40	4	grid	grid	NOUN
alkej-30	40	5	containing	contain	VERB
alkej-30	40	6	the	the	DET
alkej-30	40	7	numeral	numeral	ADJ
alkej-30	40	8	“	"	PUNCT
alkej-30	40	9	7	7	NUM
alkej-30	40	10	”	"	PUNCT
alkej-30	40	11	forms	form	VERB
alkej-30	40	12	the	the	DET
alkej-30	40	13	input	input	NOUN
alkej-30	40	14	layer	layer	NOUN
alkej-30	40	15	(	(	PUNCT
alkej-30	40	16	it	it	PRON
alkej-30	40	17	can	can	AUX
alkej-30	40	18	be	be	AUX
alkej-30	40	19	arranged	arrange	VERB
alkej-30	40	20	this	this	DET
alkej-30	40	21	two	two	NUM
alkej-30	40	22	dimension	dimension	NOUN
alkej-30	40	23	array	array	NOUN
alkej-30	40	24	as	as	ADP
alkej-30	40	25	one	one	NUM
alkej-30	40	26	dimension	dimension	NOUN
alkej-30	40	27	,	,	PUNCT
alkej-30	40	28	so	so	SCONJ
alkej-30	40	29	that	that	SCONJ
alkej-30	40	30	,	,	PUNCT
alkej-30	40	31	number	number	NOUN
alkej-30	40	32	of	of	ADP
alkej-30	40	33	input	input	NOUN
alkej-30	40	34	neurons	neuron	NOUN
alkej-30	40	35	is	be	AUX
alkej-30	40	36	thirteen	thirteen	NUM
alkej-30	40	37	)	)	PUNCT
alkej-30	40	38	.	.	PUNCT
alkej-30	41	1	ammar	ammar	PROPN
alkej-30	41	2	a.	a.	PROPN
alkej-30	41	3	hassan	hassan	PROPN
alkej-30	41	4	/al	/al	PROPN
alkej-30	41	5	-	-	PUNCT
alkej-30	41	6	khwarizmi	khwarizmi	PROPN
alkej-30	41	7	engineering	engineering	NOUN
alkej-30	41	8	journal	journal	PROPN
alkej-30	41	9	,	,	PUNCT
alkej-30	41	10	vol.2	vol.2	PROPN
alkej-30	41	11	,	,	PUNCT
alkej-30	41	12	no	no	INTJ
alkej-30	41	13	.	.	NOUN
alkej-30	41	14	2	2	NUM
alkej-30	41	15	pp	pp	ADP
alkej-30	41	16	32	32	NUM
alkej-30	41	17	-	-	SYM
alkej-30	41	18	41	41	NUM
alkej-30	41	19	(	(	PUNCT
alkej-30	41	20	2006	2006	NUM
alkej-30	41	21	)	)	PUNCT
alkej-30	41	22	23	23	NUM
alkej-30	42	1	the	the	DET
alkej-30	42	2	first	first	ADJ
alkej-30	42	3	hidden	hide	VERB
alkej-30	42	4	layer	layer	NOUN
alkej-30	42	5	is	be	AUX
alkej-30	42	6	formed	form	VERB
alkej-30	42	7	from	from	ADP
alkej-30	42	8	40	40	NUM
alkej-30	42	9	units	unit	NOUN
alkej-30	42	10	each	each	DET
alkej-30	42	11	unit	unit	NOUN
alkej-30	42	12	might	might	AUX
alkej-30	42	13	be	be	AUX
alkej-30	42	14	strongly	strongly	ADV
alkej-30	42	15	activated	activate	VERB
alkej-30	42	16	by	by	ADP
alkej-30	42	17	horizontal	horizontal	ADJ
alkej-30	42	18	line	line	NOUN
alkej-30	42	19	in	in	ADP
alkej-30	42	20	the	the	DET
alkej-30	42	21	input	input	NOUN
alkej-30	42	22	,	,	PUNCT
alkej-30	42	23	while	while	SCONJ
alkej-30	42	24	the	the	DET
alkej-30	42	25	second	second	ADJ
alkej-30	42	26	hidden	hidden	ADJ
alkej-30	42	27	layer	layer	NOUN
alkej-30	42	28	molded	mold	VERB
alkej-30	42	29	from	from	ADP
alkej-30	42	30	20	20	NUM
alkej-30	42	31	hidden	hide	VERB
alkej-30	42	32	units	unit	NOUN
alkej-30	42	33	,	,	PUNCT
alkej-30	42	34	each	each	DET
alkej-30	42	35	unit	unit	NOUN
alkej-30	42	36	fully	fully	ADV
alkej-30	42	37	connected	connect	VERB
alkej-30	42	38	with	with	ADP
alkej-30	42	39	each	each	DET
alkej-30	42	40	unit	unit	NOUN
alkej-30	42	41	in	in	ADP
alkej-30	42	42	the	the	DET
alkej-30	42	43	first	first	ADJ
alkej-30	42	44	hidden	hide	VERB
alkej-30	42	45	layer	layer	NOUN
alkej-30	42	46	.	.	PUNCT
alkej-30	43	1	the	the	DET
alkej-30	43	2	output	output	NOUN
alkej-30	43	3	layer	layer	NOUN
alkej-30	43	4	has	have	VERB
alkej-30	43	5	ten	ten	NUM
alkej-30	43	6	units	unit	NOUN
alkej-30	43	7	that	that	PRON
alkej-30	43	8	represent	represent	VERB
alkej-30	43	9	the	the	DET
alkej-30	43	10	value	value	NOUN
alkej-30	43	11	of	of	ADP
alkej-30	43	12	the	the	DET
alkej-30	43	13	digit	digit	NOUN
alkej-30	43	14	number	number	NOUN
alkej-30	43	15	.	.	PUNCT
alkej-30	44	1	knowing	know	VERB
alkej-30	44	2	that	that	SCONJ
alkej-30	44	3	,	,	PUNCT
alkej-30	44	4	the	the	DET
alkej-30	44	5	behavior	behavior	NOUN
alkej-30	44	6	of	of	ADP
alkej-30	44	7	these	these	DET
alkej-30	44	8	hidden	hide	VERB
alkej-30	44	9	units	unit	NOUN
alkej-30	44	10	is	be	AUX
alkej-30	44	11	automatically	automatically	ADV
alkej-30	44	12	learned	learn	VERB
alkej-30	44	13	not	not	PART
alkej-30	44	14	preprogrammed	preprogrammed	ADJ
alkej-30	44	15	,	,	PUNCT
alkej-30	44	16	then	then	ADV
alkej-30	44	17	the	the	DET
alkej-30	44	18	computing	compute	VERB
alkej-30	44	19	weight	weight	NOUN
alkej-30	44	20	of	of	ADP
alkej-30	44	21	each	each	DET
alkej-30	44	22	layer	layer	NOUN
alkej-30	44	23	in	in	ADP
alkej-30	44	24	the	the	DET
alkej-30	44	25	network	network	NOUN
alkej-30	44	26	accuracy	accuracy	NOUN
alkej-30	44	27	by	by	ADP
alkej-30	44	28	using	use	VERB
alkej-30	44	29	c++	c++	ADJ
alkej-30	44	30	programming	programming	NOUN
alkej-30	44	31	language	language	NOUN
alkej-30	44	32	and	and	CCONJ
alkej-30	44	33	implementing	implement	VERB
alkej-30	44	34	this	this	DET
alkej-30	44	35	result	result	NOUN
alkej-30	44	36	on	on	ADP
alkej-30	44	37	fpga	fpga	PROPN
alkej-30	44	38	as	as	SCONJ
alkej-30	44	39	shown	show	VERB
alkej-30	44	40	in	in	ADP
alkej-30	44	41	the	the	DET
alkej-30	44	42	next	next	ADJ
alkej-30	44	43	section	section	NOUN
alkej-30	44	44	.	.	PUNCT
alkej-30	45	1	3.2.implementation	3.2.implementation	NUM
alkej-30	45	2	ann	ann	PROPN
alkej-30	45	3	components	component	NOUN
alkej-30	45	4	on	on	ADP
alkej-30	45	5	fpga	fpga	PROPN
alkej-30	45	6	digital	digital	PROPN
alkej-30	45	7	ann	ann	PROPN
alkej-30	45	8	architecture	architecture	NOUN
alkej-30	45	9	proposed	propose	VERB
alkej-30	45	10	in	in	ADP
alkej-30	45	11	the	the	DET
alkej-30	45	12	previous	previous	ADJ
alkej-30	45	13	section	section	NOUN
alkej-30	45	14	is	be	AUX
alkej-30	45	15	an	an	DET
alkej-30	45	16	example	example	NOUN
alkej-30	45	17	of	of	ADP
alkej-30	45	18	a	a	DET
alkej-30	45	19	reconfigurable	reconfigurable	ADJ
alkej-30	45	20	computing	computing	NOUN
alkej-30	45	21	application	application	NOUN
alkej-30	45	22	,	,	PUNCT
alkej-30	45	23	where	where	SCONJ
alkej-30	45	24	all	all	DET
alkej-30	45	25	stages	stage	NOUN
alkej-30	45	26	of	of	ADP
alkej-30	45	27	the	the	DET
alkej-30	45	28	algorithm	algorithm	NOUN
alkej-30	45	29	reside	reside	VERB
alkej-30	45	30	together	together	ADV
alkej-30	45	31	on	on	ADP
alkej-30	45	32	the	the	DET
alkej-30	45	33	fpga	fpga	NOUN
alkej-30	45	34	at	at	ADP
alkej-30	45	35	once	once	ADV
alkej-30	45	36	.	.	PUNCT
alkej-30	46	1	these	these	DET
alkej-30	46	2	components	component	NOUN
alkej-30	46	3	based	base	VERB
alkej-30	46	4	in	in	ADP
alkej-30	46	5	idea	idea	NOUN
alkej-30	46	6	of	of	ADP
alkej-30	46	7	implementation	implementation	NOUN
alkej-30	46	8	on	on	ADP
alkej-30	46	9	simple	simple	ADJ
alkej-30	46	10	(	(	PUNCT
alkej-30	46	11	or	or	CCONJ
alkej-30	46	12	basic	basic	ADJ
alkej-30	46	13	)	)	PUNCT
alkej-30	46	14	arithmetic	arithmetic	ADJ
alkej-30	46	15	operations	operation	NOUN
alkej-30	46	16	(	(	PUNCT
alkej-30	46	17	such	such	ADJ
alkej-30	46	18	as	as	ADP
alkej-30	46	19	addition	addition	NOUN
alkej-30	46	20	and	and	CCONJ
alkej-30	46	21	multiplication	multiplication	NOUN
alkej-30	46	22	operations	operation	NOUN
alkej-30	46	23	)	)	PUNCT
alkej-30	46	24	.	.	PUNCT
alkej-30	47	1	the	the	DET
alkej-30	47	2	floating	float	VERB
alkej-30	47	3	-	-	PUNCT
alkej-30	47	4	point	point	NOUN
alkej-30	47	5	precision	precision	NOUN
alkej-30	47	6	is	be	AUX
alkej-30	47	7	the	the	DET
alkej-30	47	8	problem	problem	NOUN
alkej-30	47	9	of	of	ADP
alkej-30	47	10	which	which	PRON
alkej-30	47	11	an	an	DET
alkej-30	47	12	engineer	engineer	NOUN
alkej-30	47	13	must	must	AUX
alkej-30	47	14	deal	deal	VERB
alkej-30	47	15	with	with	ADP
alkej-30	47	16	when	when	SCONJ
alkej-30	47	17	testing	testing	NOUN
alkej-30	47	18	and	and	CCONJ
alkej-30	47	19	validating	validate	VERB
alkej-30	47	20	circuits	circuit	NOUN
alkej-30	47	21	since	since	SCONJ
alkej-30	47	22	it	it	PRON
alkej-30	47	23	limits	limit	VERB
alkej-30	47	24	quantization	quantization	NOUN
alkej-30	47	25	errors	error	NOUN
alkej-30	47	26	according	accord	VERB
alkej-30	47	27	to	to	ADP
alkej-30	47	28	number	number	NOUN
alkej-30	47	29	of	of	ADP
alkej-30	47	30	bits	bit	NOUN
alkej-30	47	31	in	in	ADP
alkej-30	47	32	each	each	DET
alkej-30	47	33	node	node	NOUN
alkej-30	47	34	.	.	PUNCT
alkej-30	48	1	therefore	therefore	ADV
alkej-30	48	2	,	,	PUNCT
alkej-30	48	3	truncation	truncation	NOUN
alkej-30	48	4	technique	technique	NOUN
alkej-30	48	5	will	will	AUX
alkej-30	48	6	be	be	AUX
alkej-30	48	7	used	use	VERB
alkej-30	48	8	in	in	ADP
alkej-30	48	9	design	design	NOUN
alkej-30	48	10	to	to	PART
alkej-30	48	11	reduce	reduce	VERB
alkej-30	48	12	the	the	DET
alkej-30	48	13	floating	float	VERB
alkej-30	48	14	-	-	PUNCT
alkej-30	48	15	point	point	NOUN
alkej-30	48	16	precision	precision	NOUN
alkej-30	48	17	value	value	NOUN
alkej-30	48	18	and	and	CCONJ
alkej-30	48	19	employ	employ	VERB
alkej-30	48	20	minimum	minimum	NOUN
alkej-30	48	21	hardware	hardware	NOUN
alkej-30	48	22	resources	resource	NOUN
alkej-30	48	23	available	available	ADJ
alkej-30	48	24	on	on	ADP
alkej-30	48	25	fpga	fpga	PROPN
alkej-30	48	26	.	.	PUNCT
alkej-30	49	1	adding	add	VERB
alkej-30	49	2	to	to	ADP
alkej-30	49	3	this	this	PRON
alkej-30	49	4	,	,	PUNCT
alkej-30	49	5	choosing	choose	VERB
alkej-30	49	6	the	the	DET
alkej-30	49	7	optimal	optimal	ADJ
alkej-30	49	8	activation	activation	NOUN
alkej-30	49	9	function	function	VERB
alkej-30	49	10	suitable	suitable	ADJ
alkej-30	49	11	for	for	ADP
alkej-30	49	12	implementation	implementation	NOUN
alkej-30	49	13	with	with	ADP
alkej-30	49	14	truncation	truncation	NOUN
alkej-30	49	15	technique	technique	NOUN
alkej-30	49	16	.	.	PUNCT
alkej-30	50	1	previously	previously	ADV
alkej-30	50	2	as	as	SCONJ
alkej-30	50	3	declared	declare	VERB
alkej-30	50	4	,	,	PUNCT
alkej-30	50	5	the	the	DET
alkej-30	50	6	ann	ann	PROPN
alkej-30	50	7	algorithm	algorithm	NOUN
alkej-30	50	8	components	component	NOUN
alkej-30	50	9	(	(	PUNCT
alkej-30	50	10	such	such	ADJ
alkej-30	50	11	as	as	ADP
alkej-30	50	12	number	number	NOUN
alkej-30	50	13	of	of	ADP
alkej-30	50	14	hidden	hidden	ADJ
alkej-30	50	15	layers	layer	NOUN
alkej-30	50	16	and	and	CCONJ
alkej-30	50	17	number	number	NOUN
alkej-30	50	18	of	of	ADP
alkej-30	50	19	units	unit	NOUN
alkej-30	50	20	in	in	ADP
alkej-30	50	21	each	each	DET
alkej-30	50	22	fig.(1	fig.(1	PROPN
alkej-30	50	23	):	):	PUNCT
alkej-30	50	24	multilayer	multilayer	ADJ
alkej-30	50	25	network	network	NOUN
alkej-30	50	26	to	to	PART
alkej-30	50	27	learn	learn	VERB
alkej-30	50	28	to	to	PART
alkej-30	50	29	classify	classify	VERB
alkej-30	50	30	english	english	ADJ
alkej-30	50	31	numbers	number	NOUN
alkej-30	50	32	0	0	NUM
alkej-30	50	33	1	1	NUM
alkej-30	50	34	2	2	NUM
alkej-30	50	35	3	3	NUM
alkej-30	50	36	4	4	NUM
alkej-30	50	37	5	5	NUM
alkej-30	50	38	6	6	NUM
alkej-30	50	39	7	7	NUM
alkej-30	50	40	8	8	NUM
alkej-30	50	41	9	9	NUM
alkej-30	50	42	output	output	NOUN
alkej-30	50	43	10	10	NUM
alkej-30	50	44	nodes	node	NOUN
alkej-30	50	45	hidden2	hidden2	NOUN
alkej-30	50	46	20	20	NUM
alkej-30	50	47	nodes	node	NOUN
alkej-30	50	48	input	input	VERB
alkej-30	50	49	25	25	NUM
alkej-30	50	50	nodes	node	NOUN
alkej-30	50	51	hidden1	hidden1	VERB
alkej-30	50	52	40	40	NUM
alkej-30	50	53	nodes	node	NOUN
alkej-30	50	54	ammar	ammar	PROPN
alkej-30	50	55	a.	a.	PROPN
alkej-30	50	56	hassan	hassan	PROPN
alkej-30	50	57	/al	/al	PROPN
alkej-30	50	58	-	-	PUNCT
alkej-30	50	59	khwarizmi	khwarizmi	PROPN
alkej-30	50	60	engineering	engineering	NOUN
alkej-30	50	61	journal	journal	PROPN
alkej-30	50	62	,	,	PUNCT
alkej-30	50	63	vol.2	vol.2	PROPN
alkej-30	50	64	,	,	PUNCT
alkej-30	50	65	no	no	INTJ
alkej-30	50	66	.	.	NOUN
alkej-30	50	67	2	2	NUM
alkej-30	51	1	pp	pp	ADP
alkej-30	51	2	32	32	NUM
alkej-30	51	3	-	-	SYM
alkej-30	51	4	41	41	NUM
alkej-30	51	5	(	(	PUNCT
alkej-30	51	6	2006	2006	NUM
alkej-30	51	7	)	)	PUNCT
alkej-30	51	8	23	23	NUM
alkej-30	51	9	layer	layer	NOUN
alkej-30	51	10	)	)	PUNCT
alkej-30	51	11	differ	differ	VERB
alkej-30	51	12	from	from	ADP
alkej-30	51	13	application	application	NOUN
alkej-30	51	14	to	to	ADP
alkej-30	51	15	another	another	PRON
alkej-30	51	16	.	.	PUNCT
alkej-30	52	1	the	the	DET
alkej-30	52	2	english	english	PROPN
alkej-30	52	3	digit	digit	NOUN
alkej-30	52	4	numbers	number	NOUN
alkej-30	52	5	nn	nn	X
alkej-30	52	6	is	be	VERB
alkej-30	52	7	the	the	DET
alkej-30	52	8	application	application	NOUN
alkej-30	52	9	used	use	VERB
alkej-30	52	10	in	in	ADP
alkej-30	52	11	this	this	DET
alkej-30	52	12	work	work	NOUN
alkej-30	52	13	to	to	PART
alkej-30	52	14	implement	implement	VERB
alkej-30	52	15	ann	ann	PROPN
alkej-30	52	16	on	on	ADP
alkej-30	52	17	fpga	fpga	PROPN
alkej-30	52	18	,	,	PUNCT
alkej-30	52	19	which	which	PRON
alkej-30	52	20	is	be	AUX
alkej-30	52	21	composed	compose	VERB
alkej-30	52	22	from	from	ADP
alkej-30	52	23	four	four	NUM
alkej-30	52	24	layers	layer	NOUN
alkej-30	52	25	.	.	PUNCT
alkej-30	53	1	the	the	DET
alkej-30	53	2	quantization	quantization	NOUN
alkej-30	53	3	error	error	NOUN
alkej-30	53	4	after	after	SCONJ
alkej-30	53	5	5,000	5,000	NUM
alkej-30	53	6	iteration	iteration	NOUN
alkej-30	53	7	using	use	VERB
alkej-30	53	8	two	two	NUM
alkej-30	53	9	types	type	NOUN
alkej-30	53	10	of	of	ADP
alkej-30	53	11	activation	activation	NOUN
alkej-30	53	12	functions	function	NOUN
alkej-30	53	13	are	be	AUX
alkej-30	53	14	given	give	VERB
alkej-30	53	15	in	in	ADP
alkej-30	53	16	table	table	NOUN
alkej-30	53	17	(	(	PUNCT
alkej-30	53	18	1	1	NUM
alkej-30	53	19	)	)	PUNCT
alkej-30	53	20	.	.	PUNCT
