id	sid	tid	token	lemma	pos
app01-4029	1	1	acta	acta	PROPN
app01-4029	1	2	polytechnica	polytechnica	PROPN
app01-4029	1	3	ctu	ctu	PROPN
app01-4029	1	4	proceedings	proceeding	NOUN
app01-4029	1	5	doi:10.14311	doi:10.14311	NOUN
app01-4029	1	6	/	/	SYM
app01-4029	1	7	app.2017.12.0099	app.2017.12.0099	PROPN
app01-4029	1	8	acta	acta	PROPN
app01-4029	1	9	polytechnica	polytechnica	PROPN
app01-4029	1	10	ctu	ctu	NOUN
app01-4029	1	11	proceedings	proceeding	NOUN
app01-4029	1	12	12:99–103	12:99–103	NUM
app01-4029	1	13	,	,	PUNCT
app01-4029	1	14	2017	2017	NUM
app01-4029	1	15	©	©	PROPN
app01-4029	1	16	czech	czech	PROPN
app01-4029	1	17	technical	technical	PROPN
app01-4029	1	18	university	university	PROPN
app01-4029	1	19	in	in	ADP
app01-4029	1	20	prague	prague	PROPN
app01-4029	1	21	,	,	PUNCT
app01-4029	1	22	2017	2017	NUM
app01-4029	1	23	available	available	ADJ
app01-4029	1	24	online	online	ADV
app01-4029	1	25	at	at	ADP
app01-4029	1	26	http://ojs.cvut.cz/ojs/index.php/app	http://ojs.cvut.cz/ojs/index.php/app	ADV
app01-4029	1	27	artificial	artificial	ADJ
app01-4029	1	28	neural	neural	ADJ
app01-4029	1	29	network	network	NOUN
app01-4029	1	30	for	for	ADP
app01-4029	1	31	models	model	NOUN
app01-4029	1	32	of	of	ADP
app01-4029	1	33	human	human	ADJ
app01-4029	1	34	operator	operator	NOUN
app01-4029	1	35	martin	martin	PROPN
app01-4029	1	36	růžek	růžek	PROPN
app01-4029	1	37	czech	czech	PROPN
app01-4029	1	38	institute	institute	PROPN
app01-4029	1	39	of	of	ADP
app01-4029	1	40	informatics	informatics	PROPN
app01-4029	1	41	,	,	PUNCT
app01-4029	1	42	robotics	robotic	NOUN
app01-4029	1	43	and	and	CCONJ
app01-4029	1	44	cybernetics	cybernetic	NOUN
app01-4029	1	45	(	(	PUNCT
app01-4029	1	46	ciirc	ciirc	PROPN
app01-4029	1	47	)	)	PUNCT
app01-4029	1	48	,	,	PUNCT
app01-4029	1	49	czech	czech	PROPN
app01-4029	1	50	technical	technical	PROPN
app01-4029	1	51	university	university	PROPN
app01-4029	1	52	in	in	ADP
app01-4029	1	53	prague	prague	PROPN
app01-4029	1	54	,	,	PUNCT
app01-4029	1	55	zikova	zikova	X
app01-4029	1	56	4	4	NUM
app01-4029	1	57	,	,	PUNCT
app01-4029	1	58	166	166	NUM
app01-4029	1	59	36	36	NUM
app01-4029	1	60	prague	prague	NOUN
app01-4029	1	61	6	6	NUM
app01-4029	1	62	,	,	PUNCT
app01-4029	1	63	czech	czech	PROPN
app01-4029	1	64	republic	republic	NOUN
app01-4029	1	65	correspondence	correspondence	NOUN
app01-4029	1	66	:	:	PUNCT
app01-4029	1	67	martin.ruzek@cvut.cz	martin.ruzek@cvut.cz	NOUN
app01-4029	1	68	abstract	abstract	ADJ
app01-4029	1	69	.	.	PUNCT
app01-4029	2	1	this	this	DET
app01-4029	2	2	paper	paper	NOUN
app01-4029	2	3	presents	present	VERB
app01-4029	2	4	a	a	DET
app01-4029	2	5	new	new	ADJ
app01-4029	2	6	approach	approach	NOUN
app01-4029	2	7	to	to	ADP
app01-4029	2	8	mental	mental	ADJ
app01-4029	2	9	functions	function	NOUN
app01-4029	2	10	modeling	modeling	NOUN
app01-4029	2	11	with	with	ADP
app01-4029	2	12	the	the	DET
app01-4029	2	13	use	use	NOUN
app01-4029	2	14	of	of	ADP
app01-4029	2	15	artificial	artificial	ADJ
app01-4029	2	16	neural	neural	ADJ
app01-4029	2	17	networks	network	NOUN
app01-4029	2	18	.	.	PUNCT
app01-4029	3	1	the	the	DET
app01-4029	3	2	artificial	artificial	ADJ
app01-4029	3	3	neural	neural	ADJ
app01-4029	3	4	networks	network	NOUN
app01-4029	3	5	seems	seem	VERB
app01-4029	3	6	to	to	PART
app01-4029	3	7	be	be	AUX
app01-4029	3	8	a	a	DET
app01-4029	3	9	promising	promising	ADJ
app01-4029	3	10	method	method	NOUN
app01-4029	3	11	for	for	ADP
app01-4029	3	12	the	the	DET
app01-4029	3	13	modeling	modeling	NOUN
app01-4029	3	14	of	of	ADP
app01-4029	3	15	a	a	DET
app01-4029	3	16	human	human	ADJ
app01-4029	3	17	operator	operator	NOUN
app01-4029	3	18	because	because	SCONJ
app01-4029	3	19	the	the	DET
app01-4029	3	20	architecture	architecture	NOUN
app01-4029	3	21	of	of	ADP
app01-4029	3	22	the	the	DET
app01-4029	3	23	ann	ann	PROPN
app01-4029	3	24	is	be	AUX
app01-4029	3	25	directly	directly	ADV
app01-4029	3	26	inspired	inspire	VERB
app01-4029	3	27	by	by	ADP
app01-4029	3	28	the	the	DET
app01-4029	3	29	biological	biological	ADJ
app01-4029	3	30	neuron	neuron	NOUN
app01-4029	3	31	.	.	PUNCT
app01-4029	4	1	on	on	ADP
app01-4029	4	2	the	the	DET
app01-4029	4	3	other	other	ADJ
app01-4029	4	4	hand	hand	NOUN
app01-4029	4	5	,	,	PUNCT
app01-4029	4	6	the	the	DET
app01-4029	4	7	classical	classical	ADJ
app01-4029	4	8	paradigms	paradigm	NOUN
app01-4029	4	9	of	of	ADP
app01-4029	4	10	artificial	artificial	ADJ
app01-4029	4	11	neural	neural	ADJ
app01-4029	4	12	networks	network	NOUN
app01-4029	4	13	are	be	AUX
app01-4029	4	14	not	not	PART
app01-4029	4	15	suitable	suitable	ADJ
app01-4029	4	16	because	because	SCONJ
app01-4029	4	17	they	they	PRON
app01-4029	4	18	simplify	simplify	VERB
app01-4029	4	19	too	too	ADV
app01-4029	4	20	much	much	ADV
app01-4029	4	21	the	the	DET
app01-4029	4	22	real	real	ADJ
app01-4029	4	23	processes	process	NOUN
app01-4029	4	24	in	in	ADP
app01-4029	4	25	biological	biological	ADJ
app01-4029	4	26	neural	neural	ADJ
app01-4029	4	27	network	network	NOUN
app01-4029	4	28	.	.	PUNCT
app01-4029	5	1	the	the	DET
app01-4029	5	2	search	search	NOUN
app01-4029	5	3	for	for	ADP
app01-4029	5	4	a	a	DET
app01-4029	5	5	compromise	compromise	NOUN
app01-4029	5	6	between	between	ADP
app01-4029	5	7	the	the	DET
app01-4029	5	8	complexity	complexity	NOUN
app01-4029	5	9	of	of	ADP
app01-4029	5	10	biological	biological	ADJ
app01-4029	5	11	neural	neural	ADJ
app01-4029	5	12	network	network	NOUN
app01-4029	5	13	and	and	CCONJ
app01-4029	5	14	the	the	DET
app01-4029	5	15	practical	practical	ADJ
app01-4029	5	16	feasibility	feasibility	NOUN
app01-4029	5	17	of	of	ADP
app01-4029	5	18	the	the	DET
app01-4029	5	19	artificial	artificial	ADJ
app01-4029	5	20	network	network	NOUN
app01-4029	5	21	led	lead	VERB
app01-4029	5	22	to	to	ADP
app01-4029	5	23	a	a	DET
app01-4029	5	24	new	new	ADJ
app01-4029	5	25	learning	learning	NOUN
app01-4029	5	26	algorithm	algorithm	NOUN
app01-4029	5	27	.	.	PUNCT
app01-4029	6	1	this	this	DET
app01-4029	6	2	algorithm	algorithm	NOUN
app01-4029	6	3	is	be	AUX
app01-4029	6	4	based	base	VERB
app01-4029	6	5	on	on	ADP
app01-4029	6	6	the	the	DET
app01-4029	6	7	classical	classical	ADJ
app01-4029	6	8	multilayered	multilayere	VERB
app01-4029	6	9	neural	neural	ADJ
app01-4029	6	10	network	network	NOUN
app01-4029	6	11	;	;	PUNCT
app01-4029	6	12	however	however	ADV
app01-4029	6	13	,	,	PUNCT
app01-4029	6	14	the	the	DET
app01-4029	6	15	learning	learning	NOUN
app01-4029	6	16	rule	rule	NOUN
app01-4029	6	17	is	be	AUX
app01-4029	6	18	different	different	ADJ
app01-4029	6	19	.	.	PUNCT
app01-4029	7	1	the	the	DET
app01-4029	7	2	neurons	neuron	NOUN
app01-4029	7	3	are	be	AUX
app01-4029	7	4	updating	update	VERB
app01-4029	7	5	their	their	PRON
app01-4029	7	6	parameters	parameter	NOUN
app01-4029	7	7	in	in	ADP
app01-4029	7	8	a	a	DET
app01-4029	7	9	way	way	NOUN
app01-4029	7	10	that	that	PRON
app01-4029	7	11	is	be	AUX
app01-4029	7	12	similar	similar	ADJ
app01-4029	7	13	to	to	ADP
app01-4029	7	14	real	real	ADJ
app01-4029	7	15	biological	biological	ADJ
app01-4029	7	16	processes	process	NOUN
app01-4029	7	17	.	.	PUNCT
app01-4029	8	1	the	the	DET
app01-4029	8	2	basic	basic	ADJ
app01-4029	8	3	idea	idea	NOUN
app01-4029	8	4	is	be	AUX
app01-4029	8	5	that	that	SCONJ
app01-4029	8	6	the	the	DET
app01-4029	8	7	neurons	neuron	NOUN
app01-4029	8	8	are	be	AUX
app01-4029	8	9	competing	compete	VERB
app01-4029	8	10	for	for	ADP
app01-4029	8	11	resources	resource	NOUN
app01-4029	8	12	and	and	CCONJ
app01-4029	8	13	the	the	DET
app01-4029	8	14	criterion	criterion	NOUN
app01-4029	8	15	to	to	PART
app01-4029	8	16	decide	decide	VERB
app01-4029	8	17	which	which	DET
app01-4029	8	18	neuron	neuron	NOUN
app01-4029	8	19	will	will	AUX
app01-4029	8	20	survive	survive	VERB
app01-4029	8	21	is	be	AUX
app01-4029	8	22	the	the	DET
app01-4029	8	23	usefulness	usefulness	NOUN
app01-4029	8	24	of	of	ADP
app01-4029	8	25	the	the	DET
app01-4029	8	26	neuron	neuron	NOUN
app01-4029	8	27	to	to	ADP
app01-4029	8	28	the	the	DET
app01-4029	8	29	whole	whole	ADJ
app01-4029	8	30	neural	neural	ADJ
app01-4029	8	31	network	network	NOUN
app01-4029	8	32	.	.	PUNCT
app01-4029	9	1	the	the	DET
app01-4029	9	2	neuron	neuron	NOUN
app01-4029	9	3	is	be	AUX
app01-4029	9	4	not	not	PART
app01-4029	9	5	using	use	VERB
app01-4029	9	6	"	"	PUNCT
app01-4029	9	7	teacher	teacher	NOUN
app01-4029	9	8	"	"	PUNCT
app01-4029	9	9	or	or	CCONJ
app01-4029	9	10	any	any	DET
app01-4029	9	11	kind	kind	NOUN
app01-4029	9	12	of	of	ADP
app01-4029	9	13	superior	superior	ADJ
app01-4029	9	14	system	system	NOUN
app01-4029	9	15	,	,	PUNCT
app01-4029	9	16	the	the	DET
app01-4029	9	17	neuron	neuron	NOUN
app01-4029	9	18	receives	receive	VERB
app01-4029	9	19	only	only	ADV
app01-4029	9	20	the	the	DET
app01-4029	9	21	information	information	NOUN
app01-4029	9	22	that	that	PRON
app01-4029	9	23	is	be	AUX
app01-4029	9	24	present	present	ADJ
app01-4029	9	25	in	in	ADP
app01-4029	9	26	the	the	DET
app01-4029	9	27	biological	biological	ADJ
app01-4029	9	28	system	system	NOUN
app01-4029	9	29	.	.	PUNCT
app01-4029	10	1	the	the	DET
app01-4029	10	2	learning	learning	NOUN
app01-4029	10	3	process	process	NOUN
app01-4029	10	4	can	can	AUX
app01-4029	10	5	be	be	AUX
app01-4029	10	6	seen	see	VERB
app01-4029	10	7	as	as	ADP
app01-4029	10	8	searching	search	VERB
app01-4029	10	9	of	of	ADP
app01-4029	10	10	some	some	DET
app01-4029	10	11	equilibrium	equilibrium	NOUN
app01-4029	10	12	point	point	NOUN
app01-4029	10	13	that	that	PRON
app01-4029	10	14	is	be	AUX
app01-4029	10	15	equal	equal	ADJ
app01-4029	10	16	to	to	ADP
app01-4029	10	17	a	a	DET
app01-4029	10	18	state	state	NOUN
app01-4029	10	19	with	with	ADP
app01-4029	10	20	maximal	maximal	ADJ
app01-4029	10	21	importance	importance	NOUN
app01-4029	10	22	of	of	ADP
app01-4029	10	23	the	the	DET
app01-4029	10	24	neuron	neuron	NOUN
app01-4029	10	25	for	for	ADP
app01-4029	10	26	the	the	DET
app01-4029	10	27	neural	neural	ADJ
app01-4029	10	28	network	network	NOUN
app01-4029	10	29	.	.	PUNCT
app01-4029	11	1	this	this	DET
app01-4029	11	2	position	position	NOUN
app01-4029	11	3	can	can	AUX
app01-4029	11	4	change	change	VERB
app01-4029	11	5	if	if	SCONJ
app01-4029	11	6	the	the	DET
app01-4029	11	7	environment	environment	NOUN
app01-4029	11	8	changes	change	VERB
app01-4029	11	9	.	.	PUNCT
app01-4029	12	1	the	the	DET
app01-4029	12	2	name	name	NOUN
app01-4029	12	3	of	of	ADP
app01-4029	12	4	this	this	DET
app01-4029	12	5	type	type	NOUN
app01-4029	12	6	of	of	ADP
app01-4029	12	7	learning	learning	NOUN
app01-4029	12	8	,	,	PUNCT
app01-4029	12	9	the	the	DET
app01-4029	12	10	homeostatic	homeostatic	ADJ
app01-4029	12	11	artificial	artificial	ADJ
app01-4029	12	12	neural	neural	ADJ
app01-4029	12	13	network	network	NOUN
app01-4029	12	14	,	,	PUNCT
app01-4029	12	15	originates	originate	NOUN
app01-4029	12	16	from	from	ADP
app01-4029	12	17	this	this	DET
app01-4029	12	18	idea	idea	NOUN
app01-4029	12	19	,	,	PUNCT
app01-4029	12	20	as	as	SCONJ
app01-4029	12	21	it	it	PRON
app01-4029	12	22	is	be	AUX
app01-4029	12	23	similar	similar	ADJ
app01-4029	12	24	to	to	ADP
app01-4029	12	25	the	the	DET
app01-4029	12	26	process	process	NOUN
app01-4029	12	27	of	of	ADP
app01-4029	12	28	homeostasis	homeostasis	NOUN
app01-4029	12	29	known	know	VERB
app01-4029	12	30	in	in	ADP
app01-4029	12	31	any	any	DET
app01-4029	12	32	living	live	VERB
app01-4029	12	33	cell	cell	NOUN
app01-4029	12	34	.	.	PUNCT
app01-4029	13	1	the	the	DET
app01-4029	13	2	simulation	simulation	NOUN
app01-4029	13	3	results	result	NOUN
app01-4029	13	4	suggest	suggest	VERB
app01-4029	13	5	that	that	SCONJ
app01-4029	13	6	this	this	DET
app01-4029	13	7	type	type	NOUN
app01-4029	13	8	of	of	ADP
app01-4029	13	9	learning	learning	NOUN
app01-4029	13	10	can	can	AUX
app01-4029	13	11	be	be	AUX
app01-4029	13	12	useful	useful	ADJ
app01-4029	13	13	also	also	ADV
app01-4029	13	14	in	in	ADP
app01-4029	13	15	other	other	ADJ
app01-4029	13	16	tasks	task	NOUN
app01-4029	13	17	of	of	ADP
app01-4029	13	18	artificial	artificial	ADJ
app01-4029	13	19	learning	learning	NOUN
app01-4029	13	20	and	and	CCONJ
app01-4029	13	21	recognition	recognition	NOUN
app01-4029	13	22	.	.	PUNCT
app01-4029	14	1	keywords	keyword	NOUN
app01-4029	14	2	:	:	PUNCT
app01-4029	14	3	neural	neural	ADJ
app01-4029	14	4	network	network	NOUN
app01-4029	14	5	,	,	PUNCT