alkej-30	54	1	by	by	ADP
alkej-30	54	2	using	use	VERB
alkej-30	54	3	sigmoid	sigmoid	NOUN
alkej-30	54	4	function	function	NOUN
alkej-30	54	5	and	and	CCONJ
alkej-30	54	6	without	without	ADP
alkej-30	54	7	truncation	truncation	NOUN
alkej-30	54	8	(	(	PUNCT
alkej-30	54	9	30	30	NUM
alkej-30	54	10	-	-	PUNCT
alkej-30	54	11	bit	bit	NOUN
alkej-30	54	12	floating	float	VERB
alkej-30	54	13	-	-	PUNCT
alkej-30	54	14	point	point	NOUN
alkej-30	54	15	)	)	PUNCT
alkej-30	54	16	,	,	PUNCT
alkej-30	54	17	quntization	quntization	NOUN
alkej-30	54	18	error	error	NOUN
alkej-30	54	19	is	be	AUX
alkej-30	54	20	0.02	0.02	NUM
alkej-30	54	21	(	(	PUNCT
alkej-30	54	22	i.e.	i.e.	X
alkej-30	54	23	98	98	NUM
alkej-30	54	24	%	%	NOUN
alkej-30	54	25	of	of	ADP
alkej-30	54	26	the	the	DET
alkej-30	54	27	corrected	correct	VERB
alkej-30	54	28	output	output	NOUN
alkej-30	54	29	)	)	PUNCT
alkej-30	54	30	.	.	PUNCT
alkej-30	55	1	while	while	SCONJ
alkej-30	55	2	,	,	PUNCT
alkej-30	55	3	by	by	ADP
alkej-30	55	4	the	the	DET
alkej-30	55	5	same	same	ADJ
alkej-30	55	6	method	method	NOUN
alkej-30	55	7	,	,	PUNCT
alkej-30	55	8	but	but	CCONJ
alkej-30	55	9	using	use	VERB
alkej-30	55	10	bipolar	bipolar	ADJ
alkej-30	55	11	function	function	NOUN
alkej-30	55	12	instead	instead	ADV
alkej-30	55	13	of	of	ADP
alkej-30	55	14	sigmoid	sigmoid	NOUN
alkej-30	55	15	function	function	NOUN
alkej-30	55	16	,	,	PUNCT
alkej-30	55	17	quntization	quntization	NOUN
alkej-30	55	18	error	error	NOUN
alkej-30	55	19	will	will	AUX
alkej-30	55	20	be	be	AUX
alkej-30	55	21	given	give	VERB
alkej-30	55	22	0.04	0.04	NUM
alkej-30	55	23	.	.	PUNCT
alkej-30	56	1	4.arithmetic	4.arithmetic	ADJ
alkej-30	56	2	architecture	architecture	NOUN
alkej-30	56	3	for	for	ADP
alkej-30	56	4	fpga	fpga	PROPN
alkej-30	56	5	based	base	VERB
alkej-30	56	6	anns	anns	PROPN
alkej-30	56	7	to	to	PART
alkej-30	56	8	calculate	calculate	VERB
alkej-30	56	9	the	the	DET
alkej-30	56	10	cost	cost	NOUN
alkej-30	56	11	required	require	VERB
alkej-30	56	12	for	for	ADP
alkej-30	56	13	english	english	ADJ
alkej-30	56	14	digit	digit	NOUN
alkej-30	56	15	number	number	NOUN
alkej-30	56	16	nn	nn	PROPN
alkej-30	56	17	in	in	ADP
alkej-30	56	18	fpga	fpga	PROPN
alkej-30	56	19	,	,	PUNCT
alkej-30	56	20	it	it	PRON
alkej-30	56	21	should	should	AUX
alkej-30	56	22	be	be	AUX
alkej-30	56	23	declared	declare	VERB
alkej-30	56	24	the	the	DET
alkej-30	56	25	way	way	NOUN
alkej-30	56	26	of	of	ADP
alkej-30	56	27	selecting	select	VERB
alkej-30	56	28	activation	activation	NOUN
alkej-30	56	29	function	function	NOUN
alkej-30	56	30	against	against	ADP
alkej-30	56	31	truncation	truncation	NOUN
alkej-30	56	32	approach	approach	NOUN
alkej-30	56	33	as	as	ADP
alkej-30	56	34	following	follow	VERB
alkej-30	56	35	:	:	PUNCT
alkej-30	56	36	4.1.sigmoid	4.1.sigmoid	NUM
alkej-30	56	37	function	function	NOUN
alkej-30	56	38	without	without	ADP
alkej-30	56	39	truncation	truncation	NOUN
alkej-30	56	40	(	(	PUNCT
alkej-30	56	41	30	30	NUM
alkej-30	56	42	-	-	PUNCT
alkej-30	56	43	bit	bit	NOUN
alkej-30	56	44	)	)	PUNCT
alkej-30	56	45	before	before	ADP
alkej-30	56	46	calculating	calculate	VERB
alkej-30	56	47	the	the	DET
alkej-30	56	48	cost	cost	NOUN
alkej-30	56	49	of	of	ADP
alkej-30	56	50	fpga	fpga	PROPN
alkej-30	56	51	based	base	VERB
alkej-30	56	52	digit	digit	PROPN
alkej-30	56	53	nn	nn	PROPN
alkej-30	56	54	,	,	PUNCT
alkej-30	56	55	it	it	PRON
alkej-30	56	56	should	should	AUX
alkej-30	56	57	be	be	AUX
alkej-30	56	58	known	know	VERB
alkej-30	56	59	that	that	SCONJ
alkej-30	56	60	this	this	DET
alkej-30	56	61	function	function	NOUN
alkej-30	56	62	produced	produce	VERB
alkej-30	56	63	floating	float	VERB
alkej-30	56	64	-	-	PUNCT
alkej-30	56	65	point	point	NOUN
alkej-30	56	66	values	value	NOUN
alkej-30	56	67	.	.	PUNCT
alkej-30	57	1	then	then	ADV
alkej-30	57	2	,	,	PUNCT
alkej-30	57	3	it	it	PRON
alkej-30	57	4	required	require	VERB
alkej-30	57	5	a	a	DET
alkej-30	57	6	large	large	ADJ
alkej-30	57	7	number	number	NOUN
alkej-30	57	8	of	of	ADP
alkej-30	57	9	logic	logic	NOUN
alkej-30	57	10	storage	storage	NOUN
alkej-30	57	11	as	as	ADP
alkej-30	57	12	basic	basic	ADJ
alkej-30	57	13	logic	logic	NOUN
alkej-30	57	14	cells	cell	NOUN
alkej-30	57	15	(	(	PUNCT
alkej-30	57	16	lcs	lcs	PROPN
alkej-30	57	17	)	)	PUNCT
alkej-30	57	18	called	call	VERB
alkej-30	57	19	lookuptables	lookuptable	NOUN
alkej-30	57	20	(	(	PUNCT
alkej-30	57	21	luts	luts	PROPN
alkej-30	57	22	)	)	PUNCT
alkej-30	57	23	.	.	PUNCT
alkej-30	58	1	these	these	DET
alkej-30	58	2	lcs	lcs	PROPN
alkej-30	58	3	are	be	AUX
alkej-30	58	4	formed	form	VERB
alkej-30	58	5	as	as	ADP
alkej-30	58	6	ram	ram	NOUN
alkej-30	58	7	to	to	PART
alkej-30	58	8	store	store	VERB
alkej-30	58	9	the	the	DET
alkej-30	58	10	output	output	NOUN
alkej-30	58	11	value	value	NOUN
alkej-30	58	12	of	of	ADP
alkej-30	58	13	this	this	DET
alkej-30	58	14	function	function	NOUN
alkej-30	58	15	in	in	ADP
alkej-30	58	16	each	each	DET
alkej-30	58	17	unit	unit	NOUN
alkej-30	58	18	in	in	ADP
alkej-30	58	19	the	the	DET
alkej-30	58	20	nn	nn	PROPN
alkej-30	58	21	algorithm	algorithm	NOUN
alkej-30	58	22	.	.	PUNCT
alkej-30	59	1	for	for	ADP
alkej-30	59	2	30	30	NUM
alkej-30	59	3	-	-	PUNCT
alkej-30	59	4	bit	bit	NOUN
alkej-30	59	5	flotation	flotation	NOUN
alkej-30	59	6	-	-	PUNCT
alkej-30	59	7	point	point	NOUN
alkej-30	59	8	,	,	PUNCT
alkej-30	59	9	ram	ram	NOUN
alkej-30	59	10	cost	cost	NOUN
alkej-30	59	11	implementation	implementation	NOUN
alkej-30	59	12	in	in	ADP
alkej-30	59	13	fpga	fpga	PROPN
alkej-30	59	14	30	30	NUM
alkej-30	59	15	-	-	PUNCT
alkej-30	59	16	bit	bit	NOUN
alkej-30	59	17	input	input	NOUN
alkej-30	59	18	and	and	CCONJ
alkej-30	59	19	30bit	30bit	NOUN
alkej-30	59	20	output	output	NOUN
alkej-30	59	21	,	,	PUNCT
alkej-30	59	22	for	for	ADP
alkej-30	59	23	each	each	DET
alkej-30	59	24	unit	unit	NOUN
alkej-30	59	25	in	in	ADP
alkej-30	59	26	nn	nn	PROPN
alkej-30	59	27	algorithm	algorithm	NOUN
alkej-30	59	28	.	.	PUNCT
alkej-30	60	1	then	then	ADV
alkej-30	60	2	,	,	PUNCT
alkej-30	60	3	when	when	SCONJ
alkej-30	60	4	sigmoid	sigmoid	NOUN
alkej-30	60	5	function	function	NOUN
alkej-30	60	6	applied	apply	VERB
alkej-30	60	7	in	in	ADP
alkej-30	60	8	algorithm	algorithm	NOUN
alkej-30	60	9	design	design	NOUN
alkej-30	60	10	is	be	AUX
alkej-30	60	11	increased	increase	VERB
alkej-30	60	12	number	number	NOUN
alkej-30	60	13	of	of	ADP
alkej-30	60	14	lcs	lcs	NOUN
alkej-30	60	15	,	,	PUNCT
alkej-30	60	16	so	so	SCONJ
alkej-30	60	17	that	that	SCONJ
alkej-30	60	18	,	,	PUNCT
alkej-30	60	19	it	it	PRON
alkej-30	60	20	increased	increase	VERB
alkej-30	60	21	the	the	DET
alkej-30	60	22	over	over	ADP
alkej-30	60	23	all	all	PRON
alkej-30	60	24	hardware	hardware	NOUN
alkej-30	60	25	resources	resource	NOUN
alkej-30	60	26	of	of	ADP
alkej-30	60	27	nn	nn	X
alkej-30	60	28	algorithm	algorithm	NOUN
alkej-30	60	29	.	.	PUNCT
alkej-30	61	1	the	the	DET
alkej-30	61	2	average	average	ADJ
alkej-30	61	3	cost	cost	NOUN
alkej-30	61	4	of	of	ADP
alkej-30	61	5	each	each	DET
alkej-30	61	6	unit	unit	NOUN
alkej-30	61	7	(	(	PUNCT
alkej-30	61	8	node	node	NOUN
alkej-30	61	9	)	)	PUNCT
alkej-30	61	10	is	be	AUX
alkej-30	61	11	calculated	calculate	VERB
alkej-30	61	12	according	accord	VERB
alkej-30	61	13	to	to	ADP
alkej-30	61	14	equation	equation	NOUN
alkej-30	61	15	(	(	PUNCT
alkej-30	61	16	1	1	NUM
alkej-30	61	17	)	)	PUNCT
alkej-30	61	18	.	.	PUNCT
alkej-30	62	1			VERB
alkej-30	62	2			PUNCT
alkej-30	62	3	*	*	PUNCT
alkej-30	62	4	*	*	PUNCT
alkej-30	62	5	/	/	SYM
alkej-30	62	6	nnunitcost	nnunitcost	ADJ
alkej-30	62	7	(	(	PUNCT
alkej-30	62	8	1	1	NUM
alkej-30	62	9	)	)	PUNCT
alkej-30	62	10	where	where	SCONJ
alkej-30	62	11	,	,	PUNCT
alkej-30	62	12	n	n	NOUN
alkej-30	62	13	=	=	NOUN
alkej-30	62	14	number	number	NOUN
alkej-30	62	15	of	of	ADP
alkej-30	62	16	bits	bit	NOUN
alkej-30	62	17	in	in	ADP
alkej-30	62	18	data	datum	NOUN
alkej-30	62	19	bus	bus	NOUN
alkej-30	62	20	.	.	PUNCT
alkej-30	63	1	α	α	NOUN
alkej-30	63	2	=	=	NOUN
alkej-30	63	3	cost	cost	NOUN
alkej-30	63	4	for	for	ADP
alkej-30	63	5	each	each	DET
alkej-30	63	6	multiplier	multipli	ADJ
alkej-30	63	7	in	in	ADP
alkej-30	63	8	fpga	fpga	PROPN
alkej-30	63	9	.	.	PUNCT
alkej-30	64	1	β	β	X
alkej-30	64	2	=	=	PUNCT
alkej-30	64	3	cost	cost	NOUN
alkej-30	64	4	for	for	ADP
alkej-30	64	5	each	each	DET
alkej-30	64	6	adder	adder	NOUN
alkej-30	64	7	/	/	SYM
alkej-30	64	8	subtractor	subtractor	NOUN
alkej-30	64	9	in	in	ADP
alkej-30	64	10	fpga	fpga	PROPN
alkej-30	64	11	.	.	PUNCT
alkej-30	65	1	δ	δ	X
alkej-30	65	2	=	=	PUNCT
alkej-30	65	3	cost	cost	NOUN
alkej-30	65	4	for	for	ADP
alkej-30	65	5	each	each	DET
alkej-30	65	6	lut	lut	PROPN
alkej-30	65	7	in	in	ADP
alkej-30	65	8	fpga	fpga	PROPN
alkej-30	65	9	for	for	ADP
alkej-30	65	10	sigmoid	sigmoid	NOUN
alkej-30	65	11	function	function	NOUN
alkej-30	65	12	.	.	PUNCT
alkej-30	66	1	ifor	ifor	PROPN
alkej-30	66	2	n=30	n=30	PROPN
alkej-30	66	3	bit	bite	VERB
alkej-30	66	4	with	with	ADP
alkej-30	66	5	sigmoid	sigmoid	NOUN
alkej-30	66	6	function	function	NOUN
alkej-30	66	7	α	α	PROPN
alkej-30	66	8	is	be	AUX
alkej-30	66	9	a	a	DET
alkej-30	66	10	(	(	PUNCT
alkej-30	66	11	30	30	NUM
alkej-30	66	12	*	*	SYM
alkej-30	66	13	30)-bit	30)-bit	NUM
alkej-30	66	14	multiplier	multipli	ADJ
alkej-30	66	15	and	and	CCONJ
alkej-30	66	16	require	require	VERB
alkej-30	66	17	about	about	ADP
alkej-30	66	18	(	(	PUNCT
alkej-30	66	19	2250	2250	NUM
alkej-30	66	20	)	)	PUNCT
alkej-30	66	21	cell	cell	NOUN
alkej-30	66	22	.	.	PUNCT
alkej-30	67	1	β	β	X
alkej-30	67	2	is	be	AUX
alkej-30	67	3	a	a	DET
alkej-30	67	4	30	30	NUM
alkej-30	67	5	-	-	PUNCT
alkej-30	67	6	bit	bit	NOUN
alkej-30	67	7	adder	adder	NOUN
alkej-30	67	8	/	/	SYM
alkej-30	67	9	subtractor	subtractor	NOUN
alkej-30	67	10	and	and	CCONJ
alkej-30	67	11	require	require	VERB
alkej-30	67	12	about	about	ADP
alkej-30	67	13	(	(	PUNCT
alkej-30	67	14	225	225	NUM
alkej-30	67	15	)	)	PUNCT
alkej-30	67	16	cell	cell	NOUN
alkej-30	67	17	.	.	PUNCT
alkej-30	68	1	finally	finally	ADV
alkej-30	68	2	δ	δ	PROPN
alkej-30	68	3	requires	require	VERB
alkej-30	68	4	about	about	ADP
alkej-30	68	5	(	(	PUNCT
alkej-30	68	6	125000	125000	NUM
alkej-30	68	7	)	)	PUNCT
alkej-30	68	8	cell	cell	NOUN
alkej-30	68	9	using	use	VERB
alkej-30	68	10	cordic	cordic	ADJ
alkej-30	68	11	approach	approach	NOUN
alkej-30	68	12	.	.	PUNCT
alkej-30	69	1	so	so	ADV
alkej-30	69	2	that	that	SCONJ
alkej-30	69	3	,	,	PUNCT
alkej-30	69	4	the	the	DET
alkej-30	69	5	cost	cost	NOUN
alkej-30	69	6	of	of	ADP
alkej-30	69	7	arithmetic	arithmetic	ADJ
alkej-30	69	8	components	component	NOUN
alkej-30	69	9	/	/	SYM
alkej-30	69	10	unit	unit	NOUN
alkej-30	69	11	(	(	PUNCT
alkej-30	69	12	for	for	ADP
alkej-30	69	13	30	30	NUM
alkej-30	69	14	-	-	PUNCT
alkej-30	69	15	bit	bit	NOUN
alkej-30	69	16	sigmoid	sigmoid	NOUN
alkej-30	69	17	)	)	PUNCT
alkej-30	69	18			NUM
alkej-30	69	19	200,000	200,000	NUM
alkej-30	69	20	cell	cell	NOUN
alkej-30	69	21	.	.	PUNCT
alkej-30	70	1	therefore	therefore	ADV
alkej-30	70	2	for	for	ADP
alkej-30	70	3	english	english	PROPN
alkej-30	70	4	digit	digit	NOUN
alkej-30	70	5	nn	nn	PROPN
alkej-30	70	6	algorithm	algorithm	NOUN
alkej-30	70	7	from	from	ADP
alkej-30	70	8	previously	previously	ADV
alkej-30	70	9	,	,	PUNCT
alkej-30	70	10	there	there	PRON
alkej-30	70	11	are	be	VERB
alkej-30	70	12	seventy	seventy	NUM
alkej-30	70	13	units	unit	NOUN
alkej-30	70	14	then	then	ADV
alkej-30	70	15	:	:	PUNCT
alkej-30	70	16	total	total	ADJ
alkej-30	70	17	cost	cost	NOUN
alkej-30	70	18	(	(	PUNCT
alkej-30	70	19	for	for	ADP
alkej-30	70	20	english	english	PROPN
alkej-30	70	21	digit	digit	PROPN
alkej-30	70	22	nn	nn	PROPN
alkej-30	70	23	)	)	PUNCT
alkej-30	70	24	=	=	NOUN
alkej-30	70	25	200,000	200,000	NUM
alkej-30	70	26	*	*	SYM
alkej-30	70	27	70	70	NUM
alkej-30	70	28	=	=	SYM
alkej-30	70	29	14,000,000	14,000,000	NUM
alkej-30	70	30	cell	cell	NOUN
alkej-30	70	31	.	.	PUNCT
alkej-30	71	1	this	this	DET
alkej-30	71	2	process	process	NOUN
alkej-30	71	3	can	can	AUX
alkej-30	71	4	be	be	AUX
alkej-30	71	5	achieved	achieve	VERB
alkej-30	71	6	approximately	approximately	ADV
alkej-30	71	7	by	by	ADP
alkej-30	71	8	17	17	NUM
alkej-30	71	9	of	of	ADP
alkej-30	71	10	propagation	propagation	NOUN
alkej-30	71	11	gates	gate	NOUN
alkej-30	71	12	delay	delay	NOUN
alkej-30	71	13	.	.	PUNCT
alkej-30	72	1	activation	activation	NOUN
alkej-30	72	2	function	function	NOUN
alkej-30	72	3	quantization	quantization	NOUN
alkej-30	72	4	error	error	NOUN
alkej-30	72	5	without	without	ADP
alkej-30	72	6	truncation	truncation	NOUN
alkej-30	72	7	(	(	PUNCT
alkej-30	72	8	30	30	NUM
alkej-30	72	9	-	-	PUNCT
alkej-30	72	10	bit	bit	NOUN
alkej-30	72	11	)	)	PUNCT
alkej-30	72	12	direct	direct	ADJ
alkej-30	72	13	truncation	truncation	NOUN
alkej-30	72	14	after	after	ADP
alkej-30	72	15	learning	learn	VERB
alkej-30	72	16	(	(	PUNCT
alkej-30	72	17	10	10	NUM
alkej-30	72	18	-	-	PUNCT
alkej-30	72	19	bit	bit	NOUN
alkej-30	72	20	)	)	PUNCT
alkej-30	72	21	sigmoid	sigmoid	NOUN
alkej-30	72	22	bipolar	bipolar	ADJ
alkej-30	72	23	2	2	NUM
alkej-30	72	24	%	%	NOUN
alkej-30	72	25	4	4	NUM
alkej-30	72	26	%	%	NOUN
alkej-30	72	27	13	13	NUM
alkej-30	72	28	-	-	SYM
alkej-30	72	29	19	19	NUM
alkej-30	72	30	%	%	NOUN
alkej-30	72	31	18	18	NUM
alkej-30	72	32	-	-	SYM
alkej-30	72	33	26	26	NUM