app01-4029	14	6	artificial	artificial	ADJ
app01-4029	14	7	neuron	neuron	NOUN
app01-4029	14	8	,	,	PUNCT
app01-4029	14	9	learning	learn	VERB
app01-4029	14	10	algorithm	algorithm	NOUN
app01-4029	14	11	,	,	PUNCT
app01-4029	14	12	mental	mental	ADJ
app01-4029	14	13	model	model	NOUN
app01-4029	14	14	.	.	PUNCT
app01-4029	15	1	1	1	X
app01-4029	15	2	.	.	X
app01-4029	15	3	introduction	introduction	NOUN
app01-4029	15	4	for	for	ADP
app01-4029	15	5	many	many	ADJ
app01-4029	15	6	practical	practical	ADJ
app01-4029	15	7	applications	application	NOUN
app01-4029	15	8	it	it	PRON
app01-4029	15	9	would	would	AUX
app01-4029	15	10	be	be	AUX
app01-4029	15	11	useful	useful	ADJ
app01-4029	15	12	to	to	PART
app01-4029	15	13	have	have	VERB
app01-4029	15	14	a	a	DET
app01-4029	15	15	model	model	NOUN
app01-4029	15	16	of	of	ADP
app01-4029	15	17	a	a	DET
app01-4029	15	18	human	human	ADJ
app01-4029	15	19	operator	operator	NOUN
app01-4029	15	20	,	,	PUNCT
app01-4029	15	21	as	as	ADP
app01-4029	15	22	for	for	ADP
app01-4029	15	23	example	example	NOUN
app01-4029	15	24	in	in	ADP
app01-4029	15	25	transport	transport	NOUN
app01-4029	15	26	engineering	engineering	NOUN
app01-4029	15	27	where	where	SCONJ
app01-4029	15	28	the	the	DET
app01-4029	15	29	human	human	ADJ
app01-4029	15	30	operator	operator	NOUN
app01-4029	15	31	plays	play	VERB
app01-4029	15	32	a	a	DET
app01-4029	15	33	principal	principal	ADJ
app01-4029	15	34	role	role	NOUN
app01-4029	15	35	.	.	PUNCT
app01-4029	16	1	unfortunately	unfortunately	ADV
app01-4029	16	2	,	,	PUNCT
app01-4029	16	3	the	the	DET
app01-4029	16	4	human	human	ADJ
app01-4029	16	5	factor	factor	NOUN
app01-4029	16	6	causes	cause	VERB
app01-4029	16	7	also	also	ADV
app01-4029	16	8	most	most	ADJ
app01-4029	16	9	of	of	ADP
app01-4029	16	10	the	the	DET
app01-4029	16	11	accidents	accident	NOUN
app01-4029	16	12	;	;	PUNCT
app01-4029	16	13	therefore	therefore	ADV
app01-4029	16	14	it	it	PRON
app01-4029	16	15	would	would	AUX
app01-4029	16	16	be	be	AUX
app01-4029	16	17	helpful	helpful	ADJ
app01-4029	16	18	to	to	PART
app01-4029	16	19	understand	understand	VERB
app01-4029	16	20	the	the	DET
app01-4029	16	21	processes	process	NOUN
app01-4029	16	22	in	in	ADP
app01-4029	16	23	the	the	DET
app01-4029	16	24	human	human	ADJ
app01-4029	16	25	brain	brain	NOUN
app01-4029	16	26	.	.	PUNCT
app01-4029	17	1	due	due	ADP
app01-4029	17	2	to	to	ADP
app01-4029	17	3	the	the	DET
app01-4029	17	4	complex	complex	ADJ
app01-4029	17	5	nature	nature	NOUN
app01-4029	17	6	of	of	ADP
app01-4029	17	7	the	the	DET
app01-4029	17	8	human	human	ADJ
app01-4029	17	9	brain	brain	NOUN
app01-4029	17	10	it	it	PRON
app01-4029	17	11	is	be	AUX
app01-4029	17	12	however	however	ADV
app01-4029	17	13	very	very	ADV
app01-4029	17	14	difficult	difficult	ADJ
app01-4029	17	15	to	to	PART
app01-4029	17	16	model	model	VERB
app01-4029	17	17	and	and	CCONJ
app01-4029	17	18	predict	predict	VERB
app01-4029	17	19	its	its	PRON
app01-4029	17	20	behavior	behavior	NOUN
app01-4029	17	21	.	.	PUNCT
app01-4029	18	1	he	he	PRON
app01-4029	18	2	need	need	VERB
app01-4029	18	3	to	to	PART
app01-4029	18	4	dispose	dispose	VERB
app01-4029	18	5	of	of	ADP
app01-4029	18	6	the	the	DET
app01-4029	18	7	model	model	NOUN
app01-4029	18	8	of	of	ADP
app01-4029	18	9	a	a	DET
app01-4029	18	10	human	human	ADJ
app01-4029	18	11	operator	operator	NOUN
app01-4029	18	12	,	,	PUNCT
app01-4029	18	13	as	as	ADP
app01-4029	18	14	the	the	DET
app01-4029	18	15	most	most	ADV
app01-4029	18	16	complex	complex	ADJ
app01-4029	18	17	part	part	NOUN
app01-4029	18	18	of	of	ADP
app01-4029	18	19	many	many	ADJ
app01-4029	18	20	transport	transport	NOUN
app01-4029	18	21	systems	system	NOUN
app01-4029	18	22	,	,	PUNCT
app01-4029	18	23	stays	stay	VERB
app01-4029	18	24	behind	behind	ADP
app01-4029	18	25	this	this	DET
app01-4029	18	26	research	research	NOUN
app01-4029	18	27	.	.	PUNCT
app01-4029	19	1	the	the	DET
app01-4029	19	2	transport	transport	NOUN
app01-4029	19	3	and	and	CCONJ
app01-4029	19	4	traffic	traffic	NOUN
app01-4029	19	5	simulations	simulation	NOUN
app01-4029	19	6	are	be	AUX
app01-4029	19	7	on	on	ADP
app01-4029	19	8	high	high	ADJ
app01-4029	19	9	level	level	NOUN
app01-4029	19	10	,	,	PUNCT
app01-4029	19	11	but	but	CCONJ
app01-4029	19	12	the	the	DET
app01-4029	19	13	principal	principal	ADJ
app01-4029	19	14	component	component	NOUN
app01-4029	19	15	of	of	ADP
app01-4029	19	16	any	any	DET
app01-4029	19	17	transport	transport	NOUN
app01-4029	19	18	system	system	NOUN
app01-4029	19	19	–	–	PUNCT
app01-4029	19	20	the	the	DET
app01-4029	19	21	human	human	ADJ
app01-4029	19	22	factor	factor	NOUN
app01-4029	19	23	–	–	PUNCT
app01-4029	19	24	is	be	AUX
app01-4029	19	25	still	still	ADV
app01-4029	19	26	quite	quite	ADV
app01-4029	19	27	unexplored	unexplored	ADJ
app01-4029	19	28	.	.	PUNCT
app01-4029	20	1	the	the	DET
app01-4029	20	2	main	main	ADJ
app01-4029	20	3	obstacles	obstacle	NOUN
app01-4029	20	4	are	be	AUX
app01-4029	20	5	the	the	DET
app01-4029	20	6	lack	lack	NOUN
app01-4029	20	7	of	of	ADP
app01-4029	20	8	knowledge	knowledge	NOUN
app01-4029	20	9	about	about	ADP
app01-4029	20	10	the	the	DET
app01-4029	20	11	mental	mental	ADJ
app01-4029	20	12	processes	process	NOUN
app01-4029	20	13	and	and	CCONJ
app01-4029	20	14	the	the	DET
app01-4029	20	15	differences	difference	NOUN
app01-4029	20	16	between	between	ADP
app01-4029	20	17	the	the	DET
app01-4029	20	18	typical	typical	ADJ
app01-4029	20	19	artificial	artificial	ADJ
app01-4029	20	20	intelligence	intelligence	NOUN
app01-4029	20	21	approaches	approach	NOUN
app01-4029	20	22	and	and	CCONJ
app01-4029	20	23	the	the	DET
app01-4029	20	24	biological	biological	ADJ
app01-4029	20	25	neural	neural	ADJ
app01-4029	20	26	networks	network	NOUN
app01-4029	20	27	.	.	PUNCT
app01-4029	21	1	the	the	DET
app01-4029	21	2	artificial	artificial	ADJ
app01-4029	21	3	neural	neural	ADJ
app01-4029	21	4	networks	network	NOUN
app01-4029	21	5	(	(	PUNCT
app01-4029	21	6	ann	ann	PROPN
app01-4029	21	7	)	)	PUNCT
app01-4029	21	8	seems	seem	VERB
app01-4029	21	9	to	to	PART
app01-4029	21	10	be	be	AUX
app01-4029	21	11	a	a	DET
app01-4029	21	12	promising	promising	ADJ
app01-4029	21	13	method	method	NOUN
app01-4029	21	14	for	for	ADP
app01-4029	21	15	these	these	DET
app01-4029	21	16	models	model	NOUN
app01-4029	21	17	because	because	SCONJ
app01-4029	21	18	the	the	DET
app01-4029	21	19	architecture	architecture	NOUN
app01-4029	21	20	of	of	ADP
app01-4029	21	21	the	the	DET
app01-4029	21	22	ann	ann	PROPN
app01-4029	21	23	is	be	AUX
app01-4029	21	24	directly	directly	ADV
app01-4029	21	25	inspired	inspire	VERB
app01-4029	21	26	by	by	ADP
app01-4029	21	27	the	the	DET
app01-4029	21	28	biological	biological	ADJ
app01-4029	21	29	neuron	neuron	NOUN
app01-4029	21	30	and	and	CCONJ
app01-4029	21	31	also	also	ADV
app01-4029	21	32	because	because	SCONJ
app01-4029	21	33	it	it	PRON
app01-4029	21	34	is	be	AUX
app01-4029	21	35	data	datum	NOUN
app01-4029	21	36	driven	drive	VERB
app01-4029	21	37	method	method	NOUN
app01-4029	21	38	.	.	PUNCT
app01-4029	22	1	the	the	DET
app01-4029	22	2	classical	classical	ADJ
app01-4029	22	3	paradigms	paradigm	NOUN
app01-4029	22	4	of	of	ADP
app01-4029	22	5	artificial	artificial	ADJ
app01-4029	22	6	neural	neural	ADJ
app01-4029	22	7	networks	network	NOUN
app01-4029	22	8	are	be	AUX
app01-4029	22	9	however	however	ADV
app01-4029	22	10	not	not	PART
app01-4029	22	11	suitable	suitable	ADJ
app01-4029	22	12	for	for	ADP
app01-4029	22	13	direct	direct	ADJ
app01-4029	22	14	use	use	NOUN
app01-4029	22	15	because	because	SCONJ
app01-4029	22	16	they	they	PRON
app01-4029	22	17	simplify	simplify	VERB
app01-4029	22	18	too	too	ADV
app01-4029	22	19	much	much	ADV
app01-4029	22	20	the	the	DET
app01-4029	22	21	real	real	ADJ
app01-4029	22	22	processes	process	NOUN
app01-4029	22	23	in	in	ADP
app01-4029	22	24	biological	biological	ADJ
app01-4029	22	25	neural	neural	ADJ
app01-4029	22	26	network	network	NOUN
app01-4029	22	27	,	,	PUNCT
app01-4029	22	28	but	but	CCONJ
app01-4029	22	29	it	it	PRON
app01-4029	22	30	is	be	AUX
app01-4029	22	31	possible	possible	ADJ
app01-4029	22	32	to	to	PART
app01-4029	22	33	update	update	VERB
app01-4029	22	34	the	the	DET
app01-4029	22	35	learning	learning	NOUN
app01-4029	22	36	algorithm	algorithm	NOUN
app01-4029	22	37	so	so	SCONJ
app01-4029	22	38	that	that	SCONJ
app01-4029	22	39	it	it	PRON
app01-4029	22	40	corresponds	correspond	VERB
app01-4029	22	41	more	more	ADV
app01-4029	22	42	frankly	frankly	ADV
app01-4029	22	43	to	to	ADP
app01-4029	22	44	the	the	DET
app01-4029	22	45	biological	biological	ADJ
app01-4029	22	46	reality	reality	NOUN
app01-4029	22	47	.	.	PUNCT
app01-4029	23	1	the	the	DET
app01-4029	23	2	neural	neural	ADJ
app01-4029	23	3	networks	network	NOUN
app01-4029	23	4	have	have	AUX
app01-4029	23	5	already	already	ADV
app01-4029	23	6	been	be	AUX
app01-4029	23	7	used	use	VERB
app01-4029	23	8	in	in	ADP
app01-4029	23	9	several	several	ADJ
app01-4029	23	10	projects	project	NOUN
app01-4029	23	11	aimed	aim	VERB
app01-4029	23	12	at	at	ADP
app01-4029	23	13	mental	mental	ADJ
app01-4029	23	14	models	model	NOUN
app01-4029	23	15	.	.	PUNCT
app01-4029	24	1	one	one	NUM
app01-4029	24	2	of	of	ADP
app01-4029	24	3	them	they	PRON
app01-4029	24	4	is	be	AUX
app01-4029	24	5	the	the	DET
app01-4029	24	6	blue	blue	ADJ
app01-4029	24	7	brain	brain	NOUN
app01-4029	24	8	project[1	project[1	NOUN
app01-4029	24	9	,	,	PUNCT
app01-4029	24	10	2	2	NUM
app01-4029	24	11	]	]	PUNCT
app01-4029	24	12	with	with	ADP
app01-4029	24	13	the	the	DET
app01-4029	24	14	goal	goal	NOUN
app01-4029	24	15	to	to	PART
app01-4029	24	16	simulate	simulate	VERB
app01-4029	24	17	the	the	DET
app01-4029	24	18	whole	whole	ADJ
app01-4029	24	19	brain	brain	NOUN
app01-4029	24	20	.	.	PUNCT
app01-4029	25	1	this	this	DET
app01-4029	25	2	model	model	NOUN
app01-4029	25	3	should	should	AUX
app01-4029	25	4	be	be	AUX
app01-4029	25	5	so	so	ADV
app01-4029	25	6	detailed	detailed	ADJ
app01-4029	25	7	that	that	SCONJ
app01-4029	25	8	every	every	DET
app01-4029	25	9	cell	cell	NOUN
app01-4029	25	10	is	be	AUX
app01-4029	25	11	depicted	depict	VERB
app01-4029	25	12	on	on	ADP
app01-4029	25	13	a	a	DET
app01-4029	25	14	molecular	molecular	ADJ
app01-4029	25	15	level	level	NOUN
app01-4029	25	16	.	.	PUNCT
app01-4029	26	1	according	accord	VERB
app01-4029	26	2	to	to	ADP
app01-4029	26	3	the	the	DET
app01-4029	26	4	authors	author	NOUN
app01-4029	26	5	,	,	PUNCT
app01-4029	26	6	processes	process	NOUN
app01-4029	26	7	like	like	ADP
app01-4029	26	8	consciousness	consciousness	NOUN
app01-4029	26	9	,	,	PUNCT
app01-4029	26	10	creativity	creativity	NOUN
app01-4029	26	11	,	,	PUNCT
app01-4029	26	12	emotions	emotion	NOUN
app01-4029	26	13	or	or	CCONJ
app01-4029	26	14	aggression	aggression	NOUN
app01-4029	26	15	will	will	AUX
app01-4029	26	16	emerge	emerge	VERB
app01-4029	26	17	.	.	PUNCT
app01-4029	27	1	another	another	DET
app01-4029	27	2	research	research	NOUN
app01-4029	27	3	aimed	aim	VERB
app01-4029	27	4	at	at	ADP
app01-4029	27	5	the	the	DET
app01-4029	27	6	models	model	NOUN
app01-4029	27	7	of	of	ADP
app01-4029	27	8	human	human	ADJ
app01-4029	27	9	mind	mind	NOUN
app01-4029	27	10	is	be	AUX
app01-4029	27	11	the	the	DET
app01-4029	27	12	darpa	darpa	PROPN
app01-4029	27	13	synapse	synapse	NOUN
app01-4029	27	14	project	project	NOUN
app01-4029	27	15	with	with	ADP
app01-4029	27	16	opposite	opposite	ADJ
app01-4029	27	17	attitude	attitude	NOUN
app01-4029	27	18	.	.	PUNCT
app01-4029	28	1	the	the	DET
app01-4029	28	2	idea	idea	NOUN
app01-4029	28	3	behind	behind	ADP
app01-4029	28	4	this	this	DET
app01-4029	28	5	research	research	NOUN
app01-4029	28	6	is	be	AUX
app01-4029	28	7	to	to	PART
app01-4029	28	8	create	create	VERB
app01-4029	28	9	a	a	DET
app01-4029	28	10	neural	neural	ADJ
app01-4029	28	11	network	network	NOUN
app01-4029	28	12	with	with	ADP
app01-4029	28	13	architecture	architecture	NOUN
app01-4029	28	14	similar	similar	ADJ
app01-4029	28	15	to	to	ADP
app01-4029	28	16	biological	biological	ADJ
app01-4029	28	17	neural	neural	ADJ
app01-4029	28	18	network	network	NOUN
app01-4029	28	19	,	,	PUNCT
app01-4029	28	20	however	however	ADV
app01-4029	28	21	with	with	ADP
app01-4029	28	22	strongly	strongly	ADV
app01-4029	28	23	simplified	simplified	ADJ
app01-4029	28	24	neurons[3	neurons[3	NOUN
app01-4029	28	25	]	]	PUNCT