alkej-30	72	34	%	%	NOUN
alkej-30	72	35	table	table	NOUN
alkej-30	72	36	(	(	PUNCT
alkej-30	72	37	1	1	NUM
alkej-30	72	38	):	):	PUNCT
alkej-30	72	39	quntization	quntization	NOUN
alkej-30	72	40	error	error	NOUN
alkej-30	72	41	with	with	ADP
alkej-30	72	42	and	and	CCONJ
alkej-30	72	43	without	without	ADP
alkej-30	72	44	truncation	truncation	NOUN
alkej-30	72	45	ammar	ammar	PROPN
alkej-30	72	46	a.	a.	PROPN
alkej-30	72	47	hassan	hassan	PROPN
alkej-30	72	48	/al	/al	PROPN
alkej-30	72	49	-	-	PUNCT
alkej-30	72	50	khwarizmi	khwarizmi	PROPN
alkej-30	72	51	engineering	engineering	NOUN
alkej-30	72	52	journal	journal	PROPN
alkej-30	72	53	,	,	PUNCT
alkej-30	72	54	vol.2	vol.2	PROPN
alkej-30	72	55	,	,	PUNCT
alkej-30	72	56	no	no	INTJ
alkej-30	72	57	.	.	NOUN
alkej-30	72	58	2	2	NUM
alkej-30	72	59	pp	pp	ADP
alkej-30	72	60	32	32	NUM
alkej-30	72	61	-	-	SYM
alkej-30	72	62	41	41	NUM
alkej-30	72	63	(	(	PUNCT
alkej-30	72	64	2006	2006	NUM
alkej-30	72	65	)	)	PUNCT
alkej-30	72	66	23	23	NUM
alkej-30	72	67	iiwhen	iiwhen	ADJ
alkej-30	72	68	applying	apply	VERB
alkej-30	72	69	truncation	truncation	NOUN
alkej-30	72	70	technique	technique	NOUN
alkej-30	72	71	through	through	ADP
alkej-30	72	72	the	the	DET
alkej-30	72	73	learning	learning	NOUN
alkej-30	72	74	process	process	NOUN
alkej-30	72	75	with	with	ADP
alkej-30	72	76	sigmoid	sigmoid	NOUN
alkej-30	72	77	function	function	NOUN
alkej-30	72	78	on	on	ADP
alkej-30	72	79	ann	ann	PROPN
alkej-30	72	80	,	,	PUNCT
alkej-30	72	81	the	the	DET
alkej-30	72	82	unit	unit	NOUN
alkej-30	72	83	output	output	NOUN
alkej-30	72	84	precision	precision	NOUN
alkej-30	72	85	reduces	reduce	VERB
alkej-30	72	86	to	to	PART
alkej-30	72	87	be	be	AUX
alkej-30	72	88	10	10	NUM
alkej-30	72	89	-	-	PUNCT
alkej-30	72	90	bit	bit	NOUN
alkej-30	72	91	and	and	CCONJ
alkej-30	72	92	using	use	VERB
alkej-30	72	93	equation	equation	NOUN
alkej-30	72	94	(	(	PUNCT
alkej-30	72	95	1	1	NUM
alkej-30	72	96	)	)	PUNCT
alkej-30	72	97	.	.	PUNCT
alkej-30	73	1	total	total	ADJ
alkej-30	73	2	cost	cost	NOUN
alkej-30	73	3	/	/	SYM
alkej-30	73	4	unit	unit	NOUN
alkej-30	73	5			ADP
alkej-30	73	6	4000	4000	NUM
alkej-30	73	7	cell	cell	NOUN
alkej-30	73	8	.	.	PUNCT
alkej-30	74	1	where	where	SCONJ
alkej-30	74	2	n	n	ADV
alkej-30	74	3	=	=	SYM
alkej-30	74	4	10	10	NUM
alkej-30	74	5	-	-	PUNCT
alkej-30	74	6	bit	bit	NOUN
alkej-30	74	7	,	,	PUNCT
alkej-30	74	8	α	α	NOUN
alkej-30	74	9	=	=	SYM
alkej-30	74	10	300	300	NUM
alkej-30	74	11	cell	cell	NOUN
alkej-30	74	12	,	,	PUNCT
alkej-30	74	13	β	β	X
alkej-30	74	14	=	=	SYM
alkej-30	74	15	75	75	NUM
alkej-30	74	16	cell	cell	NOUN
alkej-30	74	17	,	,	PUNCT
alkej-30	74	18	and	and	CCONJ
alkej-30	74	19	δ	δ	PROPN
alkej-30	74	20	=	=	NOUN
alkej-30	75	1	60	60	NUM
alkej-30	75	2	cell	cell	NOUN
alkej-30	75	3	.	.	PUNCT
alkej-30	76	1	total	total	ADJ
alkej-30	76	2	cost	cost	NOUN
alkej-30	76	3	(	(	PUNCT
alkej-30	76	4	for	for	ADP
alkej-30	76	5	english	english	PROPN
alkej-30	76	6	digit	digit	NOUN
alkej-30	76	7	nn	nn	PROPN
alkej-30	76	8	)	)	PUNCT
alkej-30	76	9	=	=	SYM
alkej-30	76	10	4000	4000	NUM
alkej-30	76	11	*	*	SYM
alkej-30	76	12	70	70	NUM
alkej-30	76	13	=	=	SYM
alkej-30	76	14	280,000	280,000	NUM
alkej-30	76	15	cell	cell	NOUN
alkej-30	76	16	with	with	ADP
alkej-30	76	17	over	over	ADP
alkej-30	76	18	all	all	DET
alkej-30	76	19	propagation	propagation	NOUN
alkej-30	76	20	delay	delay	NOUN
alkej-30	76	21	reduced	reduce	VERB
alkej-30	76	22	to	to	ADP
alkej-30	76	23	7	7	NUM
alkej-30	76	24	propagation	propagation	NOUN
alkej-30	76	25	gates	gate	NOUN
alkej-30	76	26	delay	delay	NOUN
alkej-30	76	27	.	.	PUNCT
alkej-30	77	1	from	from	ADP
alkej-30	77	2	this	this	DET
alkej-30	77	3	result	result	NOUN
alkej-30	77	4	,	,	PUNCT
alkej-30	77	5	when	when	SCONJ
alkej-30	77	6	applying	apply	VERB
alkej-30	77	7	this	this	DET
alkej-30	77	8	technique	technique	NOUN
alkej-30	77	9	in	in	ADP
alkej-30	77	10	nn	nn	PROPN
alkej-30	77	11	algorithm	algorithm	NOUN
alkej-30	77	12	design	design	NOUN
alkej-30	77	13	it	it	PRON
alkej-30	77	14	can	can	AUX
alkej-30	77	15	reduce	reduce	VERB
alkej-30	77	16	number	number	NOUN
alkej-30	77	17	of	of	ADP
alkej-30	77	18	luts	luts	PROPN
alkej-30	77	19	on	on	ADP
alkej-30	77	20	fpga	fpga	PROPN
alkej-30	77	21	and	and	CCONJ
alkej-30	77	22	so	so	ADV
alkej-30	77	23	reduce	reduce	VERB
alkej-30	77	24	the	the	DET
alkej-30	77	25	over	over	ADP
alkej-30	77	26	all	all	DET
alkej-30	77	27	hardware	hardware	NOUN
alkej-30	77	28	resources	resource	NOUN
alkej-30	77	29	capacity	capacity	NOUN
alkej-30	77	30	.	.	PUNCT
alkej-30	78	1	4.2.bipolar	4.2.bipolar	NUM
alkej-30	78	2	function	function	NOUN
alkej-30	78	3	as	as	SCONJ
alkej-30	78	4	demonstrated	demonstrate	VERB
alkej-30	78	5	from	from	ADP
alkej-30	78	6	previous	previous	ADJ
alkej-30	78	7	section	section	NOUN
alkej-30	78	8	,	,	PUNCT
alkej-30	78	9	it	it	PRON
alkej-30	78	10	required	require	VERB
alkej-30	78	11	a	a	DET
alkej-30	78	12	large	large	ADJ
alkej-30	78	13	number	number	NOUN
alkej-30	78	14	of	of	ADP
alkej-30	78	15	cells	cell	NOUN
alkej-30	78	16	to	to	PART
alkej-30	78	17	implement	implement	VERB
alkej-30	78	18	nn	nn	PROPN
alkej-30	78	19	based	base	VERB
alkej-30	78	20	on	on	ADP
alkej-30	78	21	sigmoid	sigmoid	NOUN
alkej-30	78	22	function	function	NOUN
alkej-30	78	23	.	.	PUNCT
alkej-30	79	1	then	then	ADV
alkej-30	79	2	,	,	PUNCT
alkej-30	79	3	bipolar	bipolar	ADJ
alkej-30	79	4	function	function	NOUN
alkej-30	79	5	instead	instead	ADV
alkej-30	79	6	of	of	ADP
alkej-30	79	7	sigmoid	sigmoid	NOUN
alkej-30	79	8	function	function	NOUN
alkej-30	79	9	in	in	ADP
alkej-30	79	10	a	a	DET
alkej-30	79	11	nn	nn	X
alkej-30	79	12	algorithm	algorithm	NOUN
alkej-30	79	13	can	can	AUX
alkej-30	79	14	be	be	AUX
alkej-30	79	15	used	use	VERB
alkej-30	79	16	.	.	PUNCT
alkej-30	80	1	where	where	SCONJ
alkej-30	80	2	,	,	PUNCT
alkej-30	80	3	this	this	DET
alkej-30	80	4	function	function	NOUN
alkej-30	80	5	does	do	AUX
alkej-30	80	6	not	not	PART
alkej-30	80	7	need	need	VERB
alkej-30	80	8	storage	storage	NOUN
alkej-30	80	9	cells	cell	NOUN
alkej-30	80	10	for	for	ADP
alkej-30	80	11	the	the	DET
alkej-30	80	12	output	output	NOUN
alkej-30	80	13	values	value	NOUN
alkej-30	80	14	in	in	ADP
alkej-30	80	15	luts	luts	PROPN
alkej-30	80	16	,	,	PUNCT
alkej-30	80	17	because	because	SCONJ
alkej-30	80	18	the	the	DET
alkej-30	80	19	output	output	NOUN
alkej-30	80	20	from	from	ADP
alkej-30	80	21	this	this	DET
alkej-30	80	22	function	function	NOUN
alkej-30	80	23	is	be	AUX
alkej-30	80	24	either	either	CCONJ
alkej-30	80	25	“	"	PUNCT
alkej-30	80	26	-1	-1	ADJ
alkej-30	80	27	”	"	PUNCT
alkej-30	80	28	or	or	CCONJ
alkej-30	80	29	“	"	PUNCT
alkej-30	80	30	1	1	NUM
alkej-30	80	31	”	"	PUNCT
alkej-30	80	32	,	,	PUNCT
alkej-30	80	33	this	this	DET
alkej-30	80	34	technique	technique	NOUN
alkej-30	80	35	called	call	VERB
alkej-30	80	36	multiplierless	multiplierless	NOUN
alkej-30	80	37	technique	technique	NOUN
alkej-30	80	38	.	.	PUNCT
alkej-30	81	1	this	this	DET
alkej-30	81	2	approach	approach	NOUN
alkej-30	81	3	has	have	VERB
alkej-30	81	4	α	α	NOUN
alkej-30	81	5	=	=	SYM
alkej-30	81	6	1	1	NUM
alkej-30	81	7	cell	cell	NOUN
alkej-30	81	8	and	and	CCONJ
alkej-30	81	9	δ=0	δ=0	NOUN
alkej-30	81	10	cell	cell	NOUN
alkej-30	81	11	therefore	therefore	ADV
alkej-30	81	12	,	,	PUNCT
alkej-30	81	13	the	the	DET
alkej-30	81	14	cost	cost	NOUN
alkej-30	81	15	for	for	ADP
alkej-30	81	16	each	each	DET
alkej-30	81	17	unit	unit	NOUN
alkej-30	81	18	in	in	ADP
alkej-30	81	19	a	a	DET
alkej-30	81	20	nn	nn	X
alkej-30	81	21	algorithm	algorithm	NOUN
alkej-30	81	22	based	base	VERB
alkej-30	81	23	bipolar	bipolar	ADJ
alkej-30	81	24	function	function	NOUN
alkej-30	81	25	calculated	calculate	VERB
alkej-30	81	26	using	use	VERB
alkej-30	81	27	equation	equation	NOUN
alkej-30	81	28	(	(	PUNCT
alkej-30	81	29	2	2	NUM
alkej-30	81	30	)	)	PUNCT
alkej-30	81	31	.	.	PUNCT
alkej-30	82	1	*/	*/	PROPN
alkej-30	82	2	nnunitcost	nnunitcost	PROPN
alkej-30	82	3			PROPN
alkej-30	82	4	(	(	PUNCT
alkej-30	82	5	2	2	NUM
alkej-30	82	6	)	)	PUNCT
alkej-30	82	7	n	n	NOUN
alkej-30	82	8	=	=	NOUN
alkej-30	82	9	number	number	NOUN
alkej-30	82	10	of	of	ADP
alkej-30	82	11	bits	bit	NOUN
alkej-30	82	12	in	in	ADP
alkej-30	82	13	data	datum	NOUN
alkej-30	82	14	bus	bus	NOUN
alkej-30	82	15	.	.	PUNCT
alkej-30	83	1	β	β	X
alkej-30	83	2	=	=	PUNCT
alkej-30	83	3	cost	cost	NOUN
alkej-30	83	4	for	for	ADP
alkej-30	83	5	each	each	DET
alkej-30	83	6	adder	adder	NOUN
alkej-30	83	7	/	/	SYM
alkej-30	83	8	subtractor	subtractor	NOUN
alkej-30	83	9	in	in	ADP
alkej-30	83	10	fpga	fpga	PROPN
alkej-30	83	11	.	.	PUNCT
alkej-30	84	1	iwithout	iwithout	PROPN
alkej-30	84	2	truncation	truncation	NOUN
alkej-30	84	3	technique	technique	NOUN
alkej-30	84	4	(	(	PUNCT
alkej-30	84	5	i.e.	i.e.	X
alkej-30	84	6	n=30	n=30	NOUN
alkej-30	84	7	-	-	PUNCT
alkej-30	84	8	bit	bit	NOUN
alkej-30	84	9	)	)	PUNCT
alkej-30	85	1	β	β	NOUN
alkej-30	85	2	=	=	NOUN
alkej-30	85	3	215	215	NUM
alkej-30	85	4	cell	cell	NOUN
alkej-30	85	5	,	,	PUNCT
alkej-30	85	6	therefor	therefor	ADP
alkej-30	85	7	the	the	DET
alkej-30	85	8	cost	cost	NOUN
alkej-30	85	9	/	/	SYM
alkej-30	85	10	unit	unit	NOUN
alkej-30	85	11			ADP
alkej-30	85	12	6,500	6,500	NUM
alkej-30	85	13	cell	cell	NOUN
alkej-30	85	14	.	.	PUNCT
alkej-30	86	1	this	this	DET
alkej-30	86	2	process	process	NOUN
alkej-30	86	3	exceeds	exceed	VERB
alkej-30	86	4	in	in	ADP
alkej-30	86	5	17	17	NUM
alkej-30	86	6	propagation	propagation	NOUN
alkej-30	86	7	gates	gate	NOUN
alkej-30	86	8	delay	delay	NOUN
alkej-30	86	9	.	.	PUNCT
alkej-30	87	1	then	then	ADV
alkej-30	87	2	,	,	PUNCT
alkej-30	87	3	to	to	PART
alkej-30	87	4	implement	implement	VERB
alkej-30	87	5	the	the	DET
alkej-30	87	6	english	english	PROPN
alkej-30	87	7	digit	digit	PROPN
alkej-30	87	8	nn	nn	PROPN
alkej-30	87	9	,	,	PUNCT
alkej-30	87	10	that	that	PRON
alkej-30	87	11	included	include	VERB
alkej-30	87	12	70	70	NUM
alkej-30	87	13	active	active	ADJ
alkej-30	87	14	neurons	neuron	NOUN
alkej-30	87	15	the	the	DET
alkej-30	87	16	total	total	ADJ
alkej-30	87	17	cost	cost	NOUN
alkej-30	87	18			ADP
alkej-30	87	19	455,000	455,000	NUM
alkej-30	87	20	cell	cell	NOUN
alkej-30	87	21	.	.	PUNCT
alkej-30	88	1	iiwith	iiwith	ADP
alkej-30	88	2	truncation	truncation	NOUN
alkej-30	88	3	technique	technique	NOUN
alkej-30	88	4	(	(	PUNCT
alkej-30	88	5	i.e.	i.e.	X
alkej-30	88	6	n=10	n=10	NOUN
alkej-30	88	7	-	-	PUNCT
alkej-30	88	8	bit	bit	NOUN
alkej-30	88	9	)	)	PUNCT
alkej-30	88	10	β	β	NOUN
alkej-30	88	11	=	=	SYM
alkej-30	88	12	64	64	NUM
alkej-30	88	13	cell	cell	NOUN
alkej-30	88	14	,	,	PUNCT
alkej-30	88	15	therefor	therefor	ADP
alkej-30	88	16	the	the	DET
alkej-30	88	17	cost	cost	NOUN
alkej-30	88	18	/	/	SYM
alkej-30	88	19	unit	unit	NOUN
alkej-30	88	20	=	=	NOUN
alkej-30	88	21	650	650	NUM
alkej-30	88	22	cell	cell	NOUN
alkej-30	88	23	.	.	PUNCT
alkej-30	89	1	also	also	ADV
alkej-30	89	2	,	,	PUNCT
alkej-30	89	3	this	this	DET
alkej-30	89	4	process	process	NOUN
alkej-30	89	5	exceeds	exceed	VERB
alkej-30	89	6	in	in	ADP
alkej-30	89	7	7	7	NUM
alkej-30	89	8	propagation	propagation	NOUN
alkej-30	89	9	gates	gate	NOUN
alkej-30	89	10	delay	delay	NOUN
alkej-30	89	11	.	.	PUNCT
alkej-30	90	1	so	so	ADV
alkej-30	90	2	that	that	SCONJ
alkej-30	90	3	,	,	PUNCT
alkej-30	90	4	to	to	PART
alkej-30	90	5	implement	implement	VERB
alkej-30	90	6	the	the	DET
alkej-30	90	7	english	english	PROPN
alkej-30	90	8	digit	digit	NOUN
alkej-30	90	9	nn	nn	PROPN
alkej-30	90	10	that	that	PRON
alkej-30	90	11	included	include	VERB
alkej-30	90	12	70	70	NUM
alkej-30	90	13	neurons	neuron	NOUN
alkej-30	90	14	the	the	DET
alkej-30	90	15	total	total	ADJ
alkej-30	90	16	cost	cost	NOUN
alkej-30	90	17			ADP
alkej-30	90	18	45,500	45,500	NUM
alkej-30	90	19	cell	cell	NOUN
alkej-30	90	20	.	.	PUNCT
alkej-30	91	1	then	then	ADV
alkej-30	91	2	,	,	PUNCT
alkej-30	91	3	the	the	DET
alkej-30	91	4	total	total	ADJ
alkej-30	91	5	luts	luts	PROPN
alkej-30	91	6	cost	cost	NOUN
alkej-30	91	7	of	of	ADP
alkej-30	91	8	nn	nn	PROPN
alkej-30	91	9	can	can	AUX
alkej-30	91	10	be	be	AUX
alkej-30	91	11	reduced	reduce	VERB
alkej-30	91	12	when	when	SCONJ
alkej-30	91	13	applying	apply	VERB
alkej-30	91	14	bipolar	bipolar	ADJ
alkej-30	91	15	function	function	NOUN
alkej-30	91	16	with	with	ADP
alkej-30	91	17	truncation	truncation	NOUN
alkej-30	91	18	technique	technique	NOUN
alkej-30	91	19	on	on	ADP
alkej-30	91	20	fpgas	fpgas	NOUN
alkej-30	91	21	.	.	PUNCT
alkej-30	92	1	5.proposed	5.proposed	NUM
alkej-30	92	2	backpropagation	backpropagation	NOUN
alkej-30	92	3	algorithm	algorithm	NOUN
alkej-30	92	4	[	[	X
alkej-30	92	5	5	5	NUM
alkej-30	92	6	]	]	PUNCT
alkej-30	92	7	an	an	DET
alkej-30	92	8	ann	ann	PROPN
alkej-30	92	9	using	use	VERB
alkej-30	92	10	the	the	DET
alkej-30	92	11	classic	classic	ADJ
alkej-30	92	12	backpropagation	backpropagation	NOUN
alkej-30	92	13	algorithm	algorithm	NOUN
alkej-30	92	14	[	[	X
alkej-30	92	15	6	6	NUM
alkej-30	92	16	]	]	PUNCT
alkej-30	92	17	as	as	ADP
alkej-30	92	18	in	in	ADP
alkej-30	92	19	fig.(2	fig.(2	NOUN
alkej-30	92	20	)	)	PUNCT
alkej-30	92	21	has	have	VERB
alkej-30	92	22	three	three	NUM
alkej-30	92	23	basic	basic	ADJ
alkej-30	92	24	phases	phase	NOUN
alkej-30	92	25	named	name	VERB
alkej-30	92	26	(	(	PUNCT
alkej-30	92	27	1	1	NUM
alkej-30	92	28	,	,	PUNCT