app01-4029	28	26	.	.	PUNCT
app01-4029	29	1	the	the	DET
app01-4029	29	2	expectation	expectation	NOUN
app01-4029	29	3	is	be	AUX
app01-4029	29	4	not	not	PART
app01-4029	29	5	to	to	PART
app01-4029	29	6	model	model	VERB
app01-4029	29	7	mental	mental	ADJ
app01-4029	29	8	processes	process	NOUN
app01-4029	29	9	,	,	PUNCT
app01-4029	29	10	but	but	CCONJ
app01-4029	29	11	to	to	PART
app01-4029	29	12	use	use	VERB
app01-4029	29	13	the	the	DET
app01-4029	29	14	principles	principle	NOUN
app01-4029	29	15	of	of	ADP
app01-4029	29	16	biological	biological	ADJ
app01-4029	29	17	neural	neural	ADJ
app01-4029	29	18	network	network	NOUN
app01-4029	29	19	to	to	PART
app01-4029	29	20	improve	improve	VERB
app01-4029	29	21	the	the	DET
app01-4029	29	22	computer	computer	NOUN
app01-4029	29	23	architecture	architecture	NOUN
app01-4029	29	24	.	.	PUNCT
app01-4029	30	1	the	the	DET
app01-4029	30	2	way	way	NOUN
app01-4029	30	3	of	of	ADP
app01-4029	30	4	information	information	NOUN
app01-4029	30	5	processing	processing	NOUN
app01-4029	30	6	in	in	ADP
app01-4029	30	7	the	the	DET
app01-4029	30	8	computer	computer	NOUN
app01-4029	30	9	architecture	architecture	NOUN
app01-4029	30	10	is	be	AUX
app01-4029	30	11	different	different	ADJ
app01-4029	30	12	from	from	ADP
app01-4029	30	13	biological	biological	ADJ
app01-4029	30	14	networks	network	NOUN
app01-4029	30	15	.	.	PUNCT
app01-4029	31	1	in	in	ADP
app01-4029	31	2	brain	brain	NOUN
app01-4029	31	3	,	,	PUNCT
app01-4029	31	4	the	the	DET
app01-4029	31	5	memory	memory	NOUN
app01-4029	31	6	and	and	CCONJ
app01-4029	31	7	computation	computation	NOUN
app01-4029	31	8	are	be	AUX
app01-4029	31	9	distributed	distribute	VERB
app01-4029	31	10	;	;	PUNCT
app01-4029	31	11	there	there	PRON
app01-4029	31	12	is	be	VERB
app01-4029	31	13	no	no	DET
app01-4029	31	14	central	central	ADJ
app01-4029	31	15	processor	processor	NOUN
app01-4029	31	16	or	or	CCONJ
app01-4029	31	17	memory	memory	NOUN
app01-4029	31	18	.	.	PUNCT
app01-4029	32	1	the	the	DET
app01-4029	32	2	expectation	expectation	NOUN
app01-4029	32	3	of	of	ADP
app01-4029	32	4	synapse	synapse	NOUN
app01-4029	32	5	project	project	NOUN
app01-4029	32	6	is	be	AUX
app01-4029	32	7	to	to	PART
app01-4029	32	8	understand	understand	VERB
app01-4029	32	9	the	the	DET
app01-4029	32	10	advantages	advantage	NOUN
app01-4029	32	11	of	of	ADP
app01-4029	32	12	this	this	DET
app01-4029	32	13	architecture	architecture	NOUN
app01-4029	32	14	and	and	CCONJ
app01-4029	32	15	to	to	PART
app01-4029	32	16	use	use	VERB
app01-4029	32	17	them	they	PRON
app01-4029	32	18	in	in	ADP
app01-4029	32	19	formation	formation	NOUN
app01-4029	32	20	of	of	ADP
app01-4029	32	21	novel	novel	ADJ
app01-4029	32	22	computer	computer	NOUN
app01-4029	32	23	architecture	architecture	NOUN
app01-4029	32	24	.	.	PUNCT
app01-4029	33	1	with	with	ADP
app01-4029	33	2	respect	respect	NOUN
app01-4029	33	3	to	to	ADP
app01-4029	33	4	both	both	PRON
app01-4029	33	5	above	above	ADP
app01-4029	33	6	mentioned	mention	VERB
app01-4029	33	7	researches	research	NOUN
app01-4029	33	8	,	,	PUNCT
app01-4029	33	9	the	the	DET
app01-4029	33	10	target	target	NOUN
app01-4029	33	11	of	of	ADP
app01-4029	33	12	this	this	DET
app01-4029	33	13	paper	paper	NOUN
app01-4029	33	14	is	be	AUX
app01-4029	33	15	to	to	PART
app01-4029	33	16	find	find	VERB
app01-4029	33	17	such	such	DET
app01-4029	33	18	an	an	DET
app01-4029	33	19	equilibrium	equilibrium	NOUN
app01-4029	33	20	point	point	NOUN
app01-4029	33	21	where	where	SCONJ
app01-4029	33	22	the	the	DET
app01-4029	33	23	model	model	NOUN
app01-4029	33	24	of	of	ADP
app01-4029	33	25	the	the	DET
app01-4029	33	26	neuron	neuron	NOUN
app01-4029	33	27	is	be	AUX
app01-4029	33	28	still	still	ADV
app01-4029	33	29	faithful	faithful	ADJ
app01-4029	33	30	enough	enough	ADV
app01-4029	33	31	so	so	SCONJ
app01-4029	33	32	that	that	SCONJ
app01-4029	33	33	it	it	PRON
app01-4029	33	34	can	can	AUX
app01-4029	33	35	model	model	VERB
app01-4029	33	36	the	the	DET
app01-4029	33	37	strong	strong	ADJ
app01-4029	33	38	processes	process	NOUN
app01-4029	33	39	and	and	CCONJ
app01-4029	33	40	99	99	NUM
app01-4029	33	41	http://dx.doi.org/10.14311/app.2017.12.0099	http://dx.doi.org/10.14311/app.2017.12.0099	PROPN
app01-4029	33	42	http://ojs.cvut.cz/ojs/index.php/app	http://ojs.cvut.cz/ojs/index.php/app	NOUN
app01-4029	33	43	martin	martin	PROPN
app01-4029	33	44	růžek	růžek	PROPN
app01-4029	33	45	acta	acta	PROPN
app01-4029	33	46	polytechnica	polytechnica	PROPN
app01-4029	33	47	ctu	ctu	NOUN
app01-4029	33	48	proceedings	proceeding	NOUN
app01-4029	33	49	yet	yet	ADV
app01-4029	33	50	be	be	AUX
app01-4029	33	51	simple	simple	ADJ
app01-4029	33	52	enough	enough	ADV
app01-4029	33	53	to	to	PART
app01-4029	33	54	be	be	AUX
app01-4029	33	55	practically	practically	ADV
app01-4029	33	56	realizable	realizable	ADJ
app01-4029	33	57	.	.	PUNCT
app01-4029	34	1	2	2	X
app01-4029	34	2	.	.	X
app01-4029	34	3	new	new	ADJ
app01-4029	34	4	solution	solution	NOUN
app01-4029	34	5	–	–	PUNCT
app01-4029	34	6	homeostatical	homeostatical	ADJ
app01-4029	34	7	neural	neural	ADJ
app01-4029	34	8	network	network	NOUN
app01-4029	34	9	the	the	DET
app01-4029	34	10	need	need	NOUN
app01-4029	34	11	for	for	ADP
app01-4029	34	12	a	a	DET
app01-4029	34	13	compromise	compromise	NOUN
app01-4029	34	14	between	between	ADP
app01-4029	34	15	the	the	DET
app01-4029	34	16	complexity	complexity	NOUN
app01-4029	34	17	of	of	ADP
app01-4029	34	18	biological	biological	ADJ
app01-4029	34	19	neural	neural	ADJ
app01-4029	34	20	network	network	NOUN
app01-4029	34	21	and	and	CCONJ
app01-4029	34	22	the	the	DET
app01-4029	34	23	practical	practical	ADJ
app01-4029	34	24	feasibility	feasibility	NOUN
app01-4029	34	25	of	of	ADP
app01-4029	34	26	the	the	DET
app01-4029	34	27	artificial	artificial	ADJ
app01-4029	34	28	network	network	NOUN
app01-4029	34	29	led	lead	VERB
app01-4029	34	30	to	to	ADP
app01-4029	34	31	a	a	DET
app01-4029	34	32	proposal	proposal	NOUN
app01-4029	34	33	of	of	ADP
app01-4029	34	34	new	new	ADJ
app01-4029	34	35	learning	learning	NOUN
app01-4029	34	36	algorithm	algorithm	NOUN
app01-4029	34	37	.	.	PUNCT
app01-4029	35	1	the	the	DET
app01-4029	35	2	idea	idea	NOUN
app01-4029	35	3	is	be	AUX
app01-4029	35	4	based	base	VERB
app01-4029	35	5	on	on	ADP
app01-4029	35	6	the	the	DET
app01-4029	35	7	classical	classical	ADJ
app01-4029	35	8	multilayered	multilayere	VERB
app01-4029	35	9	neural	neural	ADJ
app01-4029	35	10	network	network	NOUN
app01-4029	35	11	(	(	PUNCT
app01-4029	35	12	mlp	mlp	PROPN
app01-4029	35	13	)	)	PUNCT
app01-4029	35	14	,	,	PUNCT
app01-4029	35	15	the	the	DET
app01-4029	35	16	difference	difference	NOUN
app01-4029	35	17	is	be	AUX
app01-4029	35	18	in	in	ADP
app01-4029	35	19	the	the	DET
app01-4029	35	20	learning	learning	NOUN
app01-4029	35	21	process	process	NOUN
app01-4029	35	22	.	.	PUNCT
app01-4029	36	1	the	the	DET
app01-4029	36	2	neurons	neuron	NOUN
app01-4029	36	3	are	be	AUX
app01-4029	36	4	updating	update	VERB
app01-4029	36	5	their	their	PRON
app01-4029	36	6	parameters	parameter	NOUN
app01-4029	36	7	in	in	ADP
app01-4029	36	8	a	a	DET
app01-4029	36	9	way	way	NOUN
app01-4029	36	10	that	that	PRON
app01-4029	36	11	is	be	AUX
app01-4029	36	12	similar	similar	ADJ
app01-4029	36	13	to	to	ADP
app01-4029	36	14	the	the	DET
app01-4029	36	15	real	real	ADJ
app01-4029	36	16	biological	biological	ADJ
app01-4029	36	17	processes	process	NOUN
app01-4029	36	18	.	.	PUNCT
app01-4029	37	1	the	the	DET
app01-4029	37	2	basic	basic	ADJ
app01-4029	37	3	idea	idea	NOUN
app01-4029	37	4	is	be	AUX
app01-4029	37	5	that	that	SCONJ
app01-4029	37	6	the	the	DET
app01-4029	37	7	neurons	neuron	NOUN
app01-4029	37	8	are	be	AUX
app01-4029	37	9	in	in	ADP
app01-4029	37	10	competition	competition	NOUN
app01-4029	37	11	for	for	ADP
app01-4029	37	12	resources	resource	NOUN
app01-4029	37	13	and	and	CCONJ
app01-4029	37	14	the	the	DET
app01-4029	37	15	survival	survival	NOUN
app01-4029	37	16	criterion	criterion	NOUN
app01-4029	37	17	is	be	AUX
app01-4029	37	18	the	the	DET
app01-4029	37	19	usefulness	usefulness	NOUN
app01-4029	37	20	of	of	ADP
app01-4029	37	21	the	the	DET
app01-4029	37	22	neuron	neuron	NOUN
app01-4029	37	23	to	to	ADP
app01-4029	37	24	the	the	DET
app01-4029	37	25	whole	whole	ADJ
app01-4029	37	26	neural	neural	ADJ
app01-4029	37	27	network	network	NOUN
app01-4029	37	28	.	.	PUNCT
app01-4029	38	1	the	the	DET
app01-4029	38	2	neurons	neuron	NOUN
app01-4029	38	3	are	be	AUX
app01-4029	38	4	not	not	PART
app01-4029	38	5	using	use	VERB
app01-4029	38	6	any	any	DET
app01-4029	38	7	"	"	PUNCT
app01-4029	38	8	teacher	teacher	NOUN
app01-4029	38	9	"	"	PUNCT
app01-4029	38	10	or	or	CCONJ
app01-4029	38	11	other	other	ADJ
app01-4029	38	12	kind	kind	NOUN
app01-4029	38	13	of	of	ADP
app01-4029	38	14	superior	superior	ADJ
app01-4029	38	15	system	system	NOUN
app01-4029	38	16	,	,	PUNCT
app01-4029	38	17	they	they	PRON
app01-4029	38	18	have	have	VERB
app01-4029	38	19	the	the	DET
app01-4029	38	20	same	same	ADJ
app01-4029	38	21	information	information	NOUN
app01-4029	38	22	as	as	ADP
app01-4029	38	23	the	the	DET
app01-4029	38	24	biological	biological	ADJ
app01-4029	38	25	neuron	neuron	NOUN
app01-4029	38	26	.	.	PUNCT
app01-4029	39	1	the	the	DET
app01-4029	39	2	learning	learning	NOUN
app01-4029	39	3	process	process	NOUN
app01-4029	39	4	can	can	AUX
app01-4029	39	5	be	be	AUX
app01-4029	39	6	seen	see	VERB
app01-4029	39	7	as	as	ADP
app01-4029	39	8	searching	search	VERB
app01-4029	39	9	of	of	ADP
app01-4029	39	10	some	some	DET
app01-4029	39	11	equilibrium	equilibrium	NOUN
app01-4029	39	12	position	position	NOUN
app01-4029	39	13	which	which	PRON
app01-4029	39	14	represents	represent	VERB
app01-4029	39	15	a	a	DET
app01-4029	39	16	state	state	NOUN
app01-4029	39	17	where	where	SCONJ
app01-4029	39	18	the	the	DET
app01-4029	39	19	importance	importance	NOUN
app01-4029	39	20	of	of	ADP
app01-4029	39	21	the	the	DET
app01-4029	39	22	neuron	neuron	NOUN
app01-4029	39	23	for	for	ADP
app01-4029	39	24	the	the	DET
app01-4029	39	25	neural	neural	ADJ
app01-4029	39	26	network	network	NOUN
app01-4029	39	27	is	be	AUX
app01-4029	39	28	maximal	maximal	ADJ
app01-4029	39	29	.	.	PUNCT
app01-4029	40	1	this	this	DET
app01-4029	40	2	position	position	NOUN
app01-4029	40	3	can	can	AUX
app01-4029	40	4	change	change	VERB
app01-4029	40	5	in	in	ADP
app01-4029	40	6	time	time	NOUN
app01-4029	40	7	if	if	SCONJ
app01-4029	40	8	the	the	DET
app01-4029	40	9	environment	environment	NOUN
app01-4029	40	10	changes	change	VERB
app01-4029	40	11	.	.	PUNCT
app01-4029	41	1	the	the	DET
app01-4029	41	2	name	name	NOUN
app01-4029	41	3	of	of	ADP
app01-4029	41	4	this	this	DET
app01-4029	41	5	type	type	NOUN
app01-4029	41	6	of	of	ADP
app01-4029	41	7	learning	learning	NOUN
app01-4029	41	8	,	,	PUNCT
app01-4029	41	9	the	the	DET
app01-4029	41	10	homeostatic	homeostatic	ADJ
app01-4029	41	11	artificial	artificial	ADJ
app01-4029	41	12	neural	neural	ADJ
app01-4029	41	13	network	network	NOUN
app01-4029	41	14	,	,	PUNCT
app01-4029	41	15	is	be	AUX
app01-4029	41	16	derived	derive	VERB
app01-4029	41	17	from	from	ADP
app01-4029	41	18	the	the	DET
app01-4029	41	19	similarity	similarity	NOUN
app01-4029	41	20	of	of	ADP
app01-4029	41	21	this	this	DET
app01-4029	41	22	idea	idea	NOUN
app01-4029	41	23	to	to	ADP
app01-4029	41	24	the	the	DET
app01-4029	41	25	process	process	NOUN
app01-4029	41	26	of	of	ADP
app01-4029	41	27	homeostasis	homeostasis	NOUN
app01-4029	41	28	that	that	PRON
app01-4029	41	29	is	be	AUX
app01-4029	41	30	known	know	VERB
app01-4029	41	31	from	from	ADP
app01-4029	41	32	biology	biology	NOUN
app01-4029	41	33	.	.	PUNCT
app01-4029	42	1	the	the	DET
app01-4029	42	2	proposed	propose	VERB
app01-4029	42	3	neural	neural	ADJ
app01-4029	42	4	network	network	NOUN
app01-4029	42	5	is	be	AUX
app01-4029	42	6	based	base	VERB
app01-4029	42	7	on	on	ADP
app01-4029	42	8	the	the	DET
app01-4029	42	9	idea	idea	NOUN
app01-4029	42	10	of	of	ADP
app01-4029	42	11	mcculloch	mcculloch	NOUN
app01-4029	42	12	-	-	PUNCT
app01-4029	42	13	pitts	pitts	PROPN
app01-4029	42	14	neuron	neuron	NOUN
app01-4029	42	15	:	:	PUNCT
app01-4029	42	16	y	y	PROPN
app01-4029	42	17	=	=	PUNCT
app01-4029	42	18	φf	φf	PROPN
app01-4029	42	19	n∑	n∑	PROPN
app01-4029	42	20	i=0	i=0	PROPN
app01-4029	42	21	xiwi	xiwi	X
app01-4029	42	22	(	(	PUNCT