alkej-30	92	29	2	2	NUM
alkej-30	92	30	and	and	CCONJ
alkej-30	92	31	3	3	NUM
alkej-30	92	32	)	)	PUNCT
alkej-30	92	33	of	of	ADP
alkej-30	92	34	execution	execution	NOUN
alkej-30	92	35	the	the	DET
alkej-30	92	36	proposed	propose	VERB
alkej-30	92	37	backpropagation	backpropagation	NOUN
alkej-30	92	38	algorithm	algorithm	NOUN
alkej-30	92	39	has	have	VERB
alkej-30	92	40	same	same	ADJ
alkej-30	92	41	structure	structure	NOUN
alkej-30	92	42	of	of	ADP
alkej-30	92	43	the	the	DET
alkej-30	92	44	classic	classic	ADJ
alkej-30	92	45	backpropagation	backpropagation	NOUN
alkej-30	92	46	algorithm	algorithm	NOUN
alkej-30	92	47	with	with	ADP
alkej-30	92	48	three	three	NUM
alkej-30	92	49	additional	additional	ADJ
alkej-30	92	50	steps	step	NOUN
alkej-30	92	51	for	for	ADP
alkej-30	92	52	the	the	DET
alkej-30	92	53	proposed	propose	VERB
alkej-30	92	54	backpropagation	backpropagation	NOUN
alkej-30	92	55	algorithm	algorithm	NOUN
alkej-30	92	56	named	name	VERB
alkej-30	92	57	(	(	PUNCT
alkej-30	92	58	1a	1a	NOUN
alkej-30	92	59	,	,	PUNCT
alkej-30	92	60	2a	2a	NUM
alkej-30	92	61	and	and	CCONJ
alkej-30	92	62	3a	3a	NUM
alkej-30	92	63	)	)	PUNCT
alkej-30	92	64	as	as	ADP
alkej-30	92	65	following	follow	VERB
alkej-30	92	66	:	:	PUNCT
alkej-30	92	67	ammar	ammar	PROPN
alkej-30	92	68	a.	a.	PROPN
alkej-30	92	69	hassan	hassan	PROPN
alkej-30	92	70	/al	/al	PROPN
alkej-30	92	71	-	-	PUNCT
alkej-30	92	72	khwarizmi	khwarizmi	PROPN
alkej-30	92	73	engineering	engineering	NOUN
alkej-30	92	74	journal	journal	PROPN
alkej-30	92	75	,	,	PUNCT
alkej-30	92	76	vol.2	vol.2	PROPN
alkej-30	92	77	,	,	PUNCT
alkej-30	92	78	no	no	INTJ
alkej-30	92	79	.	.	NOUN
alkej-30	92	80	2	2	NUM
alkej-30	92	81	pp	pp	ADP
alkej-30	92	82	32	32	NUM
alkej-30	92	83	-	-	SYM
alkej-30	92	84	41	41	NUM
alkej-30	92	85	(	(	PUNCT
alkej-30	92	86	2006	2006	NUM
alkej-30	92	87	)	)	PUNCT
alkej-30	92	88	23	23	NUM
alkej-30	92	89	fig	fig	NOUN
alkej-30	92	90	.	.	PUNCT
alkej-30	93	1	(	(	PUNCT
alkej-30	93	2	2	2	NUM
alkej-30	93	3	):	):	PUNCT
alkej-30	93	4	generic	generic	ADJ
alkej-30	93	5	structure	structure	NOUN
alkej-30	93	6	of	of	ADP
alkej-30	93	7	an	an	DET
alkej-30	93	8	ann	ann	PROPN
alkej-30	93	9	.	.	PUNCT
alkej-30	94	1	5.1.initialization	5.1.initialization	NUM
alkej-30	94	2	the	the	DET
alkej-30	94	3	following	follow	VERB
alkej-30	94	4	initial	initial	ADJ
alkej-30	94	5	parameters	parameter	NOUN
alkej-30	94	6	have	have	VERB
alkej-30	94	7	to	to	PART
alkej-30	94	8	be	be	AUX
alkej-30	94	9	determined	determine	VERB
alkej-30	94	10	by	by	ADP
alkej-30	94	11	the	the	DET
alkej-30	94	12	ann	ann	PROPN
alkej-30	94	13	trainer	trainer	NOUN
alkej-30	94	14	a	a	X
alkej-30	94	15	priori	priori	ADV
alkej-30	94	16	:	:	PUNCT
alkej-30	94	17	(	(	PUNCT
alkej-30	94	18	i	i	NOUN
alkej-30	94	19	)	)	PUNCT
alkej-30	94	20	)	)	PUNCT
alkej-30	95	1	(	(	PUNCT
alkej-30	95	2	)	)	PUNCT
alkej-30	95	3	(	(	PUNCT
alkej-30	95	4	nw	nw	PROPN
alkej-30	95	5	s	s	X
alkej-30	95	6	kj	kj	PROPN
alkej-30	95	7	is	be	AUX
alkej-30	95	8	defined	define	VERB
alkej-30	95	9	as	as	ADP
alkej-30	95	10	the	the	DET
alkej-30	95	11	synaptic	synaptic	ADJ
alkej-30	95	12	weight	weight	NOUN
alkej-30	95	13	that	that	PRON
alkej-30	95	14	corresponds	correspond	VERB
alkej-30	95	15	to	to	ADP
alkej-30	95	16	the	the	DET
alkej-30	95	17	connection	connection	NOUN
alkej-30	95	18	from	from	ADP
alkej-30	95	19	neuron	neuron	PROPN
alkej-30	95	20	unit	unit	PROPN
alkej-30	95	21	j	j	PROPN
alkej-30	95	22	in	in	ADP
alkej-30	95	23	the	the	DET
alkej-30	95	24	(	(	PUNCT
alkej-30	95	25	s-1	s-1	PROPN
alkej-30	95	26	)	)	PUNCT
alkej-30	95	27	th	th	X
alkej-30	95	28	layer	layer	NOUN
alkej-30	95	29	,	,	PUNCT
alkej-30	95	30	to	to	ADP
alkej-30	95	31	k	k	PROPN
alkej-30	95	32	in	in	ADP
alkej-30	95	33	the	the	DET
alkej-30	95	34	s	s	X
alkej-30	95	35	th	th	NOUN
alkej-30	95	36	layer	layer	NOUN
alkej-30	95	37	of	of	ADP
alkej-30	95	38	the	the	DET
alkej-30	95	39	neural	neural	ADJ
alkej-30	95	40	network	network	NOUN
alkej-30	95	41	.	.	PUNCT
alkej-30	96	1	(	(	PUNCT
alkej-30	96	2	ii	ii	NOUN
alkej-30	96	3	)	)	PUNCT
alkej-30	96	4			NUM
alkej-30	96	5	is	be	AUX
alkej-30	96	6	defined	define	VERB
alkej-30	96	7	as	as	ADP
alkej-30	96	8	the	the	DET
alkej-30	96	9	learning	learning	NOUN
alkej-30	96	10	rate	rate	NOUN
alkej-30	96	11	and	and	CCONJ
alkej-30	96	12	is	be	AUX
alkej-30	96	13	a	a	DET
alkej-30	96	14	constant	constant	ADJ
alkej-30	96	15	scaling	scaling	NOUN
alkej-30	96	16	factor	factor	NOUN
alkej-30	96	17	.	.	PUNCT
alkej-30	97	1	(	(	PUNCT
alkej-30	97	2	iii	iii	NOUN
alkej-30	97	3	)	)	PUNCT
alkej-30	97	4	)	)	PUNCT
alkej-30	98	1	(	(	PUNCT
alkej-30	98	2	s	s	AUX
alkej-30	98	3	k	k	NOUN
alkej-30	98	4	is	be	AUX
alkej-30	98	5	defined	define	VERB
alkej-30	98	6	as	as	ADP
alkej-30	98	7	the	the	DET
alkej-30	98	8	bias	bias	NOUN
alkej-30	98	9	of	of	ADP
alkej-30	98	10	a	a	DET
alkej-30	98	11	neuron	neuron	NOUN
alkej-30	98	12	,	,	PUNCT
alkej-30	98	13	which	which	PRON
alkej-30	98	14	is	be	AUX
alkej-30	98	15	similar	similar	ADJ
alkej-30	98	16	to	to	ADP
alkej-30	98	17	synaptic	synaptic	ADJ
alkej-30	98	18	weight	weight	NOUN
alkej-30	98	19	in	in	SCONJ
alkej-30	98	20	that	that	SCONJ
alkej-30	98	21	it	it	PRON
alkej-30	98	22	corresponds	correspond	VERB
alkej-30	98	23	to	to	ADP
alkej-30	98	24	a	a	DET
alkej-30	98	25	connection	connection	NOUN
alkej-30	98	26	to	to	PART
alkej-30	98	27	neuron	neuron	PROPN
alkej-30	98	28	unit	unit	NOUN
alkej-30	98	29	k	k	PROPN
alkej-30	98	30	in	in	ADP
alkej-30	98	31	the	the	DET
alkej-30	98	32	(	(	PUNCT
alkej-30	98	33	s-1)th	s-1)th	NOUN
alkej-30	98	34	layer	layer	NOUN
alkej-30	98	35	of	of	ADP
alkej-30	98	36	the	the	DET
alkej-30	98	37	ann	ann	PROPN
alkej-30	98	38	,	,	PUNCT
alkej-30	98	39	but	but	CCONJ
alkej-30	98	40	is	be	AUX
alkej-30	98	41	not	not	PART
alkej-30	98	42	connected	connect	VERB
alkej-30	98	43	to	to	ADP
alkej-30	98	44	any	any	DET
alkej-30	98	45	neuron	neuron	NOUN
alkej-30	98	46	unit	unit	PROPN
alkej-30	98	47	j	j	PROPN
alkej-30	98	48	in	in	ADP
alkej-30	98	49	the(s-1	the(s-1	PROPN
alkej-30	98	50	)	)	PUNCT
alkej-30	98	51	th	th	NOUN
alkej-30	98	52	layer	layer	NOUN
alkej-30	98	53	.	.	PUNCT
alkej-30	99	1	(	(	PUNCT
alkej-30	99	2	1a	1a	X
alkej-30	99	3	)	)	PUNCT
alkej-30	99	4	set	set	VERB
alkej-30	99	5	counter	counter	NOUN
alkej-30	99	6	=	=	NOUN
alkej-30	99	7	0	0	SYM
alkej-30	99	8	5.2.forward	5.2.forward	NUM
alkej-30	99	9	computation	computation	NOUN
alkej-30	99	10	during	during	ADP
alkej-30	99	11	the	the	DET
alkej-30	99	12	forward	forward	ADJ
alkej-30	99	13	computation	computation	NOUN
alkej-30	99	14	,	,	PUNCT
alkej-30	99	15	data	datum	NOUN
alkej-30	99	16	from	from	ADP
alkej-30	99	17	neurons	neuron	NOUN
alkej-30	99	18	of	of	ADP
alkej-30	99	19	a	a	DET
alkej-30	99	20	lower	low	ADJ
alkej-30	99	21	layer	layer	NOUN
alkej-30	99	22	(	(	PUNCT
alkej-30	99	23	i.e	i.e	X
alkej-30	99	24	(	(	PUNCT
alkej-30	99	25	s-1	s-1	PROPN
alkej-30	99	26	)	)	PUNCT
alkej-30	99	27	th	th	NOUN
alkej-30	99	28	layer	layer	NOUN
alkej-30	99	29	)	)	PUNCT
alkej-30	99	30	,	,	PUNCT
alkej-30	99	31	are	be	AUX
alkej-30	99	32	propagated	propagate	VERB
alkej-30	99	33	forward	forward	ADV
alkej-30	99	34	to	to	ADP
alkej-30	99	35	neurons	neuron	NOUN
alkej-30	99	36	in	in	ADP
alkej-30	99	37	the	the	DET
alkej-30	99	38	upper	upper	ADJ
alkej-30	99	39	layer	layer	NOUN
alkej-30	99	40	(	(	PUNCT
alkej-30	99	41	i.e.	i.e.	X
alkej-30	99	42	(	(	PUNCT
alkej-30	99	43	s	s	X
alkej-30	99	44	)	)	PUNCT
alkej-30	99	45	th	th	NOUN
alkej-30	99	46	layer	layer	NOUN
alkej-30	99	47	)	)	PUNCT
alkej-30	99	48	via	via	ADP
alkej-30	99	49	a	a	DET
alkej-30	99	50	feedforward	feedforward	ADJ
alkej-30	99	51	connection	connection	NOUN
alkej-30	99	52	network	network	NOUN
alkej-30	99	53	.	.	PUNCT
alkej-30	100	1	the	the	DET
alkej-30	100	2	structure	structure	NOUN
alkej-30	100	3	of	of	ADP
alkej-30	100	4	such	such	DET
alkej-30	100	5	a	a	DET
alkej-30	100	6	neural	neural	ADJ
alkej-30	100	7	network	network	NOUN
alkej-30	100	8	is	be	AUX
alkej-30	100	9	shown	show	VERB
alkej-30	100	10	in	in	ADP
alkej-30	100	11	figure	figure	NOUN
alkej-30	100	12	2	2	NUM
alkej-30	100	13	,	,	PUNCT
alkej-30	100	14	where	where	SCONJ
alkej-30	100	15	layers	layer	NOUN
alkej-30	100	16	are	be	AUX
alkej-30	100	17	numbered	number	VERB
alkej-30	100	18	0	0	PUNCT
alkej-30	100	19	to	to	ADP
alkej-30	100	20	m	m	PRON
alkej-30	100	21	,	,	PUNCT
alkej-30	100	22	and	and	CCONJ
alkej-30	100	23	neurons	neuron	NOUN
alkej-30	100	24	are	be	AUX
alkej-30	100	25	numbered	number	VERB
alkej-30	100	26	1	1	NUM
alkej-30	100	27	to	to	PART
alkej-30	100	28	n.	n.	VERB
alkej-30	100	29	the	the	DET
alkej-30	100	30	computation	computation	NOUN
alkej-30	100	31	performed	perform	VERB
alkej-30	100	32	by	by	ADP
alkej-30	100	33	each	each	DET
alkej-30	100	34	neuron	neuron	NOUN
alkej-30	100	35	(	(	PUNCT
alkej-30	100	36	in	in	ADP
alkej-30	100	37	the	the	DET
alkej-30	100	38	hidden	hide	VERB
alkej-30	100	39	layer	layer	NOUN
alkej-30	100	40	)	)	PUNCT
alkej-30	100	41	is	be	AUX
alkej-30	100	42	as	as	SCONJ
alkej-30	100	43	follows	follow	VERB
alkej-30	100	44	:	:	PUNCT
alkej-30	100	45	θowh	θowh	ADV
alkej-30	100	46	(	(	PUNCT
alkej-30	100	47	s	s	NOUN
alkej-30	100	48	)	)	PUNCT
alkej-30	100	49	k	k	NOUN
alkej-30	100	50	)	)	PUNCT
alkej-30	100	51	(	(	PUNCT
alkej-30	100	52	sj	sj	PROPN
alkej-30	100	53	s	s	PROPN
alkej-30	100	54	-	-	PUNCT
alkej-30	100	55	n	n	PRON
alkej-30	100	56	j	j	PROPN
alkej-30	100	57	(	(	PUNCT
alkej-30	100	58	s	s	PROPN
alkej-30	100	59	)	)	PUNCT
alkej-30	100	60	kj	kj	NOUN
alkej-30	100	61	(	(	PUNCT
alkej-30	100	62	s	s	NOUN
alkej-30	100	63	)	)	PUNCT
alkej-30	100	64	k	k	PROPN
alkej-30	100	65			ADV
alkej-30	100	66			PUNCT
alkej-30	101	1			NUM
alkej-30	101	2	1	1	NUM
alkej-30	101	3	)	)	PUNCT
alkej-30	101	4	1	1	NUM
alkej-30	101	5	(	(	PUNCT
alkej-30	101	6	1	1	NUM
alkej-30	101	7	(	(	PUNCT
alkej-30	101	8	3	3	NUM
alkej-30	101	9	)	)	PUNCT
alkej-30	101	10	where	where	SCONJ
alkej-30	101	11	j	j	PROPN
alkej-30	101	12	<	<	X
alkej-30	101	13	k	k	PROPN
alkej-30	101	14	and	and	CCONJ
alkej-30	101	15	s=1,	s=1,	PROPN
alkej-30	101	16	…	…	PROPN
alkej-30	101	17	.,m	.,m	NUM
alkej-30	101	18	)	)	PUNCT
alkej-30	101	19	1(s	1(s	NUM
alkej-30	101	20	-	-	SYM
alkej-30	101	21	n	n	CCONJ
alkej-30	101	22	=	=	NOUN
alkej-30	101	23	number	number	NOUN
alkej-30	101	24	of	of	ADP
alkej-30	101	25	neurons	neuron	NOUN
alkej-30	101	26	in	in	ADP
alkej-30	101	27	the	the	DET
alkej-30	101	28	(	(	PUNCT
alkej-30	101	29	s-1)th	s-1)th	NOUN
alkej-30	101	30	layer	layer	NOUN
alkej-30	101	31	of	of	ADP
alkej-30	101	32	the	the	DET
alkej-30	101	33	ann	ann	PROPN
alkej-30	101	34	.	.	PUNCT
alkej-30	101	35	)	)	PUNCT
alkej-30	102	1	(	(	PUNCT
alkej-30	102	2	s	s	VERB
alkej-30	102	3	kh	kh	X
alkej-30	102	4	=	=	PUNCT
alkej-30	102	5	weight	weight	NOUN
alkej-30	102	6	sum	sum	NOUN
alkej-30	102	7	of	of	ADP
alkej-30	102	8	the	the	DET
alkej-30	102	9	k	k	PROPN
alkej-30	102	10	th	th	X
alkej-30	102	11	neuron	neuron	NOUN
alkej-30	102	12	in	in	ADP
alkej-30	102	13	the	the	DET
alkej-30	102	14	sth	sth	NOUN
alkej-30	102	15	layer	layer	NOUN
alkej-30	102	16	.	.	PUNCT
alkej-30	102	17	)	)	PUNCT
alkej-30	103	1	(	(	PUNCT
alkej-30	103	2	s	s	NOUN
alkej-30	103	3	kjw	kjw	NOUN
alkej-30	103	4	=	=	SYM
alkej-30	103	5	synaptic	synaptic	ADJ
alkej-30	103	6	weight	weight	NOUN
alkej-30	103	7	which	which	PRON
alkej-30	103	8	corresponds	correspond	VERB
alkej-30	103	9	to	to	ADP
alkej-30	103	10	the	the	DET
alkej-30	103	11	connection	connection	NOUN
alkej-30	103	12	from	from	ADP
alkej-30	103	13	neuron	neuron	PROPN
alkej-30	103	14	unit	unit	PROPN
alkej-30	103	15	j	j	PROPN
alkej-30	103	16	in	in	ADP
alkej-30	103	17	the	the	DET
alkej-30	103	18	(	(	PUNCT
alkej-30	103	19	s-1	s-1	PROPN
alkej-30	103	20	)	)	PUNCT
alkej-30	103	21	th	th	NOUN
alkej-30	103	22	layer	layer	NOUN
alkej-30	103	23	to	to	PART
alkej-30	103	24	neuron	neuron	VERB
alkej-30	103	25	unit	unit	NOUN
alkej-30	104	1	k	k	PROPN
alkej-30	104	2	in	in	ADP
alkej-30	104	3	the	the	DET
alkej-30	104	4	s	s	X
alkej-30	104	5	th	th	NOUN
alkej-30	104	6	layer	layer	NOUN
alkej-30	104	7	of	of	ADP
alkej-30	104	8	the	the	DET
alkej-30	104	9	neural	neural	ADJ
alkej-30	104	10	network	network	NOUN
alkej-30	104	11	)	)	PUNCT
alkej-30	104	12	1	1	NUM
alkej-30	104	13	(	(	PUNCT
alkej-30	104	14	s	s	X
alkej-30	104	15	jo	jo	NOUN
alkej-30	104	16	output	output	NOUN
alkej-30	104	17	of	of	ADP
alkej-30	104	18	the	the	DET
alkej-30	104	19	jth	jth	PROPN
alkej-30	104	20	neuron	neuron	PROPN
alkej-30	104	21	in	in	ADP
alkej-30	104	22	the	the	DET
alkej-30	104	23	(	(	PUNCT
alkej-30	104	24	s-1	s-1	PROPN
alkej-30	104	25	)	)	PUNCT
alkej-30	104	26	th	th	NOUN
alkej-30	104	27	layer	layer	NOUN
alkej-30	104	28	.	.	PUNCT
alkej-30	105	1	on	on	ADP
alkej-30	105	2	the	the	DET
alkej-30	105	3	other	other	ADJ
alkej-30	105	4	hand	hand	NOUN
alkej-30	105	5	,	,	PUNCT
alkej-30	105	6	the	the	DET
alkej-30	105	7	output	output	NOUN
alkej-30	105	8	computation	computation	NOUN
alkej-30	105	9	of	of	ADP
alkej-30	105	10	neurons	neuron	NOUN
alkej-30	105	11	in	in	ADP
alkej-30	105	12	any	any	DET
alkej-30	105	13	layer	layer	NOUN
alkej-30	105	14	is	be	AUX
alkej-30	105	15	as	as	SCONJ
alkej-30	105	16	follows	follow	VERB
alkej-30	105	17	:	:	PUNCT
alkej-30	105	18	)	)	PUNCT
alkej-30	106	1	f	f	X