app01-4029	42	23	1	1	X
app01-4029	42	24	)	)	PUNCT
app01-4029	42	25	where	where	SCONJ
app01-4029	42	26	f	f	PROPN
app01-4029	42	27	is	be	AUX
app01-4029	42	28	the	the	DET
app01-4029	42	29	transfer	transfer	NOUN
app01-4029	42	30	function	function	NOUN
app01-4029	42	31	.	.	PUNCT
app01-4029	43	1	the	the	DET
app01-4029	43	2	sigmoid	sigmoid	NOUN
app01-4029	43	3	transfer	transfer	NOUN
app01-4029	43	4	function	function	NOUN
app01-4029	43	5	was	be	AUX
app01-4029	43	6	used	use	VERB
app01-4029	43	7	:	:	PUNCT
app01-4029	43	8	f(x	f(x	PROPN
app01-4029	43	9	)	)	PUNCT
app01-4029	44	1	=	=	SYM
app01-4029	44	2	2	2	NUM
app01-4029	44	3	(	(	PUNCT
app01-4029	44	4	1	1	NUM
app01-4029	44	5	+	+	CCONJ
app01-4029	44	6	e−α∗x)−	e−α∗x)−	PROPN
app01-4029	44	7	1	1	NUM
app01-4029	44	8	(	(	PUNCT
app01-4029	44	9	2	2	NUM
app01-4029	44	10	)	)	PUNCT
app01-4029	44	11	as	as	SCONJ
app01-4029	44	12	the	the	DET
app01-4029	44	13	similarity	similarity	NOUN
app01-4029	44	14	to	to	ADP
app01-4029	44	15	biological	biological	ADJ
app01-4029	44	16	neuron	neuron	NOUN
app01-4029	44	17	was	be	AUX
app01-4029	44	18	the	the	DET
app01-4029	44	19	basic	basic	ADJ
app01-4029	44	20	requirement	requirement	NOUN
app01-4029	44	21	,	,	PUNCT
app01-4029	44	22	the	the	DET
app01-4029	44	23	back	back	ADJ
app01-4029	44	24	propagation	propagation	NOUN
app01-4029	44	25	algorithm	algorithm	NOUN
app01-4029	44	26	is	be	AUX
app01-4029	44	27	not	not	PART
app01-4029	44	28	a	a	DET
app01-4029	44	29	solution	solution	NOUN
app01-4029	44	30	because	because	SCONJ
app01-4029	44	31	a	a	DET
app01-4029	44	32	higher	high	ADJ
app01-4029	44	33	structure	structure	NOUN
app01-4029	44	34	(	(	PUNCT
app01-4029	44	35	or	or	CCONJ
app01-4029	44	36	teacher	teacher	NOUN
app01-4029	44	37	)	)	PUNCT
app01-4029	44	38	is	be	AUX
app01-4029	44	39	used	use	VERB
app01-4029	44	40	to	to	PART
app01-4029	44	41	train	train	VERB
app01-4029	44	42	the	the	DET
app01-4029	44	43	neuron	neuron	NOUN
app01-4029	44	44	.	.	PUNCT
app01-4029	45	1	in	in	ADP
app01-4029	45	2	the	the	DET
app01-4029	45	3	so	so	ADV
app01-4029	45	4	called	call	VERB
app01-4029	45	5	homeostatic	homeostatic	ADJ
app01-4029	45	6	neuron	neuron	NOUN
app01-4029	45	7	,	,	PUNCT
app01-4029	45	8	the	the	DET
app01-4029	45	9	unit	unit	NOUN
app01-4029	45	10	is	be	AUX
app01-4029	45	11	using	use	VERB
app01-4029	45	12	its	its	PRON
app01-4029	45	13	proper	proper	ADJ
app01-4029	45	14	forward	forward	ADJ
app01-4029	45	15	connection	connection	NOUN
app01-4029	45	16	to	to	PART
app01-4029	45	17	improve	improve	VERB
app01-4029	45	18	its	its	PRON
app01-4029	45	19	function	function	NOUN
app01-4029	45	20	.	.	PUNCT
app01-4029	46	1	the	the	DET
app01-4029	46	2	’	'	PUNCT
app01-4029	46	3	axon	axon	NOUN
app01-4029	46	4	’	'	PUNCT
app01-4029	46	5	in	in	ADP
app01-4029	46	6	this	this	DET
app01-4029	46	7	model	model	NOUN
app01-4029	46	8	has	have	VERB
app01-4029	46	9	two	two	NUM
app01-4029	46	10	functions	function	NOUN
app01-4029	46	11	–	–	PUNCT
app01-4029	46	12	the	the	DET
app01-4029	46	13	first	first	ADJ
app01-4029	46	14	one	one	NOUN
app01-4029	46	15	is	be	AUX
app01-4029	46	16	the	the	DET
app01-4029	46	17	transmission	transmission	NOUN
app01-4029	46	18	of	of	ADP
app01-4029	46	19	the	the	DET
app01-4029	46	20	output	output	NOUN
app01-4029	46	21	to	to	ADP
app01-4029	46	22	higher	high	ADJ
app01-4029	46	23	layer	layer	NOUN
app01-4029	46	24	(	(	PUNCT
app01-4029	46	25	as	as	ADP
app01-4029	46	26	in	in	ADP
app01-4029	46	27	back	back	ADJ
app01-4029	46	28	propagation	propagation	NOUN
app01-4029	46	29	)	)	PUNCT
app01-4029	46	30	,	,	PUNCT
app01-4029	46	31	the	the	DET
app01-4029	46	32	second	second	NOUN
app01-4029	46	33	is	be	AUX
app01-4029	46	34	the	the	DET
app01-4029	46	35	transmission	transmission	NOUN
app01-4029	46	36	of	of	ADP
app01-4029	46	37	the	the	DET
app01-4029	46	38	utility	utility	NOUN
app01-4029	46	39	information	information	NOUN
app01-4029	46	40	from	from	ADP
app01-4029	46	41	higher	high	ADJ
app01-4029	46	42	layer	layer	NOUN
app01-4029	46	43	to	to	ADP
app01-4029	46	44	the	the	DET
app01-4029	46	45	lower	low	ADJ
app01-4029	46	46	one	one	NUM
app01-4029	46	47	.	.	PUNCT
app01-4029	47	1	the	the	DET
app01-4029	47	2	idea	idea	NOUN
app01-4029	47	3	of	of	ADP
app01-4029	47	4	this	this	DET
app01-4029	47	5	type	type	NOUN
app01-4029	47	6	of	of	ADP
app01-4029	47	7	training	training	NOUN
app01-4029	47	8	is	be	AUX
app01-4029	47	9	that	that	SCONJ
app01-4029	47	10	the	the	DET
app01-4029	47	11	neuron	neuron	NOUN
app01-4029	47	12	improves	improve	VERB
app01-4029	47	13	its	its	PRON
app01-4029	47	14	relative	relative	ADJ
app01-4029	47	15	importance	importance	NOUN
app01-4029	47	16	in	in	ADP
app01-4029	47	17	the	the	DET
app01-4029	47	18	network	network	NOUN
app01-4029	47	19	,	,	PUNCT
app01-4029	47	20	in	in	ADP
app01-4029	47	21	other	other	ADJ
app01-4029	47	22	words	word	NOUN
app01-4029	47	23	,	,	PUNCT
app01-4029	47	24	it	it	PRON
app01-4029	47	25	is	be	AUX
app01-4029	47	26	trying	try	VERB
app01-4029	47	27	to	to	PART
app01-4029	47	28	maximize	maximize	VERB
app01-4029	47	29	the	the	DET
app01-4029	47	30	part	part	NOUN
app01-4029	47	31	of	of	ADP
app01-4029	47	32	its	its	PRON
app01-4029	47	33	output	output	NOUN
app01-4029	47	34	signal	signal	NOUN
app01-4029	47	35	that	that	PRON
app01-4029	47	36	is	be	AUX
app01-4029	47	37	accepted	accept	VERB
app01-4029	47	38	by	by	ADP
app01-4029	47	39	other	other	ADJ
app01-4029	47	40	neurons	neuron	NOUN
app01-4029	47	41	.	.	PUNCT
app01-4029	48	1	this	this	DET
app01-4029	48	2	idea	idea	NOUN
app01-4029	48	3	corresponds	correspond	VERB
app01-4029	48	4	to	to	ADP
app01-4029	48	5	the	the	DET
app01-4029	48	6	biological	biological	ADJ
app01-4029	48	7	reality	reality	NOUN
app01-4029	48	8	because	because	SCONJ
app01-4029	48	9	the	the	DET
app01-4029	48	10	information	information	NOUN
app01-4029	48	11	transmitted	transmit	VERB
app01-4029	48	12	by	by	ADP
app01-4029	48	13	the	the	DET
app01-4029	48	14	axon	axon	NOUN
app01-4029	48	15	has	have	VERB
app01-4029	48	16	the	the	DET
app01-4029	48	17	form	form	NOUN
app01-4029	48	18	of	of	ADP
app01-4029	48	19	energy	energy	NOUN
app01-4029	48	20	(	(	PUNCT