alkej-30	106	2	(	(	PUNCT
alkej-30	106	3	ho	ho	X
alkej-30	106	4	(	(	PUNCT
alkej-30	106	5	s	s	NOUN
alkej-30	106	6	)	)	PUNCT
alkej-30	106	7	k	k	PROPN
alkej-30	106	8	(	(	PUNCT
alkej-30	106	9	s	s	X
alkej-30	106	10	)	)	PUNCT
alkej-30	107	1	k	k	NOUN
alkej-30	107	2			NUM
alkej-30	107	3	(	(	PUNCT
alkej-30	107	4	4	4	NUM
alkej-30	107	5	)	)	PUNCT
alkej-30	107	6	where	where	SCONJ
alkej-30	107	7	k	k	PROPN
alkej-30	107	8	=	=	NOUN
alkej-30	107	9	1,	1,	NUM
alkej-30	107	10	…	…	PUNCT
alkej-30	107	11	,n	,n	PUNCT
alkej-30	107	12	and	and	CCONJ
alkej-30	107	13	s=	s=	VERB
alkej-30	107	14	1,	1,	NUM
alkej-30	107	15	…	…	SYM
alkej-30	107	16	,m	,m	PUNCT
alkej-30	107	17	o	o	NOUN
alkej-30	107	18	s	s	X
alkej-30	107	19	k	k	NOUN
alkej-30	107	20	)	)	PUNCT
alkej-30	107	21	(	(	PUNCT
alkej-30	107	22	=	=	PUNCT
alkej-30	107	23	neuron	neuron	NOUN
alkej-30	107	24	output	output	NOUN
alkej-30	107	25	of	of	ADP
alkej-30	107	26	the	the	DET
alkej-30	107	27	kth	kth	PROPN
alkej-30	107	28	neuron	neuron	PROPN
alkej-30	107	29	in	in	ADP
alkej-30	107	30	the	the	DET
alkej-30	107	31	sth	sth	NOUN
alkej-30	107	32	layer	layer	NOUN
alkej-30	107	33	.	.	PUNCT
alkej-30	107	34	)	)	PUNCT
alkej-30	108	1	f	f	PROPN
alkej-30	108	2	(	(	PUNCT
alkej-30	108	3	h	h	NOUN
alkej-30	108	4	(	(	PUNCT
alkej-30	108	5	s	s	NOUN
alkej-30	108	6	)	)	PUNCT
alkej-30	108	7	k	k	NOUN
alkej-30	109	1	=	=	PUNCT
alkej-30	109	2	activation	activation	NOUN
alkej-30	109	3	function	function	NOUN
alkej-30	109	4	computed	compute	VERB
alkej-30	109	5	on	on	ADP
alkej-30	109	6	the	the	DET
alkej-30	109	7	weighted	weight	VERB
alkej-30	109	8	sum	sum	NOUN
alkej-30	109	9	h	h	NOUN
alkej-30	109	10	(	(	PUNCT
alkej-30	109	11	s	s	X
alkej-30	109	12	)	)	PUNCT
alkej-30	109	13	k	k	PROPN
alkej-30	109	14	.	.	PUNCT
alkej-30	110	1	ammar	ammar	PROPN
alkej-30	110	2	a.	a.	PROPN
alkej-30	110	3	hassan	hassan	PROPN
alkej-30	110	4	/al	/al	PROPN
alkej-30	110	5	-	-	PUNCT
alkej-30	110	6	khwarizmi	khwarizmi	PROPN
alkej-30	110	7	engineering	engineering	NOUN
alkej-30	110	8	journal	journal	PROPN
alkej-30	110	9	,	,	PUNCT
alkej-30	110	10	vol.2	vol.2	PROPN
alkej-30	110	11	,	,	PUNCT
alkej-30	110	12	no	no	INTJ
alkej-30	110	13	.	.	NOUN
alkej-30	110	14	2	2	NUM
alkej-30	110	15	pp	pp	ADP
alkej-30	110	16	32	32	NUM
alkej-30	110	17	-	-	SYM
alkej-30	110	18	41	41	NUM
alkej-30	110	19	(	(	PUNCT
alkej-30	110	20	2006	2006	NUM
alkej-30	110	21	)	)	PUNCT
alkej-30	110	22	23	23	NUM
alkej-30	110	23	note	note	VERB
alkej-30	110	24	that	that	SCONJ
alkej-30	110	25	some	some	DET
alkej-30	110	26	sort	sort	NOUN
alkej-30	110	27	of	of	ADP
alkej-30	110	28	sigmoid	sigmoid	NOUN
alkej-30	110	29	function	function	NOUN
alkej-30	110	30	is	be	AUX
alkej-30	110	31	often	often	ADV
alkej-30	110	32	used	use	VERB
alkej-30	110	33	as	as	ADP
alkej-30	110	34	the	the	DET
alkej-30	110	35	nonlinear	nonlinear	ADJ
alkej-30	110	36	activation	activation	NOUN
alkej-30	110	37	function	function	NOUN
alkej-30	110	38	,	,	PUNCT
alkej-30	110	39	such	such	ADJ
alkej-30	110	40	as	as	ADP
alkej-30	110	41	the	the	DET
alkej-30	110	42	following	follow	VERB
alkej-30	110	43	logsig	logsig	PRON
alkej-30	110	44	function	function	NOUN
alkej-30	110	45	as	as	ADP
alkej-30	110	46	in	in	ADP
alkej-30	110	47	equation	equation	NOUN
alkej-30	110	48	(	(	PUNCT
alkej-30	110	49	5	5	NUM
alkej-30	110	50	)	)	PUNCT
alkej-30	110	51	or	or	CCONJ
alkej-30	110	52	bipoler	bipoler	NOUN
alkej-30	110	53	as	as	ADP
alkej-30	110	54	in	in	ADP
alkej-30	110	55	equation	equation	NOUN
alkej-30	110	56	(	(	PUNCT
alkej-30	110	57	6	6	NUM
alkej-30	110	58	)	)	PUNCT
alkej-30	110	59	as	as	SCONJ
alkej-30	110	60	follows	follow	VERB
alkej-30	110	61	:	:	PUNCT
alkej-30	110	62	(	(	PUNCT
alkej-30	110	63	-x	-x	X
alkej-30	110	64	)	)	PUNCT
alkej-30	110	65	sig	sig	NOUN
alkej-30	110	66	f(x	f(x	PROPN
alkej-30	110	67	)	)	PUNCT
alkej-30	110	68	exp1	exp1	NOUN
alkej-30	110	69	1	1	NUM
alkej-30	110	70	log	log	NOUN
alkej-30	110	71			ADV
alkej-30	110	72			PROPN
alkej-30	110	73	(	(	PUNCT
alkej-30	110	74	5	5	NUM
alkej-30	110	75	)	)	PUNCT
alkej-30	110	76			NOUN
alkej-30	110	77			NUM
alkej-30	110	78			ADP
alkej-30	110	79			PROPN
alkej-30	110	80			NUM
alkej-30	111	1			NOUN
alkej-30	112	1	01	01	NUM
alkej-30	112	2	01	01	NUM
alkej-30	113	1	or	or	CCONJ
alkej-30	113	2	x	x	SYM
alkej-30	113	3	f	f	PROPN
alkej-30	113	4	for	for	ADP
alkej-30	113	5	x	x	PROPN
alkej-30	113	6	bipoler	bipoler	PROPN
alkej-30	113	7	f(x	f(x	PROPN
alkej-30	113	8	)	)	PUNCT
alkej-30	113	9	(	(	PUNCT
alkej-30	113	10	6	6	NUM
alkej-30	113	11	)	)	PUNCT
alkej-30	113	12	(	(	PUNCT
alkej-30	113	13	2a	2a	NUM
alkej-30	113	14	)	)	PUNCT
alkej-30	113	15	increment	increment	VERB
alkej-30	113	16	counter	counter	NOUN
alkej-30	113	17	for	for	ADP
alkej-30	113	18	cycle	cycle	NOUN
alkej-30	113	19	counter	counter	NOUN
alkej-30	113	20	=	=	X
alkej-30	113	21	counter	counter	X
alkej-30	113	22	+1	+1	PROPN
alkej-30	113	23	.	.	PUNCT
alkej-30	114	1	5.3.backward	5.3.backward	NUM
alkej-30	114	2	computation	computation	NOUN
alkej-30	114	3	in	in	ADP
alkej-30	114	4	this	this	DET
alkej-30	114	5	step	step	NOUN
alkej-30	114	6	,	,	PUNCT
alkej-30	114	7	the	the	DET
alkej-30	114	8	weights	weight	NOUN
alkej-30	114	9	of	of	ADP
alkej-30	114	10	the	the	DET
alkej-30	114	11	networks	network	NOUN
alkej-30	114	12	are	be	AUX
alkej-30	114	13	updated	update	VERB
alkej-30	114	14	.	.	PUNCT
alkej-30	115	1	criterion	criterion	NOUN
alkej-30	115	2	for	for	ADP
alkej-30	115	3	the	the	DET
alkej-30	115	4	learning	learning	NOUN
alkej-30	115	5	algorithm	algorithm	NOUN
alkej-30	115	6	is	be	AUX
alkej-30	115	7	to	to	PART
alkej-30	115	8	minimize	minimize	VERB
alkej-30	115	9	the	the	DET
alkej-30	115	10	error	error	NOUN
alkej-30	115	11	between	between	ADP
alkej-30	115	12	the	the	DET
alkej-30	115	13	expected	expect	VERB
alkej-30	115	14	(	(	PUNCT
alkej-30	115	15	or	or	CCONJ
alkej-30	115	16	teacher	teacher	NOUN
alkej-30	115	17	)	)	PUNCT
alkej-30	115	18	value	value	NOUN
alkej-30	115	19	and	and	CCONJ
alkej-30	115	20	the	the	DET
alkej-30	115	21	actual	actual	ADJ
alkej-30	115	22	output	output	NOUN
alkej-30	115	23	value	value	NOUN
alkej-30	115	24	that	that	PRON
alkej-30	115	25	was	be	AUX
alkej-30	115	26	determined	determine	VERB
alkej-30	115	27	in	in	ADP
alkej-30	115	28	the	the	DET
alkej-30	115	29	forward	forward	ADJ
alkej-30	115	30	computation	computation	NOUN
alkej-30	115	31	.	.	PUNCT
alkej-30	116	1	the	the	DET
alkej-30	116	2	following	follow	VERB
alkej-30	116	3	steps	step	NOUN
alkej-30	116	4	are	be	AUX
alkej-30	116	5	performed	perform	VERB
alkej-30	116	6	:	:	PUNCT
alkej-30	116	7	istarting	istarte	VERB
alkej-30	116	8	with	with	ADP
alkej-30	116	9	the	the	DET
alkej-30	116	10	output	output	NOUN
alkej-30	116	11	layer	layer	NOUN
alkej-30	116	12	,	,	PUNCT
alkej-30	116	13	and	and	CCONJ
alkej-30	116	14	moving	move	VERB
alkej-30	116	15	back	back	ADV
alkej-30	116	16	towards	towards	ADP
alkej-30	116	17	the	the	DET
alkej-30	116	18	input	input	NOUN
alkej-30	116	19	layer	layer	NOUN
alkej-30	116	20	,	,	PUNCT
alkej-30	116	21	calculate	calculate	VERB
alkej-30	116	22	the	the	DET
alkej-30	116	23	local	local	ADJ
alkej-30	116	24	gradients	gradient	NOUN
alkej-30	116	25	,	,	PUNCT
alkej-30	116	26	as	as	SCONJ
alkej-30	116	27	follows	follow	VERB
alkej-30	116	28	:	:	PUNCT
alkej-30	116	29			NUM
alkej-30	116	30			PROPN
alkej-30	116	31			NUM
alkej-30	116	32			NUM
alkej-30	116	33			ADP
alkej-30	117	1			PRON
alkej-30	118	1			PRON
alkej-30	118	2			PRON
alkej-30	118	3			X
alkej-30	118	4			VERB
alkej-30	118	5			PROPN
alkej-30	118	6			PROPN
alkej-30	118	7	)	)	PUNCT
alkej-30	118	8	1	1	NUM
alkej-30	118	9	(	(	PUNCT
alkej-30	118	10	1	1	NUM
alkej-30	118	11	11	11	NUM
alkej-30	118	12	11	11	NUM
alkej-30	118	13	sn	sn	PROPN
alkej-30	118	14	j	j	PROPN
alkej-30	118	15	)	)	PUNCT
alkej-30	118	16	(	(	PUNCT
alkej-30	118	17	s	s	VERB
alkej-30	118	18	j	j	PROPN
alkej-30	118	19	s	s	X
alkej-30	118	20	kj	kj	PROPN
alkej-30	118	21	(	(	PUNCT
alkej-30	118	22	s	s	PROPN
alkej-30	118	23	)	)	PUNCT
alkej-30	118	24	kk	kk	PROPN
alkej-30	118	25	(	(	PUNCT
alkej-30	118	26	s	s	NOUN
alkej-30	118	27	)	)	PUNCT
alkej-30	118	28	k	k	NOUN
alkej-30	118	29	,	,	PUNCT
alkej-30	118	30	...	...	PUNCT
alkej-30	118	31	,	,	PUNCT
alkej-30	119	1	m	m	PROPN
alkej-30	119	2	s	s	PART
alkej-30	119	3	ms	ms	PROPN
alkej-30	119	4	δw	δw	PROPN
alkej-30	119	5	ot	ot	PROPN
alkej-30	119	6	ε	ε	PROPN
alkej-30	119	7	(	(	PUNCT
alkej-30	119	8	7	7	NUM
alkej-30	119	9	)	)	PUNCT
alkej-30	119	10	tk	tk	NOUN
alkej-30	119	11	=	=	NOUN
alkej-30	119	12	the	the	DET
alkej-30	119	13	target	target	NOUN
alkej-30	119	14	output	output	NOUN
alkej-30	119	15	for	for	ADP
alkej-30	119	16	kth	kth	PROPN
alkej-30	119	17	neuron	neuron	PROPN
alkej-30	119	18	in	in	ADP
alkej-30	119	19	the	the	DET
alkej-30	119	20	m	m	NOUN
alkej-30	119	21	layer	layer	NOUN
alkej-30	119	22	.	.	PUNCT
alkej-30	120	1	)	)	PUNCT
alkej-30	121	1	1	1	NUM
alkej-30	121	2	(	(	PUNCT
alkej-30	121	3	sn	sn	NOUN
alkej-30	121	4	=	=	PUNCT
alkej-30	121	5	number	number	NOUN
alkej-30	121	6	of	of	ADP
alkej-30	121	7	neurons	neuron	NOUN
alkej-30	121	8	in	in	ADP
alkej-30	121	9	the	the	DET
alkej-30	121	10	(	(	PUNCT
alkej-30	121	11	s+1)th	s+1)th	PROPN
alkej-30	121	12	layer	layer	NOUN
alkej-30	121	13	of	of	ADP
alkej-30	121	14	the	the	DET
alkej-30	121	15	ann	ann	PROPN
alkej-30	121	16	.	.	PUNCT
alkej-30	121	17	where	where	SCONJ
alkej-30	121	18			PROPN
alkej-30	121	19	)	)	PUNCT
alkej-30	121	20	(	(	PUNCT
alkej-30	121	21	s	s	X
alkej-30	121	22	k	k	NOUN
alkej-30	121	23	=	=	PUNCT
alkej-30	121	24	error	error	NOUN
alkej-30	121	25	term	term	NOUN
alkej-30	121	26	for	for	ADP
alkej-30	121	27	the	the	DET
alkej-30	121	28	kth	kth	PROPN
alkej-30	121	29	neurons	neuron	NOUN
alkej-30	121	30	in	in	ADP
alkej-30	121	31	the	the	DET
alkej-30	121	32	sth	sth	NOUN
alkej-30	121	33	layer	layer	NOUN
alkej-30	121	34	.	.	PUNCT
alkej-30	122	1	the	the	DET
alkej-30	122	2	difference	difference	NOUN
alkej-30	122	3	between	between	ADP
alkej-30	122	4	the	the	DET
alkej-30	122	5	teaching	teaching	NOUN
alkej-30	122	6	signal	signal	NOUN
alkej-30	122	7	b	b	PROPN
alkej-30	122	8	_	_	PRON
alkej-30	122	9	and	and	CCONJ
alkej-30	122	10	the	the	DET
alkej-30	122	11	neuron	neuron	NOUN
alkej-30	122	12	output	output	NOUN
alkej-30	122	13	)	)	PUNCT
alkej-30	122	14	(	(	PUNCT
alkej-30	122	15	s	s	VERB
alkej-30	122	16	ko	ko	PROPN
alkej-30	122	17	)	)	PUNCT
alkej-30	122	18	1	1	NUM
alkej-30	122	19	(	(	PUNCT
alkej-30	122	20	s	s	ADJ
alkej-30	122	21	j	j	NOUN
alkej-30	122	22	=	=	PUNCT
alkej-30	122	23	local	local	ADJ
alkej-30	122	24	gradient	gradient	NOUN
alkej-30	122	25	for	for	ADP
alkej-30	122	26	the	the	DET
alkej-30	122	27	j	j	PROPN
alkej-30	122	28	th	th	X
alkej-30	122	29	neuron	neuron	NOUN
alkej-30	122	30	in	in	ADP
alkej-30	122	31	the	the	DET
alkej-30	122	32	(	(	PUNCT
alkej-30	122	33	s+1)th	s+1)th	PROPN
alkej-30	122	34	layer	layer	NOUN
alkej-30	122	35	.	.	PUNCT
alkej-30	123	1	,	,	PUNCT
alkej-30	123	2	....	....	PUNCT
alkej-30	123	3	,	,	PUNCT
alkej-30	123	4	m	m	PROPN
alkej-30	123	5	s	s	PART
alkej-30	123	6	)	)	PUNCT
alkej-30	123	7	(	(	PUNCT
alkej-30	123	8	hfεδ	hfεδ	NOUN
alkej-30	123	9	(	(	PUNCT
alkej-30	123	10	s	s	NOUN
alkej-30	123	11	)	)	PUNCT
alkej-30	123	12	k	k	NOUN
alkej-30	123	13	\(s	\(s	PROPN
alkej-30	123	14	)	)	PUNCT
alkej-30	123	15	k	k	PROPN
alkej-30	123	16	(	(	PUNCT
alkej-30	123	17	s	s	X
alkej-30	123	18	)	)	PUNCT
alkej-30	123	19	k	k	NOUN
alkej-30	123	20	1	1	NUM
alkej-30	123	21	(	(	PUNCT
alkej-30	123	22	8)	8)	NUM
alkej-30	123	23	iiusing	iiuse	VERB
alkej-30	123	24	the	the	DET
alkej-30	123	25	local	local	ADJ
alkej-30	123	26	gradients	gradient	NOUN
alkej-30	123	27	calculated	calculate	VERB
alkej-30	123	28	in	in	ADP
alkej-30	123	29	step	step	NOUN
alkej-30	123	30	1	1	NUM
alkej-30	123	31	,	,	PUNCT
alkej-30	123	32	calculate	calculate	VERB
alkej-30	123	33	the	the	DET
alkej-30	123	34	weight	weight	NOUN
alkej-30	123	35	(	(	PUNCT
alkej-30	123	36	and	and	CCONJ
alkej-30	123	37	bias	bias	NOUN
alkej-30	123	38	)	)	PUNCT
alkej-30	123	39	changes	change	NOUN
alkej-30	123	40	for	for	ADP
alkej-30	123	41	all	all	DET
alkej-30	123	42	the	the	DET
alkej-30	123	43	weights	weight	NOUN
alkej-30	123	44	as	as	SCONJ
alkej-30	123	45	follows	follow	VERB
alkej-30	123	46	:	:	PUNCT
alkej-30	123	47	noδw	noδw	ADJ
alkej-30	123	48	s)(s	s)(	VERB
alkej-30	123	49	j	j	PROPN
alkej-30	123	50	(	(	PUNCT
alkej-30	123	51	s	s	PROPN
alkej-30	123	52	)	)	PUNCT
alkej-30	123	53	k	k	PROPN
alkej-30	123	54	(	(	PUNCT
alkej-30	123	55	s	s	NOUN
alkej-30	123	56	)	)	PUNCT
alkej-30	123	57	kj	kj	NOUN
alkej-30	123	58	,	,	PUNCT
alkej-30	123	59	...	...	PUNCT
alkej-30	123	60	,	,	PUNCT
alkej-30	123	61	and	and	CCONJ
alkej-30	123	62	j,	j,	PROPN
alkej-30	123	63	....	....	PUNCT
alkej-30	123	64	,ns	,ns	PUNCT
alkej-30	123	65	k	k	PROPN
alkej-30	123	66	η	η	PROPN
alkej-30	123	67	δ	δ	PROPN
alkej-30	123	68	1	1	NUM
alkej-30	123	69	1	1	NUM
alkej-30	123	70	11	11	NUM
alkej-30	123	71			VERB
alkej-30	123	72			NOUN
alkej-30	123	73	(	(	PUNCT
alkej-30	123	74	9	9	NUM
alkej-30	123	75	)	)	PUNCT
alkej-30	123	76	where	where	SCONJ
alkej-30	123	77	w	w	PROPN
alkej-30	123	78	(	(	PUNCT
alkej-30	123	79	s	s	NOUN
alkej-30	123	80	)	)	PUNCT
alkej-30	123	81	kj	kj	PROPN
alkej-30	123	82	δ	δ	PROPN
alkej-30	123	83	is	be	AUX
alkej-30	123	84	the	the	DET
alkej-30	123	85	change	change	NOUN
alkej-30	123	86	in	in	ADP
alkej-30	123	87	synaptic	synaptic	ADJ
alkej-30	123	88	weight	weight	NOUN
alkej-30	123	89	(	(	PUNCT
alkej-30	123	90	or	or	CCONJ
alkej-30	123	91	bias	bias	NOUN
alkej-30	123	92	)	)	PUNCT
alkej-30	123	93	corresponding	correspond	VERB
alkej-30	123	94	to	to	ADP
alkej-30	123	95	the	the	DET
alkej-30	123	96	gradient	gradient	NOUN
alkej-30	123	97	of	of	ADP
alkej-30	123	98	error	error	NOUN
alkej-30	123	99	for	for	ADP
alkej-30	123	100	connection	connection	NOUN
alkej-30	123	101	from	from	ADP
alkej-30	123	102	neuron	neuron	PROPN
alkej-30	123	103	unit	unit	PROPN
alkej-30	123	104	j	j	PROPN
alkej-30	123	105	in	in	ADP
alkej-30	123	106	the	the	DET
alkej-30	123	107	(	(	PUNCT
alkej-30	123	108	s+1	s+1	NOUN
alkej-30	123	109	)	)	PUNCT
alkej-30	123	110	th	th	NOUN
alkej-30	123	111	layer	layer	NOUN
alkej-30	123	112	,	,	PUNCT
alkej-30	123	113	to	to	PART
alkej-30	123	114	neuron	neuron	VERB
alkej-30	123	115	k	k	PROPN
alkej-30	123	116	in	in	ADP
alkej-30	123	117	the	the	DET
alkej-30	123	118	s	s	X
alkej-30	123	119	th	th	NOUN
alkej-30	123	120	layer	layer	NOUN
alkej-30	123	121	.	.	PUNCT
alkej-30	124	1	iiionce	iiionce	NOUN
alkej-30	124	2	all	all	DET
alkej-30	124	3	weight	weight	NOUN
alkej-30	124	4	(	(	PUNCT
alkej-30	124	5	and	and	CCONJ
alkej-30	124	6	bias	bias	NOUN
alkej-30	124	7	)	)	PUNCT
alkej-30	124	8	changes	change	NOUN
alkej-30	124	9	have	have	AUX
alkej-30	124	10	been	be	AUX
alkej-30	124	11	calculated	calculate	VERB
alkej-30	124	12	in	in	ADP
alkej-30	124	13	step	step	NOUN
alkej-30	124	14	2	2	NUM
alkej-30	124	15	,	,	PUNCT
alkej-30	124	16	update	update	VERB
alkej-30	124	17	all	all	DET
alkej-30	124	18	the	the	DET
alkej-30	124	19	weights	weight	NOUN
alkej-30	124	20	(	(	PUNCT
alkej-30	124	21	and	and	CCONJ
alkej-30	124	22	biases	bias	NOUN
alkej-30	124	23	)	)	PUNCT
alkej-30	124	24	as	as	SCONJ
alkej-30	124	25	follows	follow	VERB
alkej-30	124	26	:	:	PUNCT
alkej-30	124	27	(	(	PUNCT
alkej-30	124	28	n	n	CCONJ
alkej-30	124	29	)	)	PUNCT
alkej-30	124	30	(	(	PUNCT
alkej-30	124	31	n	n	CCONJ
alkej-30	124	32	)	)	PUNCT
alkej-30	124	33	δ	δ	PROPN
alkej-30	124	34	)	)	PUNCT
alkej-30	124	35	(	(	PUNCT
alkej-30	124	36	n	n	CCONJ
alkej-30	124	37	www	www	NOUN
alkej-30	124	38	s	s	PROPN
alkej-30	124	39	kj	kj	PROPN
alkej-30	124	40	s	s	PROPN
alkej-30	124	41	kj	kj	PROPN
alkej-30	124	42	s	s	PROPN
alkej-30	124	43	kj	kj	PROPN
alkej-30	124	44	1	1	PROPN
alkej-30	124	45	(	(	PUNCT
alkej-30	124	46	10	10	NUM
alkej-30	124	47	)	)	PUNCT
alkej-30	124	48	where	where	SCONJ
alkej-30	124	49	k	k	NOUN
alkej-30	124	50	=	=	SYM
alkej-30	124	51	1	1	NUM
alkej-30	124	52	,	,	PUNCT
alkej-30	124	53	…	…	PUNCT
alkej-30	124	54	..	..	PUNCT
alkej-30	124	55	,	,	PUNCT
alkej-30	124	56	n	n	CCONJ
alkej-30	124	57	neurons	neuron	NOUN
alkej-30	124	58	in	in	ADP
alkej-30	124	59	the	the	DET
alkej-30	124	60	s	s	X
alkej-30	124	61	th	th	NOUN
alkej-30	124	62	layer	layer	NOUN
alkej-30	124	63	and	and	CCONJ
alkej-30	124	64	j	j	NOUN
alkej-30	124	65	=	=	SYM
alkej-30	124	66	1	1	NUM
alkej-30	124	67	,	,	PUNCT
alkej-30	124	68	…	…	PUNCT
alkej-30	124	69	……	……	NOUN
alkej-30	124	70	,	,	PUNCT
alkej-30	124	71	n	n	PRON
alkej-30	124	72	neurons	neuron	NOUN
alkej-30	124	73	in	in	ADP
alkej-30	124	74	the	the	PRON
alkej-30	124	75	(	(	PUNCT
alkej-30	124	76	s-1	s-1	PROPN
alkej-30	124	77	)	)	PUNCT
alkej-30	124	78	th	th	NOUN
alkej-30	124	79	layer	layer	NOUN
alkej-30	124	80	.	.	PUNCT
alkej-30	125	1	)	)	PUNCT
alkej-30	125	2	1	1	NUM
alkej-30	125	3	(	(	PUNCT
alkej-30	125	4	)	)	PUNCT
alkej-30	125	5	(	(	PUNCT
alkej-30	125	6	nw	nw	PROPN
alkej-30	125	7	s	s	PART
alkej-30	125	8	kj	kj	NOUN
alkej-30	125	9	=	=	PUNCT
alkej-30	125	10	update	update	NOUN
alkej-30	125	11	synaptic	synaptic	ADJ
alkej-30	125	12	weight	weight	NOUN
alkej-30	125	13	(	(	PUNCT
alkej-30	125	14	or	or	CCONJ
alkej-30	125	15	bias	bias	NOUN
alkej-30	125	16	)	)	PUNCT
alkej-30	125	17	to	to	PART
alkej-30	125	18	be	be	AUX
alkej-30	125	19	used	use	VERB
alkej-30	125	20	in	in	ADP
alkej-30	125	21	the	the	DET
alkej-30	125	22	(	(	PUNCT
alkej-30	125	23	n+1	n+1	NOUN
alkej-30	125	24	)	)	PUNCT
alkej-30	125	25	th	th	X
alkej-30	125	26	iteration	iteration	NOUN
alkej-30	125	27	of	of	ADP
alkej-30	125	28	the	the	DET
alkej-30	125	29	forward	forward	ADJ
alkej-30	125	30	computation	computation	NOUN
alkej-30	125	31	.	.	PUNCT
alkej-30	125	32	)	)	PUNCT
alkej-30	126	1	(	(	PUNCT
alkej-30	126	2	)	)	PUNCT
alkej-30	126	3	(	(	PUNCT
alkej-30	126	4	nw	nw	PROPN
alkej-30	126	5	s	s	PROPN
alkej-30	126	6	kj	kj	NOUN
alkej-30	126	7	=	=	SYM
alkej-30	126	8	change	change	NOUN
alkej-30	126	9	in	in	ADP
alkej-30	126	10	synaptic	synaptic	ADJ
alkej-30	126	11	weight	weight	NOUN
alkej-30	126	12	(	(	PUNCT
alkej-30	126	13	or	or	CCONJ
alkej-30	126	14	bias	bias	NOUN
alkej-30	126	15	)	)	PUNCT
alkej-30	126	16	calculated	calculate	VERB
alkej-30	126	17	in	in	ADP
alkej-30	126	18	the	the	DET
alkej-30	126	19	n	n	ADV
alkej-30	126	20	th	th	X
alkej-30	126	21	iteration	iteration	NOUN
alkej-30	126	22	of	of	ADP
alkej-30	126	23	the	the	DET
alkej-30	126	24	backward	backward	ADJ
alkej-30	126	25	computation	computation	NOUN
alkej-30	126	26	,	,	PUNCT
alkej-30	126	27	where	where	SCONJ
alkej-30	126	28	n	n	PRON
alkej-30	126	29	=	=	NOUN
alkej-30	126	30	the	the	DET
alkej-30	126	31	current	current	ADJ
alkej-30	126	32	iteration	iteration	NOUN
alkej-30	126	33	.	.	PUNCT
alkej-30	127	1	ammar	ammar	PROPN
alkej-30	127	2	a.	a.	PROPN
alkej-30	127	3	hassan	hassan	PROPN
alkej-30	127	4	/al	/al	PROPN
alkej-30	127	5	-	-	PUNCT
alkej-30	127	6	khwarizmi	khwarizmi	PROPN
alkej-30	127	7	engineering	engineering	NOUN
alkej-30	127	8	journal	journal	PROPN
alkej-30	127	9	,	,	PUNCT
alkej-30	127	10	vol.2	vol.2	PROPN
alkej-30	127	11	,	,	PUNCT
alkej-30	127	12	no	no	INTJ
alkej-30	127	13	.	.	NOUN
alkej-30	127	14	2	2	NUM
alkej-30	127	15	pp	pp	ADP
alkej-30	127	16	32	32	NUM
alkej-30	127	17	-	-	SYM
alkej-30	127	18	41	41	NUM
alkej-30	127	19	(	(	PUNCT
alkej-30	127	20	2006	2006	NUM
alkej-30	127	21	)	)	PUNCT
alkej-30	127	22	23	23	NUM
alkej-30	127	23	)	)	PUNCT
alkej-30	127	24	(	(	PUNCT
alkej-30	127	25	)	)	PUNCT
alkej-30	127	26	(	(	PUNCT
alkej-30	127	27	nw	nw	PROPN
alkej-30	127	28	s	s	PROPN
alkej-30	127	29	kj	kj	NOUN
alkej-30	127	30	=	=	SYM
alkej-30	127	31	synaptic	synaptic	ADJ
alkej-30	127	32	weight	weight	NOUN
alkej-30	127	33	(	(	PUNCT
alkej-30	127	34	or	or	CCONJ
alkej-30	127	35	bias	bias	NOUN
alkej-30	127	36	)	)	PUNCT
alkej-30	127	37	to	to	PART
alkej-30	127	38	be	be	AUX
alkej-30	127	39	used	use	VERB
alkej-30	127	40	in	in	ADP
alkej-30	127	41	the	the	DET
alkej-30	127	42	n	n	ADV
alkej-30	127	43	th	th	X
alkej-30	127	44	iteration	iteration	NOUN
alkej-30	127	45	of	of	ADP
alkej-30	127	46	the	the	DET
alkej-30	127	47	forward	forward	ADJ
alkej-30	127	48	and	and	CCONJ
alkej-30	127	49	backward	backward	ADJ
alkej-30	127	50	computations	computation	NOUN
alkej-30	127	51	,	,	PUNCT
alkej-30	127	52	where	where	SCONJ
alkej-30	127	53	n	n	ADV
alkej-30	127	54	=	=	PUNCT
alkej-30	127	55	the	the	DET
alkej-30	127	56	current	current	ADJ
alkej-30	127	57	iteration	iteration	NOUN
alkej-30	127	58	.	.	PUNCT
alkej-30	128	1	(	(	PUNCT
alkej-30	128	2	3a	3a	NUM
alkej-30	128	3	)	)	PUNCT
alkej-30	128	4	truncation	truncation	NOUN
alkej-30	128	5	for	for	ADP
alkej-30	128	6	each	each	DET
alkej-30	128	7	counter	counter	NOUN
alkej-30	128	8	>	>	X
alkej-30	128	9	q	q	PUNCT
alkej-30	128	10	makes	make	VERB
alkej-30	128	11	a	a	DET
alkej-30	128	12	truncation	truncation	NOUN
alkej-30	128	13	as	as	ADP
alkej-30	128	14	in	in	ADP
alkej-30	128	15	equation	equation	NOUN
alkej-30	128	16	(	(	PUNCT
alkej-30	128	17	11	11	NUM
alkej-30	128	18	)	)	PUNCT
alkej-30	128	19	to	to	ADP
alkej-30	128	20	the	the	DET
alkej-30	128	21	values	value	NOUN
alkej-30	128	22	of	of	ADP
alkej-30	128	23	the	the	DET
alkej-30	128	24	weights	weight	NOUN
alkej-30	128	25	)	)	PUNCT
alkej-30	128	26	(	(	PUNCT
alkej-30	128	27	)	)	PUNCT
alkej-30	128	28	(	(	PUNCT
alkej-30	128	29	nw	nw	PROPN
alkej-30	128	30	s	s	X
alkej-30	128	31	kj	kj	PROPN
alkej-30	128	32	.	.	PUNCT
alkej-30	128	33	)	)	PUNCT
alkej-30	129	1	-	-	PUNCT
alkej-30	129	2	)	)	PUNCT
alkej-30	129	3	*	*	PUNCT
alkej-30	129	4	(	(	PUNCT
alkej-30	129	5	/	/	SYM
alkej-30	129	6	(	(	PUNCT
alkej-30	129	7	n	n	CCONJ
alkej-30	129	8	)	)	PUNCT
alkej-30	129	9	int	int	NOUN
alkej-30	129	10	(	(	PUNCT
alkej-30	129	11	w(n)w	w(n)w	NOUN
alkej-30	129	12	nn(s	nn(s	NUM
alkej-30	129	13	)	)	PUNCT
alkej-30	129	14	kj	kj	NOUN
alkej-30	129	15	(	(	PUNCT
alkej-30	129	16	s	s	PROPN
alkej-30	129	17	)	)	PUNCT
alkej-30	129	18	kj	kj	PROPN
alkej-30	129	19	122	122	NUM
alkej-30	129	20	(	(	PUNCT
alkej-30	129	21	11	11	NUM
alkej-30	129	22	)	)	PUNCT
alkej-30	129	23	where	where	SCONJ
alkej-30	129	24	q	q	NOUN
alkej-30	129	25	is	be	AUX
alkej-30	129	26	a	a	DET
alkej-30	129	27	small	small	ADJ
alkej-30	129	28	integer	integer	NOUN
alkej-30	129	29	value	value	NOUN
alkej-30	129	30	depends	depend	VERB
alkej-30	129	31	on	on	ADP
alkej-30	129	32	the	the	DET
alkej-30	129	33	ann	ann	PROPN
alkej-30	129	34	,	,	PUNCT
alkej-30	129	35	it	it	PRON
alkej-30	129	36	defaults	default	VERB
alkej-30	129	37	between	between	ADP
alkej-30	129	38	5to50	5to50	PROPN
alkej-30	129	39	.	.	PUNCT
alkej-30	130	1	n	n	CCONJ
alkej-30	130	2	:	:	PUNCT
alkej-30	130	3	number	number	NOUN
alkej-30	130	4	of	of	ADP
alkej-30	130	5	bits	bit	NOUN
alkej-30	130	6	in	in	ADP
alkej-30	130	7	data	datum	NOUN
alkej-30	130	8	bus	bus	NOUN
alkej-30	130	9	.	.	PUNCT
alkej-30	131	1	for	for	ADP
alkej-30	131	2	truncation	truncation	NOUN
alkej-30	131	3	in	in	ADP
alkej-30	131	4	the	the	DET
alkej-30	131	5	range	range	NOUN
alkej-30	131	6	of	of	ADP
alkej-30	131	7	10	10	NUM
alkej-30	131	8	-	-	PUNCT
alkej-30	131	9	bit	bit	NOUN
alkej-30	131	10	this	this	DET
alkej-30	131	11	equation	equation	NOUN
alkej-30	131	12	becomes	become	VERB
alkej-30	131	13	as	as	ADP
alkej-30	131	14	in	in	ADP
alkej-30	131	15	equation	equation	NOUN
alkej-30	131	16	(	(	PUNCT
alkej-30	131	17	12	12	NUM
alkej-30	131	18	)	)	PUNCT
alkej-30	131	19	.	.	PUNCT
alkej-30	132	1	10231024	10231024	NUM
alkej-30	132	2	)	)	PUNCT
alkej-30	133	1	*	*	PUNCT
alkej-30	133	2	/	/	PUNCT
alkej-30	133	3	(	(	PUNCT
alkej-30	133	4	n	n	CCONJ
alkej-30	133	5	)	)	PUNCT
alkej-30	133	6	int	int	NOUN
alkej-30	133	7	(	(	PUNCT
alkej-30	133	8	w(n)w	w(n)w	X
alkej-30	133	9	(	(	PUNCT
alkej-30	133	10	s	s	NOUN
alkej-30	133	11	)	)	PUNCT
alkej-30	133	12	kj	kj	NOUN
alkej-30	133	13	(	(	PUNCT
alkej-30	133	14	s	s	PROPN
alkej-30	133	15	)	)	PUNCT
alkej-30	133	16	kj	kj	PROPN
alkej-30	133	17			PROPN
alkej-30	133	18	(	(	PUNCT
alkej-30	133	19	12	12	NUM
alkej-30	133	20	)	)	PUNCT
alkej-30	133	21	6.comparative	6.comparative	NUM
alkej-30	133	22	study	study	NOUN
alkej-30	133	23	the	the	DET
alkej-30	133	24	simple	simple	ADJ
alkej-30	133	25	example	example	NOUN
alkej-30	133	26	is	be	AUX
alkej-30	133	27	the	the	DET
alkej-30	133	28	four	four	NUM
alkej-30	133	29	-	-	PUNCT
alkej-30	133	30	layer	layer	NOUN
alkej-30	133	31	network	network	NOUN
alkej-30	133	32	to	to	ADP
alkej-30	133	33	the	the	DET
alkej-30	133	34	problem	problem	NOUN
alkej-30	133	35	of	of	ADP
alkej-30	133	36	recognizing	recognize	VERB
alkej-30	133	37	english	english	ADJ
alkej-30	133	38	digit	digit	NOUN
alkej-30	133	39	numbers	number	NOUN
alkej-30	133	40	that	that	PRON
alkej-30	133	41	has	have	VERB
alkej-30	133	42	70	70	NUM
alkej-30	133	43	nodes	node	NOUN
alkej-30	133	44	.	.	PUNCT
alkej-30	134	1	the	the	DET
alkej-30	134	2	implementation	implementation	NOUN
alkej-30	134	3	of	of	ADP
alkej-30	134	4	this	this	PRON
alkej-30	134	5	nn	nn	NOUN
alkej-30	134	6	using	use	VERB
alkej-30	134	7	ise	ise	PROPN
alkej-30	134	8	4.1i	4.1i	PROPN
alkej-30	134	9	on	on	ADP
alkej-30	134	10	xilinx	xilinx	PROPN
alkej-30	134	11	platform	platform	NOUN
alkej-30	134	12	[	[	X
alkej-30	134	13	7	7	NUM
alkej-30	134	14	,	,	PUNCT
alkej-30	134	15	8	8	NUM
alkej-30	134	16	]	]	PUNCT
alkej-30	134	17	shows	show	VERB
alkej-30	134	18	the	the	DET
alkej-30	134	19	effect	effect	NOUN
alkej-30	134	20	of	of	ADP
alkej-30	134	21	the	the	DET
alkej-30	134	22	proposed	propose	VERB
alkej-30	134	23	algorithm	algorithm	NOUN
alkej-30	134	24	on	on	ADP
alkej-30	134	25	the	the	DET
alkej-30	134	26	total	total	ADJ
alkej-30	134	27	cost	cost	NOUN
alkej-30	134	28	and	and	CCONJ
alkej-30	134	29	the	the	DET
alkej-30	134	30	final	final	ADJ
alkej-30	134	31	error	error	NOUN
alkej-30	134	32	as	as	ADP
alkej-30	134	33	in	in	ADP
alkej-30	134	34	table	table	NOUN
alkej-30	134	35	(	(	PUNCT
alkej-30	134	36	2	2	NUM
alkej-30	134	37	)	)	PUNCT
alkej-30	134	38	.	.	PUNCT
alkej-30	135	1	7.conclusion	7.conclusion	NUM
alkej-30	135	2	generally	generally	ADV
alkej-30	135	3	,	,	PUNCT
alkej-30	135	4	any	any	DET
alkej-30	135	5	complete	complete	ADJ
alkej-30	135	6	circuit	circuit	NOUN
alkej-30	135	7	of	of	ADP
alkej-30	135	8	ann	ann	PROPN
alkej-30	135	9	has	have	VERB
alkej-30	135	10	a	a	DET
alkej-30	135	11	very	very	ADV
alkej-30	135	12	high	high	ADJ
alkej-30	135	13	cost	cost	NOUN
alkej-30	135	14	because	because	SCONJ
alkej-30	135	15	the	the	DET
alkej-30	135	16	high	high	ADJ
alkej-30	135	17	resolution	resolution	NOUN
alkej-30	135	18	of	of	ADP
alkej-30	135	19	the	the	DET
alkej-30	135	20	weight	weight	NOUN
alkej-30	135	21	values	value	NOUN
alkej-30	135	22	required	require	VERB
alkej-30	135	23	is	be	AUX
alkej-30	135	24	about	about	ADV
alkej-30	135	25	30	30	NUM
alkej-30	135	26	-	-	PUNCT
alkej-30	135	27	bit	bit	NOUN
alkej-30	135	28	or	or	CCONJ
alkej-30	135	29	more	more	ADJ
alkej-30	135	30	.	.	PUNCT
alkej-30	136	1	the	the	DET
alkej-30	136	2	truncation	truncation	NOUN
alkej-30	136	3	of	of	ADP
alkej-30	136	4	this	this	DET
alkej-30	136	5	data	datum	NOUN
alkej-30	136	6	to	to	ADP
alkej-30	136	7	low	low	ADJ
alkej-30	136	8	number	number	NOUN
alkej-30	136	9	such	such	ADJ
alkej-30	136	10	as	as	ADP
alkej-30	136	11	10	10	NUM
alkej-30	136	12	-	-	PUNCT
alkej-30	136	13	bit	bit	NOUN
alkej-30	136	14	will	will	AUX
alkej-30	136	15	reduce	reduce	VERB
alkej-30	136	16	the	the	DET
alkej-30	136	17	total	total	ADJ
alkej-30	136	18	cost	cost	NOUN
alkej-30	136	19	to	to	ADP
alkej-30	136	20	5	5	NUM
alkej-30	136	21	%	%	NOUN
alkej-30	136	22	from	from	ADP
alkej-30	136	23	the	the	DET
alkej-30	136	24	total	total	ADJ
alkej-30	136	25	cost	cost	NOUN
alkej-30	136	26	but	but	CCONJ
alkej-30	136	27	increase	increase	VERB
alkej-30	136	28	the	the	DET
alkej-30	136	29	error	error	NOUN
alkej-30	136	30	to	to	ADP
alkej-30	136	31	more	more	ADJ
alkej-30	136	32	than	than	ADP
alkej-30	136	33	10	10	NUM
alkej-30	136	34	times	time	NOUN
alkej-30	136	35	.	.	PUNCT
alkej-30	137	1	in	in	ADP
alkej-30	137	2	addition	addition	NOUN
alkej-30	137	3	to	to	ADP
alkej-30	137	4	this	this	PRON
alkej-30	137	5	,	,	PUNCT
alkej-30	137	6	the	the	DET
alkej-30	137	7	effect	effect	NOUN
alkej-30	137	8	of	of	ADP
alkej-30	137	9	the	the	DET
alkej-30	137	10	transfer	transfer	NOUN
alkej-30	137	11	function	function	NOUN
alkej-30	137	12	type	type	NOUN
alkej-30	137	13	such	such	ADJ
alkej-30	137	14	as	as	ADP
alkej-30	137	15	sigmoid	sigmoid	NOUN
alkej-30	137	16	or	or	CCONJ
alkej-30	137	17	bipolar	bipolar	ADJ
alkej-30	137	18	function	function	NOUN
alkej-30	137	19	declared	declare	VERB
alkej-30	137	20	the	the	DET
alkej-30	137	21	cost	cost	NOUN
alkej-30	137	22	of	of	ADP
alkej-30	137	23	the	the	DET
alkej-30	137	24	classic	classic	ADJ
alkej-30	137	25	nn	nn	NOUN
alkej-30	137	26	,	,	PUNCT
alkej-30	137	27	where	where	SCONJ
alkej-30	137	28	sigmoid	sigmoid	NOUN
alkej-30	137	29	function	function	NOUN
alkej-30	137	30	is	be	AUX
alkej-30	137	31	30	30	NUM
alkej-30	137	32	times	time	NOUN
alkej-30	137	33	over	over	ADP
alkej-30	137	34	the	the	DET
alkej-30	137	35	bipolar	bipolar	ADJ
alkej-30	137	36	transfer	transfer	NOUN
alkej-30	137	37	function	function	NOUN
alkej-30	137	38	but	but	CCONJ
alkej-30	137	39	the	the	DET
alkej-30	137	40	bipolar	bipolar	NOUN
alkej-30	137	41	has	have	VERB
alkej-30	137	42	in	in	ADP
alkej-30	137	43	average	average	ADJ
alkej-30	137	44	twice	twice	DET
alkej-30	137	45	the	the	DET
alkej-30	137	46	error	error	NOUN
alkej-30	137	47	.	.	PUNCT
alkej-30	138	1	this	this	DET
alkej-30	138	2	work	work	NOUN
alkej-30	138	3	has	have	AUX
alkej-30	138	4	shown	show	VERB
alkej-30	138	5	capability	capability	NOUN
alkej-30	138	6	choice	choice	NOUN
alkej-30	138	7	of	of	ADP
alkej-30	138	8	different	different	ADJ
alkej-30	138	9	transfer	transfer	NOUN
alkej-30	138	10	functions	function	NOUN
alkej-30	138	11	for	for	ADP
alkej-30	138	12	nn	nn	PROPN
alkej-30	138	13	algorithm	algorithm	NOUN
alkej-30	138	14	that	that	PRON
alkej-30	138	15	are	be	AUX
alkej-30	138	16	suitable	suitable	ADJ
alkej-30	138	17	to	to	PART
alkej-30	138	18	reduce	reduce	VERB
alkej-30	138	19	the	the	DET
alkej-30	138	20	hardware	hardware	NOUN
alkej-30	138	21	cost	cost	NOUN
alkej-30	138	22	with	with	ADP
alkej-30	138	23	an	an	DET
alkej-30	138	24	optimal	optimal	ADJ
alkej-30	138	25	choice	choice	NOUN
alkej-30	138	26	of	of	ADP
alkej-30	138	27	precision	precision	NOUN
alkej-30	138	28	value	value	NOUN
alkej-30	138	29	,	,	PUNCT
alkej-30	138	30	by	by	ADP
alkej-30	138	31	applying	apply	VERB
alkej-30	138	32	proposed	propose	VERB
alkej-30	138	33	truncation	truncation	NOUN
alkej-30	138	34	algorithm	algorithm	NOUN
alkej-30	138	35	to	to	ADP
alkej-30	138	36	reduced	reduce	VERB
alkej-30	138	37	precision	precision	NOUN
alkej-30	138	38	value	value	NOUN
alkej-30	138	39	from	from	ADP
alkej-30	138	40	30	30	NUM
alkej-30	138	41	-	-	PUNCT
alkej-30	138	42	bit	bit	NOUN
alkej-30	138	43	to	to	PART
alkej-30	138	44	10	10	NUM
alkej-30	138	45	-	-	PUNCT
alkej-30	138	46	bit	bit	NOUN
alkej-30	138	47	with	with	ADP
alkej-30	138	48	minimum	minimum	ADJ
alkej-30	138	49	possible	possible	ADJ
alkej-30	138	50	error	error	NOUN
alkej-30	138	51	.	.	PUNCT
alkej-30	139	1	the	the	DET
alkej-30	139	2	matching	matching	NOUN
alkej-30	139	3	of	of	ADP
alkej-30	139	4	the	the	DET
alkej-30	139	5	proposed	propose	VERB
alkej-30	139	6	algorithm	algorithm	NOUN
alkej-30	139	7	with	with	ADP
alkej-30	139	8	bipolar	bipolar	ADJ
alkej-30	139	9	transfer	transfer	NOUN
alkej-30	139	10	function	function	NOUN
alkej-30	139	11	will	will	AUX
alkej-30	139	12	reduce	reduce	VERB
alkej-30	139	13	the	the	DET
alkej-30	139	14	cost	cost	NOUN
alkej-30	139	15	to	to	ADP
alkej-30	139	16	0.3	0.3	NUM
alkej-30	139	17	%	%	NOUN
alkej-30	139	18	from	from	ADP
alkej-30	139	19	the	the	DET
alkej-30	139	20	total	total	ADJ
alkej-30	139	21	cost	cost	NOUN
alkej-30	139	22	and	and	CCONJ
alkej-30	139	23	increases	increase	VERB
alkej-30	139	24	activation	activation	NOUN
alkej-30	139	25	function	function	NOUN
alkej-30	139	26	number	number	NOUN
alkej-30	139	27	of	of	ADP
alkej-30	139	28	bits	bit	NOUN
alkej-30	139	29	algorithm	algorithm	NOUN
alkej-30	139	30	final	final	ADJ
alkej-30	139	31	error	error	NOUN
alkej-30	139	32	%	%	NOUN
alkej-30	139	33	total	total	ADJ
alkej-30	139	34	nn	nn	INTJ
alkej-30	139	35	cost	cost	NOUN
alkej-30	139	36	/	/	SYM
alkej-30	139	37	cell	cell	NOUN
alkej-30	139	38	max	max	NOUN
alkej-30	139	39	speed	speed	NOUN
alkej-30	139	40	of	of	ADP
alkej-30	139	41	nn	nn	PROPN
alkej-30	139	42	/	/	SYM
alkej-30	139	43	mhz	mhz	NOUN
alkej-30	139	44	sigmoid	sigmoid	NOUN
alkej-30	139	45	30	30	NUM
alkej-30	139	46	classic	classic	ADJ
alkej-30	139	47	2	2	NUM
alkej-30	139	48	14,000,000	14,000,000	NUM
alkej-30	139	49	35	35	NUM
alkej-30	139	50	bipolar	bipolar	ADJ
alkej-30	139	51	30	30	NUM
alkej-30	139	52	classic	classic	ADJ
alkej-30	139	53	4	4	NUM
alkej-30	139	54	455,000	455,000	NUM
alkej-30	139	55	35	35	NUM
alkej-30	139	56	sigmoid	sigmoid	NOUN
alkej-30	139	57	10	10	NUM
alkej-30	139	58	classic	classic	ADJ
alkej-30	139	59	with	with	ADP
alkej-30	139	60	truncation	truncation	NOUN
alkej-30	139	61	16	16	NUM
alkej-30	139	62	280,000	280,000	NUM
alkej-30	139	63	74	74	NUM
alkej-30	139	64	bipolar	bipolar	ADJ
alkej-30	139	65	10	10	NUM
alkej-30	139	66	classic	classic	ADJ
alkej-30	139	67	with	with	ADP
alkej-30	139	68	truncation	truncation	NOUN
alkej-30	139	69	22	22	NUM
alkej-30	139	70	45,500	45,500	NUM
alkej-30	139	71	74	74	NUM
alkej-30	139	72	sigmoid	sigmoid	NOUN
alkej-30	139	73	10	10	NUM
alkej-30	139	74	proposed	propose	VERB
alkej-30	139	75	6	6	NUM
alkej-30	139	76	455,000	455,000	NUM
alkej-30	139	77	74	74	NUM
alkej-30	139	78	bipolar	bipolar	ADJ
alkej-30	139	79	10	10	NUM
alkej-30	139	80	proposed	propose	VERB
alkej-30	139	81	9	9	NUM
alkej-30	139	82	45,500	45,500	NUM
alkej-30	139	83	74	74	NUM
alkej-30	139	84	table	table	NOUN
alkej-30	139	85	(	(	PUNCT
alkej-30	139	86	2	2	NUM
alkej-30	139	87	):	):	PUNCT
alkej-30	139	88	quntization	quntization	NOUN
alkej-30	139	89	error	error	NOUN
alkej-30	139	90	,	,	PUNCT
alkej-30	139	91	cost	cost	NOUN
alkej-30	139	92	and	and	CCONJ
alkej-30	139	93	the	the	DET
alkej-30	139	94	maximum	maximum	ADJ
alkej-30	139	95	speed	speed	NOUN
alkej-30	139	96	of	of	ADP
alkej-30	139	97	nn	nn	NOUN
alkej-30	139	98	with	with	ADP
alkej-30	139	99	and	and	CCONJ
alkej-30	139	100	without	without	ADP
alkej-30	139	101	truncation	truncation	NOUN
alkej-30	139	102	.	.	PUNCT
alkej-30	140	1	ammar	ammar	PROPN
alkej-30	140	2	a.	a.	PROPN
alkej-30	140	3	hassan	hassan	PROPN
alkej-30	140	4	/al	/al	PROPN
alkej-30	140	5	-	-	PUNCT
alkej-30	140	6	khwarizmi	khwarizmi	PROPN
alkej-30	140	7	engineering	engineering	NOUN
alkej-30	140	8	journal	journal	PROPN
alkej-30	140	9	,	,	PUNCT
alkej-30	140	10	vol.2	vol.2	PROPN
alkej-30	140	11	,	,	PUNCT
alkej-30	140	12	no	no	INTJ
alkej-30	140	13	.	.	NOUN
alkej-30	140	14	2	2	NUM
alkej-30	140	15	pp	pp	ADP
alkej-30	140	16	32	32	NUM
alkej-30	140	17	-	-	SYM
alkej-30	140	18	41	41	NUM
alkej-30	140	19	(	(	PUNCT
alkej-30	140	20	2006	2006	NUM
alkej-30	140	21	)	)	PUNCT
alkej-30	140	22	34	34	NUM
alkej-30	140	23	the	the	DET
alkej-30	140	24	speed	speed	NOUN
alkej-30	140	25	to	to	ADP
alkej-30	140	26	twice	twice	DET
alkej-30	140	27	the	the	DET
alkej-30	140	28	original	original	ADJ
alkej-30	140	29	speed	speed	NOUN
alkej-30	140	30	but	but	CCONJ
alkej-30	140	31	increase	increase	VERB
alkej-30	140	32	the	the	DET
alkej-30	140	33	error	error	NOUN
alkej-30	140	34	from	from	ADP
alkej-30	140	35	2	2	NUM
alkej-30	140	36	%	%	NOUN
alkej-30	140	37	to	to	PART
alkej-30	140	38	10	10	NUM
alkej-30	140	39	%	%	NOUN
alkej-30	140	40	.	.	PUNCT
alkej-30	141	1	while	while	SCONJ
alkej-30	141	2	,	,	PUNCT
alkej-30	141	3	the	the	DET
alkej-30	141	4	direct	direct	ADJ
alkej-30	141	5	truncation	truncation	NOUN
alkej-30	141	6	with	with	ADP
alkej-30	141	7	classic	classic	ADJ
alkej-30	141	8	learning	learning	NOUN
alkej-30	141	9	algorithm	algorithm	NOUN
alkej-30	141	10	with	with	ADP
alkej-30	141	11	bipolar	bipolar	ADJ
alkej-30	141	12	transfer	transfer	NOUN
alkej-30	141	13	function	function	NOUN
alkej-30	141	14	will	will	AUX
alkej-30	141	15	give	give	VERB
alkej-30	141	16	a	a	DET
alkej-30	141	17	very	very	ADV
alkej-30	141	18	high	high	ADJ
alkej-30	141	19	error	error	NOUN
alkej-30	141	20	reaching	reach	VERB
alkej-30	141	21	to	to	ADP
alkej-30	141	22	25	25	NUM
alkej-30	141	23	%	%	NOUN
alkej-30	141	24	while	while	SCONJ
alkej-30	141	25	the	the	DET
alkej-30	141	26	truncation	truncation	NOUN
alkej-30	141	27	using	use	VERB
alkej-30	141	28	the	the	DET
alkej-30	141	29	proposed	propose	VERB
alkej-30	141	30	learning	learn	VERB
alkej-30	141	31	algorithm	algorithm	NOUN
alkej-30	141	32	with	with	ADP
alkej-30	141	33	bipolar	bipolar	ADJ
alkej-30	141	34	transfer	transfer	NOUN
alkej-30	141	35	function	function	NOUN
alkej-30	141	36	will	will	AUX
alkej-30	141	37	reduce	reduce	VERB
alkej-30	141	38	the	the	DET
alkej-30	141	39	error	error	NOUN
alkej-30	141	40	to	to	ADP
alkej-30	141	41	less	less	ADJ
alkej-30	141	42	than	than	ADP
alkej-30	141	43	10	10	NUM
alkej-30	141	44	%	%	NOUN
alkej-30	141	45	with	with	ADP
alkej-30	141	46	the	the	DET
alkej-30	141	47	same	same	ADJ
alkej-30	141	48	cost	cost	NOUN
alkej-30	141	49	and	and	CCONJ
alkej-30	141	50	same	same	ADJ
alkej-30	141	51	speed	speed	NOUN
alkej-30	141	52	.	.	PUNCT
alkej-30	142	1	8.references	8.references	NUM
alkej-30	143	1	[	[	X
alkej-30	143	2	1	1	NUM
alkej-30	143	3	]	]	PUNCT
alkej-30	143	4	m.	m.	NOUN
alkej-30	143	5	skrbek	skrbek	NOUN
alkej-30	143	6	,	,	PUNCT
alkej-30	143	7	“	"	PUNCT
alkej-30	143	8	fast	fast	ADJ
alkej-30	143	9	neural	neural	ADJ
alkej-30	143	10	network	network	NOUN
alkej-30	143	11	implementation	implementation	NOUN
alkej-30	143	12	”	"	PUNCT
alkej-30	143	13	,	,	PUNCT
alkej-30	143	14	neural	neural	ADJ
alkej-30	143	15	network	network	NOUN
alkej-30	143	16	world	world	NOUN
alkej-30	143	17	,	,	PUNCT
alkej-30	143	18	vol	vol	NOUN
alkej-30	143	19	.	.	PUNCT
alkej-30	143	20	vol	vol	NOUN
alkej-30	143	21	.	.	PROPN
alkej-30	143	22	9	9	NUM
alkej-30	143	23	,	,	PUNCT
alkej-30	143	24	n.	n.	NOUN
alkej-30	143	25	no	no	NOUN
alkej-30	143	26	.	.	PROPN
alkej-30	143	27	5	5	NUM
alkej-30	143	28	,	,	PUNCT
alkej-30	143	29	pp	pp	ADJ
alkej-30	143	30	.	.	PUNCT
alkej-30	144	1	375–391	375–391	NUM
alkej-30	144	2	,	,	PUNCT
alkej-30	144	3	1999	1999	NUM
alkej-30	144	4	.	.	PUNCT
alkej-30	145	1	[	[	X
alkej-30	145	2	2	2	X
alkej-30	145	3	]	]	PUNCT
alkej-30	145	4	j.	j.	PROPN
alkej-30	145	5	g.	g.	PROPN
alkej-30	145	6	eldredge	eldredge	PROPN
alkej-30	145	7	,	,	PUNCT
alkej-30	145	8	“	"	PUNCT
alkej-30	145	9	fpga	fpga	NOUN
alkej-30	145	10	density	density	NOUN
alkej-30	145	11	enhancement	enhancement	NOUN
alkej-30	145	12	of	of	ADP
alkej-30	145	13	a	a	DET
alkej-30	145	14	neural	neural	ADJ
alkej-30	145	15	network	network	NOUN
alkej-30	145	16	through	through	ADP
alkej-30	145	17	run	run	NOUN
alkej-30	145	18	-	-	PUNCT
alkej-30	145	19	time	time	NOUN
alkej-30	145	20	reconfiguration	reconfiguration	NOUN
alkej-30	145	21	”	"	PUNCT
alkej-30	145	22	,	,	PUNCT
alkej-30	145	23	master	master	NOUN
alkej-30	145	24	’s	’s	PART
alkej-30	145	25	thesis	thesis	NOUN
alkej-30	145	26	,	,	PUNCT
alkej-30	145	27	department	department	NOUN
alkej-30	145	28	of	of	ADP
alkej-30	145	29	electrical	electrical	ADJ
alkej-30	145	30	and	and	CCONJ
alkej-30	145	31	computer	computer	NOUN
alkej-30	145	32	engineering	engineering	NOUN
alkej-30	145	33	,	,	PUNCT
alkej-30	145	34	brigham	brigham	PROPN
alkej-30	145	35	young	young	PROPN
alkej-30	145	36	university	university	NOUN
alkej-30	145	37	,	,	PUNCT
alkej-30	145	38	may	may	PROPN
alkej-30	145	39	1994	1994	NUM
alkej-30	145	40	.	.	PUNCT
alkej-30	146	1	[	[	X
alkej-30	146	2	3	3	X
alkej-30	146	3	]	]	X
alkej-30	146	4	d.e	d.e	PROPN
alkej-30	146	5	rumelhart	rumelhart	PROPN
alkej-30	146	6	,	,	PUNCT
alkej-30	146	7	j.l	j.l	PROPN
alkej-30	146	8	mcclelland	mcclelland	PROPN
alkej-30	146	9	and	and	CCONJ
alkej-30	146	10	pdp	pdp	PROPN
alkej-30	146	11	research	research	NOUN
alkej-30	146	12	group	group	NOUN
alkej-30	146	13	,	,	PUNCT
alkej-30	146	14	parallel	parallel	ADJ
alkej-30	146	15	distrubuted	distrubuted	ADJ
alkej-30	146	16	processing	processing	NOUN
alkej-30	146	17	:	:	PUNCT
alkej-30	146	18	explorations	exploration	NOUN
alkej-30	146	19	in	in	ADP
alkej-30	146	20	the	the	DET
alkej-30	146	21	microstructure	microstructure	NOUN
alkej-30	146	22	of	of	ADP
alkej-30	146	23	cognition	cognition	NOUN
alkej-30	146	24	,	,	PUNCT
alkej-30	146	25	volume	volume	NOUN
alkej-30	146	26	1	1	NUM
alkej-30	146	27	:	:	PUNCT
alkej-30	146	28	foundations	foundation	NOUN
alkej-30	146	29	,	,	PUNCT
alkej-30	146	30	mit	mit	PROPN
alkej-30	146	31	press	press	NOUN
alkej-30	146	32	,	,	PUNCT
alkej-30	146	33	cambridge	cambridge	PROPN
alkej-30	146	34	,	,	PUNCT
alkej-30	146	35	massachusetts	massachusetts	PROPN
alkej-30	146	36	,	,	PUNCT
alkej-30	146	37	1986	1986	NUM
alkej-30	146	38	.	.	PUNCT
alkej-30	147	1	[	[	X
alkej-30	147	2	4	4	NUM
alkej-30	147	3	]	]	PUNCT
alkej-30	147	4	a.	a.	NOUN
alkej-30	147	5	dehon	dehon	PROPN
alkej-30	147	6	,	,	PUNCT
alkej-30	147	7	“	"	PUNCT
alkej-30	147	8	the	the	DET
alkej-30	147	9	density	density	NOUN
alkej-30	147	10	advantage	advantage	NOUN
alkej-30	147	11	of	of	ADP
alkej-30	147	12	configurable	configurable	ADJ
alkej-30	147	13	computing	computing	NOUN
alkej-30	147	14	”	"	PUNCT
alkej-30	147	15	,	,	PUNCT
alkej-30	147	16	ieee	ieee	NOUN
alkej-30	147	17	computer	computer	NOUN
alkej-30	147	18	,	,	PUNCT
alkej-30	147	19	vol	vol	NOUN
alkej-30	147	20	.	.	PROPN
alkej-30	147	21	33	33	NUM
alkej-30	147	22	,	,	PUNCT
alkej-30	147	23	n.	n.	NOUN
alkej-30	147	24	5	5	NUM
alkej-30	147	25	,	,	PUNCT
alkej-30	147	26	pp	pp	PROPN
alkej-30	147	27	.	.	PUNCT
alkej-30	148	1	41–49	41–49	NUM
alkej-30	148	2	,	,	PUNCT
alkej-30	148	3	april	april	PROPN
alkej-30	148	4	2000	2000	NUM
alkej-30	148	5	.	.	PUNCT
alkej-30	149	1	[	[	X
alkej-30	149	2	5	5	NUM
alkej-30	149	3	]	]	SYM
alkej-30	149	4	holt	holt	PROPN
alkej-30	149	5	,	,	PUNCT
alkej-30	149	6	j.l	j.l	PROPN
alkej-30	149	7	.	.	PROPN
alkej-30	149	8	,	,	PUNCT
alkej-30	149	9	t.e	t.e	PROPN
alkej-30	149	10	.	.	PROPN
alkej-30	149	11	baker	baker	PROPN
alkej-30	149	12	.	.	PUNCT
alkej-30	150	1	back	back	ADJ
alkej-30	150	2	propagation	propagation	NOUN
alkej-30	150	3	simulations	simulation	NOUN
alkej-30	150	4	using	use	VERB
alkej-30	150	5	limited	limited	ADJ
alkej-30	150	6	precision	precision	NOUN
alkej-30	150	7	calculations	calculation	NOUN
alkej-30	150	8	,	,	PUNCT
alkej-30	150	9	in	in	ADP
alkej-30	150	10	proceedings	proceeding	NOUN
alkej-30	150	11	of	of	ADP
alkej-30	150	12	international	international	ADJ
alkej-30	150	13	joint	joint	ADJ
alkej-30	150	14	conference	conference	NOUN
alkej-30	150	15	on	on	ADP
alkej-30	150	16	neural	neural	ADJ
alkej-30	150	17	networks	network	NOUN
alkej-30	150	18	.	.	PUNCT
alkej-30	151	1	1991	1991	NUM
alkej-30	151	2	.	.	PUNCT
alkej-30	152	1	pp	pp	ADV
alkej-30	152	2	121	121	NUM
alkej-30	152	3	-	-	SYM
alkej-30	152	4	126	126	NUM
alkej-30	152	5	vol	vol	NOUN
alkej-30	152	6	.	.	PUNCT
alkej-30	153	1	2	2	NUM
alkej-30	153	2	.	.	PUNCT
alkej-30	154	1	[	[	X
alkej-30	154	2	6	6	NUM
alkej-30	154	3	]	]	PUNCT
alkej-30	154	4	e.	e.	PROPN
alkej-30	154	5	k.	k.	PROPN
alkej-30	154	6	knight	knight	PROPN
alkej-30	154	7	,	,	PUNCT
alkej-30	154	8	“	"	PUNCT
alkej-30	154	9	artificial	artificial	ADJ
alkej-30	154	10	intellingence	intellingence	NOUN
alkej-30	154	11	”	"	PUNCT
alkej-30	154	12	mcgraw	mcgraw	PROPN
alkej-30	154	13	-	-	PUNCT
alkej-30	154	14	hill	hill	PROPN
alkej-30	154	15	new	new	PROPN
alkej-30	154	16	york	york	PROPN
alkej-30	154	17	,	,	PUNCT
alkej-30	154	18	second	second	ADJ
alkej-30	154	19	edition	edition	NOUN
alkej-30	154	20	,	,	PUNCT
alkej-30	154	21	1991	1991	NUM
alkej-30	154	22	.	.	PUNCT
alkej-30	155	1	[	[	X
alkej-30	155	2	7	7	NUM
alkej-30	155	3	]	]	SYM
alkej-30	155	4	xilinx.com	xilinx.com	X
alkej-30	155	5	,	,	PUNCT
alkej-30	155	6	“	"	PUNCT
alkej-30	155	7	virtextm2.5v	virtextm2.5v	X
alkej-30	155	8	fpgas	fpgas	NOUN
alkej-30	155	9	”	"	PUNCT
alkej-30	155	10	,	,	PUNCT
alkej-30	155	11	data	datum	NOUN
alkej-30	155	12	sheet	sheet	NOUN
alkej-30	155	13	,	,	PUNCT
alkej-30	155	14	www.xilinx.com	www.xilinx.com	PROPN
alkej-30	155	15	,	,	PUNCT
alkej-30	155	16	may	may	PROPN
alkej-30	155	17	1999	1999	NUM
alkej-30	155	18	.	.	PUNCT
alkej-30	156	1	[	[	X
alkej-30	156	2	8	8	NUM
alkej-30	156	3	]	]	X
alkej-30	156	4	wolf	wolf	PROPN
alkej-30	156	5	,	,	PUNCT
alkej-30	156	6	d.f	d.f	PROPN
alkej-30	156	7	.	.	PROPN
alkej-30	156	8	,	,	PUNCT
alkej-30	156	9	romero	romero	PROPN
alkej-30	156	10	,	,	PUNCT
alkej-30	156	11	r.	r.	PROPN
alkej-30	156	12	a.	a.	PROPN
alkej-30	156	13	f.	f.	PROPN
alkej-30	156	14	,	,	PUNCT
alkej-30	156	15	marques	marques	PROPN
alkej-30	156	16	,	,	PUNCT
alkej-30	156	17	e.	e.	PROPN
alkej-30	156	18	using	use	VERB
alkej-30	156	19	embedded	embed	VERB
alkej-30	156	20	processors	processor	NOUN
alkej-30	156	21	in	in	ADP
alkej-30	156	22	hardware	hardware	NOUN
alkej-30	156	23	models	model	NOUN
alkej-30	156	24	of	of	ADP
alkej-30	156	25	artificial	artificial	ADJ
alkej-30	156	26	neural	neural	ADJ
alkej-30	156	27	networks	network	NOUN
alkej-30	156	28	.	.	PUNCT
alkej-30	157	1	in	in	ADP
alkej-30	157	2	proceedings	proceeding	NOUN
alkej-30	157	3	of	of	ADP
alkej-30	157	4	sbai	sbai	NOUN
alkej-30	157	5	simp	simp	PROPN
alkej-30	157	6	َ	َ	PROPN
alkej-30	157	7	sio	sio	PROPN
alkej-30	157	8	brasileiro	brasileiro	PROPN
alkej-30	157	9	de	de	PROPN
alkej-30	157	10	automao	automao	PROPN
alkej-30	157	11	inteligente	inteligente	PROPN
alkej-30	157	12	.	.	PUNCT
alkej-30	158	1	2001	2001	NUM
alkej-30	158	2	.	.	PUNCT
alkej-30	159	1	pp	pp	ADV
alkej-30	159	2	78	78	NUM
alkej-30	159	3	-	-	SYM
alkej-30	159	4	83	83	NUM
alkej-30	159	5	.	.	PUNCT
alkej-30	160	1	9.list	9.list	NUM
alkej-30	160	2	of	of	ADP
alkej-30	160	3	symbols	symbols	PROPN
alkej-30	160	4	ann	ann	PROPN
alkej-30	160	5	:	:	PUNCT
alkej-30	160	6	artificial	artificial	ADJ
alkej-30	160	7	neural	neural	ADJ
alkej-30	160	8	network	network	NOUN
alkej-30	160	9	.	.	PUNCT
alkej-30	161	1	asic	asic	NOUN
alkej-30	161	2	:	:	PUNCT
alkej-30	161	3	specific	specific	ADJ
alkej-30	161	4	integrated	integrate	VERB
alkej-30	161	5	circuit	circuit	NOUN
alkej-30	161	6	.	.	PUNCT
alkej-30	162	1	cordic	cordic	ADJ
alkej-30	162	2	:	:	PUNCT
alkej-30	162	3	coordinate	coordinate	VERB
alkej-30	162	4	rotation	rotation	NOUN
alkej-30	162	5	digital	digital	ADJ
alkej-30	162	6	computer	computer	NOUN
alkej-30	162	7	.	.	PUNCT
alkej-30	163	1	fpga	fpga	PROPN
alkej-30	163	2	:	:	PUNCT
alkej-30	163	3	field	field	NOUN
alkej-30	163	4	programmable	programmable	ADJ
alkej-30	163	5	gate	gate	PROPN
alkej-30	163	6	array	array	NOUN
alkej-30	163	7	.	.	PUNCT
alkej-30	164	1	lc	lc	NOUN
alkej-30	164	2	:	:	PUNCT
alkej-30	164	3	logic	logic	NOUN
alkej-30	164	4	cell	cell	NOUN
alkej-30	164	5	.	.	PUNCT
alkej-30	165	1	lut	lut	PROPN
alkej-30	165	2	:	:	PUNCT
alkej-30	165	3	lookuptable	lookuptable	ADJ
alkej-30	165	4	.	.	PUNCT
alkej-30	166	1	ram	ram	NOUN
alkej-30	166	2	:	:	PUNCT
alkej-30	166	3	random	random	ADJ
alkej-30	166	4	access	access	NOUN
alkej-30	166	5	memory	memory	NOUN
alkej-30	166	6	.	.	PUNCT
alkej-30	167	1	ammar	ammar	PROPN
alkej-30	167	2	a.	a.	PROPN
alkej-30	167	3	hassan	hassan	PROPN
alkej-30	167	4	/al	/al	PROPN
alkej-30	167	5	-	-	PUNCT
alkej-30	167	6	khwarizmi	khwarizmi	PROPN
alkej-30	167	7	engineering	engineering	NOUN
alkej-30	167	8	journal	journal	PROPN
alkej-30	167	9	,	,	PUNCT
alkej-30	167	10	vol.2	vol.2	PROPN
alkej-30	167	11	,	,	PUNCT
alkej-30	167	12	no	no	INTJ
alkej-30	167	13	.	.	NOUN
alkej-30	167	14	2	2	NUM
alkej-30	167	15	pp	pp	ADP
alkej-30	167	16	32	32	NUM
alkej-30	167	17	-	-	SYM
alkej-30	167	18	41	41	NUM
alkej-30	167	19	(	(	PUNCT
alkej-30	167	20	2006	2006	NUM
alkej-30	167	21	)	)	PUNCT
alkej-30	167	22	34	34	NUM
alkej-30	167	23	بناء	بناء	ADP
alkej-30	167	24	مستوى	مستوى	PROPN
alkej-30	167	25	واطئ	واطئ	PROPN
alkej-30	167	26	الكلّفة	الكلّفة	PROPN
alkej-30	167	27	لخوارزمية	لخوارزمية	ADJ
alkej-30	167	28	االنتشار	االنتشار	PROPN
alkej-30	167	29	العكسي	العكسي	PROPN
alkej-30	167	30	عمار	عمار	PROPN
alkej-30	167	31	عادل	عادل	PROPN
alkej-30	167	32	حسن	حسن	NOUN
alkej-30	167	33	لهــندسـة/	لهــندسـة/	NUM
alkej-30	167	34	كــلية	كــلية	NOUN
alkej-30	167	35	اقـسم	اقـسم	PROPN
alkej-30	167	36	هـندسة	هـندسة	PROPN
alkej-30	167	37	الحـاسبـات	الحـاسبـات	PROPN
alkej-30	167	38	جامـعة	جامـعة	PROPN
alkej-30	167	39	بغـداد	بغـداد	ADJ
alkej-30	167	40	الخالصة	الخالصة	PROPN
alkej-30	167	41	:	:	PUNCT
alkej-30	167	42	(	(	PUNCT
alkej-30	167	43	كانت	كانت	INTJ
alkej-30	167	44	قليلة	قليلة	PROPN
alkej-30	167	45	وقبل	وقبل	PROPN
alkej-30	167	46	أكثر	أكثر	PROPN
alkej-30	167	47	من	من	INTJ
alkej-30	167	48	annsمن	annsمن	PROPN
alkej-30	167	49	أولى	أولى	PROPN
alkej-30	167	50	التطبيقات	التطبيقات	PROPN
alkej-30	168	1	الناجحة	الناجحة	ADJ
alkej-30	168	2	التي	التي	PROPN
alkej-30	168	3	تم	تم	NOUN
alkej-30	169	1	نشُرها	نشُرها	PROPN
alkej-30	169	2	للشبكات	للشبكات	ADJ
alkej-30	169	3	العصبية	العصبية	NOUN
alkej-30	169	4	االصطناعية	االصطناعية	PROPN
alkej-30	169	5	)	)	PUNCT
alkej-30	169	6	جال	جال	VERB
alkej-30	169	7	هذا	هذا	NOUN
alkej-30	169	8	النوع	النوع	NOUN
alkej-30	169	9	من	من	PRON
alkej-30	169	10	البحوث	البحوث	NOUN
alkej-30	169	11	.	.	PUNCT
alkej-30	170	1	يمتاز	يمتاز	PROPN
alkej-30	170	2	هذا	هذا	PROPN
alkej-30	170	3	الملخص	الملخص	PROPN
alkej-30	170	4	بتوفير	بتوفير	PROPN
alkej-30	170	5	الفكرة	الفكرة	PROPN
alkej-30	170	6	عقد	عقد	PROPN
alkej-30	170	7	.	.	PROPN
alkej-30	170	8	لذلك	لذلك	PROPN
alkej-30	170	9	حان	حان	PROPN
alkej-30	170	10	الوقت	الوقت	PROPN
alkej-30	170	11	لمراجعة	لمراجعة	PROPN
alkej-30	170	12	التقّدم	التقّدم	PROPN
alkej-30	170	13	الذي	الذي	PROPN
alkej-30	170	14	تم	تم	PUNCT
alkej-30	170	15	في	في	ADP
alkej-30	170	16	م	م	PROPN
alkej-30	170	17	لبناء	لبناء	NOUN
alkej-30	170	18	(	(	PUNCT
alkej-30	170	19	fpgas)األساسية	fpgas)األساسية	NOUN
alkej-30	170	20	حول	حول	PROPN
alkej-30	170	21	تطبيق	تطبيق	PROPN
alkej-30	170	22	أصناف	أصناف	PROPN
alkej-30	170	23	األنواع	األنواع	PROPN
alkej-30	170	24	المتوفرة	المتوفرة	PROPN
alkej-30	170	25	للبوابات	للبوابات	PROPN
alkej-30	170	26	المرتبة	المرتبة	PROPN
alkej-30	170	27	بصيغة	بصيغة	NOUN
alkej-30	170	28	صفوف	صفوف	VERB
alkej-30	170	29	قابلة	قابلة	PROPN
alkej-30	170	30	للبرمجة	للبرمجة	PROPN
alkej-30	170	31	الشبكات	الشبكات	PROPN
alkej-30	170	32	العصبية	العصبية	PROPN
alkej-30	170	33	االصطناعية	االصطناعية	PROPN
alkej-30	170	34	.	.	PUNCT
alkej-30	171	1	تقنيات	تقنيات	PROPN
alkej-30	171	2	مختلفة	مختلفة	PROPN
alkej-30	171	3	التطبيق	التطبيق	PROPN
alkej-30	171	4	وأفكار	وأفكار	NOUN
alkej-30	171	5	للتصميم	للتصميم	VERB
alkej-30	171	6	سيتم	سيتم	PROPN
alkej-30	171	7	مناقشتها	مناقشتها	PROPN
alkej-30	171	8	الحقاً	الحقاً	PROPN
alkej-30	171	9	,	,	PUNCT
alkej-30	171	10	مثالً	مثالً	PROPN
alkej-30	171	11	الحصول	الحصول	PROPN
alkej-30	171	12	على	على	PROPN
alkej-30	171	13	الدالة	الدالة	PROPN
alkej-30	171	14	الفاعلة	الفاعلة	PROPN
alkej-30	171	15	والمناسبة	والمناسبة	PROPN
alkej-30	171	16	وتقنية	وتقنية	NOUN
alkej-30	171	17	التقليم	التقليم	VERB
alkej-30	171	18	العددية	العددية	PROPN
alkej-30	171	19	.	.	PUNCT
alkej-30	172	1	كذلك	كذلك	PROPN
alkej-30	172	2	,	,	PUNCT
alkej-30	172	3	العمل	العمل	PROPN
alkej-30	172	4	على	على	PROPN
alkej-30	172	5	تحسين	تحسين	PROPN
alkej-30	172	6	خوارزمية	خوارزمية	PROPN
alkej-30	172	7	التعلم	التعلم	PROPN
alkej-30	172	8	للتقليل	للتقليل	NOUN
alkej-30	173	1	من	من	PRON
alkej-30	173	2	كلفة	كلفة	PROPN
alkej-30	173	3	بناء	بناء	ADP
alkej-30	173	4	الكلية	الكلية	PROPN
alkej-30	173	5	وتحسين	وتحسين	PROPN
alkej-30	173	6	أداء	أداء	PROPN
alkej-30	173	7	الشبكة	الشبكة	PROPN
alkej-30	173	8	العصبية	العصبية	PROPN
alkej-30	173	9	.	.	PUNCT
alkej-30	174	1	وأخيراً	وأخيراً	NOUN
alkej-30	174	2	,	,	PUNCT
alkej-30	174	3	بناء	بناء	ADP
alkej-30	174	4	دائرة	دائرة	ADJ
alkej-30	174	5	متكاملة	متكاملة	NOUN
alkej-30	174	6	لها	لها	NOUN
alkej-30	174	7	الخلية	الخلية	PROPN
alkej-30	174	8	العصبية	العصبية	PROPN
alkej-30	174	9	وبالتالي	وبالتالي	PROPN
alkej-30	174	10	تقليل	تقليل	PROPN
alkej-30	174	11	الكلفة	الكلفة	PROPN
alkej-30	174	12	07السرعة	07السرعة	PROPN
alkej-30	175	1	العالية	العالية	NOUN
alkej-30	175	2	لتميز	لتميز	NOUN
alkej-30	175	3	أشكال	أشكال	PROPN
alkej-30	175	4	األرقام	األرقام	PROPN
alkej-30	175	5	اإلنكليزية	اإلنكليزية	VERB
alkej-30	175	6	من	من	PROPN
alkej-30	175	7	خالل	خالل	PROPN
alkej-30	175	8	شبكة	شبكة	PROPN
alkej-30	175	9	عصبية	عصبية	NOUN
alkej-30	175	10	اصطناعية	اصطناعية	PROPN
alkej-30	175	11	لها	لها	PROPN
alkej-30	175	12	أربعة	أربعة	NOUN
alkej-30	175	13	طبقات	طبقات	PROPN
alkej-30	175	14	من	من	PROPN
alkej-30	175	15	خالل	خالل	PROPN
alkej-30	175	16	)	)	PUNCT
alkej-30	175	17	.	.	PUNCT
alkej-30	176	1	xilinx	xilinx	PROPN
alkej-30	176	2	fpga	fpga	PROPN
alkej-30	176	3	(	(	PUNCT
alkej-30	176	4	عقدة	عقدة	NOUN
alkej-30	176	5	)	)	PUNCT
alkej-30	176	6	خلية	خلية	PROPN
alkej-30	176	7	عصبية	عصبية	PROPN
alkej-30	176	8	(	(	PUNCT
alkej-30	176	9	على	على	PROPN
alkej-30	176	10	رقاقة	رقاقة	NOUN
alkej-30	176	11	واحدة	واحدة	PROPN
alkej-30	176	12	باستخدام	باستخدام	NOUN
alkej-30	176	13	تقنية	تقنية	X