app01-4029	48	21	and	and	CCONJ
app01-4029	48	22	is	be	AUX
app01-4029	48	23	inseparable	inseparable	ADJ
app01-4029	48	24	from	from	ADP
app01-4029	48	25	energy	energy	NOUN
app01-4029	48	26	)	)	PUNCT
app01-4029	48	27	.	.	PUNCT
app01-4029	49	1	therefore	therefore	ADV
app01-4029	49	2	,	,	PUNCT
app01-4029	49	3	the	the	DET
app01-4029	49	4	neuron	neuron	NOUN
app01-4029	49	5	knows	know	VERB
app01-4029	49	6	which	which	DET
app01-4029	49	7	part	part	NOUN
app01-4029	49	8	of	of	ADP
app01-4029	49	9	its	its	PRON
app01-4029	49	10	output	output	NOUN
app01-4029	49	11	energy	energy	NOUN
app01-4029	49	12	was	be	AUX
app01-4029	49	13	accepted	accept	VERB
app01-4029	49	14	by	by	ADP
app01-4029	49	15	other	other	ADJ
app01-4029	49	16	neurons	neuron	NOUN
app01-4029	49	17	.	.	PUNCT
app01-4029	50	1	the	the	DET
app01-4029	50	2	process	process	NOUN
app01-4029	50	3	of	of	ADP
app01-4029	50	4	learning	learning	NOUN
app01-4029	50	5	can	can	AUX
app01-4029	50	6	be	be	AUX
app01-4029	50	7	described	describe	VERB
app01-4029	50	8	by	by	ADP
app01-4029	50	9	the	the	DET
app01-4029	50	10	following	following	ADJ
app01-4029	50	11	algorithm	algorithm	NOUN
app01-4029	50	12	:	:	PUNCT
app01-4029	50	13	first	first	ADV
app01-4029	50	14	,	,	PUNCT
app01-4029	50	15	the	the	DET
app01-4029	50	16	neuron	neuron	NOUN
app01-4029	50	17	computes	compute	VERB
app01-4029	50	18	its	its	PRON
app01-4029	50	19	output	output	NOUN
app01-4029	50	20	with	with	ADP
app01-4029	50	21	its	its	PRON
app01-4029	50	22	initial	initial	ADJ
app01-4029	50	23	random	random	ADJ
app01-4029	50	24	weight	weight	NOUN
app01-4029	50	25	.	.	PUNCT
app01-4029	51	1	then	then	ADV
app01-4029	51	2	the	the	DET
app01-4029	51	3	neurons	neuron	NOUN
app01-4029	51	4	in	in	ADP
app01-4029	51	5	the	the	DET
app01-4029	51	6	higher	high	ADJ
app01-4029	51	7	layer	layer	NOUN
app01-4029	51	8	set	set	VERB
app01-4029	51	9	their	their	PRON
app01-4029	51	10	weights	weight	NOUN
app01-4029	51	11	according	accord	VERB
app01-4029	51	12	to	to	ADP
app01-4029	51	13	their	their	PRON
app01-4029	51	14	level	level	NOUN
app01-4029	51	15	of	of	ADP
app01-4029	51	16	contentment	contentment	NOUN
app01-4029	51	17	with	with	ADP
app01-4029	51	18	the	the	DET
app01-4029	51	19	reference	reference	NOUN
app01-4029	51	20	neuron	neuron	NOUN
app01-4029	51	21	.	.	PUNCT
app01-4029	52	1	in	in	ADP
app01-4029	52	2	the	the	DET
app01-4029	52	3	next	next	ADJ
app01-4029	52	4	step	step	NOUN
app01-4029	52	5	,	,	PUNCT
app01-4029	52	6	the	the	DET
app01-4029	52	7	neuron	neuron	NOUN
app01-4029	52	8	changes	change	VERB
app01-4029	52	9	its	its	PRON
app01-4029	52	10	weights	weight	NOUN
app01-4029	52	11	accordingly	accordingly	ADV
app01-4029	52	12	.	.	PUNCT
app01-4029	53	1	several	several	ADJ
app01-4029	53	2	possibilities	possibility	NOUN
app01-4029	53	3	of	of	ADP
app01-4029	53	4	the	the	DET
app01-4029	53	5	weight	weight	NOUN
app01-4029	53	6	change	change	NOUN
app01-4029	53	7	are	be	AUX
app01-4029	53	8	described	describe	VERB
app01-4029	53	9	later	later	ADV
app01-4029	53	10	in	in	ADP
app01-4029	53	11	this	this	DET
app01-4029	53	12	paper	paper	NOUN
app01-4029	53	13	.	.	PUNCT
app01-4029	54	1	then	then	ADV
app01-4029	54	2	the	the	DET
app01-4029	54	3	new	new	ADJ
app01-4029	54	4	output	output	NOUN
app01-4029	54	5	is	be	AUX
app01-4029	54	6	computed	compute	VERB
app01-4029	54	7	.	.	PUNCT
app01-4029	55	1	the	the	DET
app01-4029	55	2	neurons	neuron	NOUN
app01-4029	55	3	in	in	ADP
app01-4029	55	4	the	the	DET
app01-4029	55	5	higher	high	ADJ
app01-4029	55	6	layer	layer	NOUN
app01-4029	55	7	read	read	VERB
app01-4029	55	8	the	the	DET
app01-4029	55	9	output	output	NOUN
app01-4029	55	10	and	and	CCONJ
app01-4029	55	11	re	re	NOUN
app01-4029	55	12	-	-	VERB
app01-4029	55	13	calculate	calculate	VERB
app01-4029	55	14	their	their	PRON
app01-4029	55	15	inputs	input	NOUN
app01-4029	55	16	weights	weight	NOUN
app01-4029	55	17	.	.	PUNCT
app01-4029	56	1	the	the	DET
app01-4029	56	2	reference	reference	NOUN
app01-4029	56	3	neuron	neuron	NOUN
app01-4029	56	4	then	then	ADV
app01-4029	56	5	decides	decide	VERB
app01-4029	56	6	which	which	DET
app01-4029	56	7	setting	set	VERB
app01-4029	56	8	was	be	AUX
app01-4029	56	9	better	well	ADJ
app01-4029	56	10	.	.	PUNCT
app01-4029	57	1	this	this	DET
app01-4029	57	2	algorithm	algorithm	NOUN
app01-4029	57	3	has	have	VERB
app01-4029	57	4	several	several	ADJ
app01-4029	57	5	variants	variant	NOUN
app01-4029	57	6	,	,	PUNCT
app01-4029	57	7	all	all	PRON
app01-4029	57	8	of	of	ADP
app01-4029	57	9	them	they	PRON
app01-4029	57	10	are	be	AUX
app01-4029	57	11	using	use	VERB
app01-4029	57	12	at	at	ADV
app01-4029	57	13	least	least	ADV
app01-4029	57	14	2	2	NUM
app01-4029	57	15	successive	successive	ADJ
app01-4029	57	16	values	value	NOUN
app01-4029	57	17	of	of	ADP
app01-4029	57	18	the	the	DET
app01-4029	57	19	level	level	NOUN
app01-4029	57	20	of	of	ADP
app01-4029	57	21	acceptance	acceptance	NOUN
app01-4029	57	22	.	.	PUNCT
app01-4029	58	1	this	this	PRON
app01-4029	58	2	implies	imply	VERB
app01-4029	58	3	that	that	SCONJ
app01-4029	58	4	the	the	DET
app01-4029	58	5	neuron	neuron	NOUN
app01-4029	58	6	must	must	AUX
app01-4029	58	7	be	be	AUX
app01-4029	58	8	equipped	equip	VERB
app01-4029	58	9	with	with	ADP
app01-4029	58	10	a	a	DET
app01-4029	58	11	memory	memory	NOUN
app01-4029	58	12	.	.	PUNCT
app01-4029	59	1	the	the	DET
app01-4029	59	2	process	process	NOUN
app01-4029	59	3	of	of	ADP
app01-4029	59	4	learning	learning	NOUN
app01-4029	59	5	is	be	AUX
app01-4029	59	6	on	on	ADP
app01-4029	59	7	figure	figure	NOUN
app01-4029	59	8	1	1	NUM
app01-4029	59	9	.	.	PUNCT
app01-4029	59	10	from	from	ADP
app01-4029	59	11	the	the	DET
app01-4029	59	12	point	point	NOUN
app01-4029	59	13	of	of	ADP
app01-4029	59	14	view	view	NOUN
app01-4029	59	15	of	of	ADP
app01-4029	59	16	the	the	DET
app01-4029	59	17	reference	reference	NOUN
app01-4029	59	18	neuron	neuron	NOUN
app01-4029	59	19	the	the	DET
app01-4029	59	20	learning	learning	NOUN
app01-4029	59	21	is	be	AUX
app01-4029	59	22	described	describe	VERB
app01-4029	59	23	by	by	ADP
app01-4029	59	24	the	the	DET
app01-4029	59	25	following	follow	VERB
app01-4029	59	26	algorithm	algorithm	NOUN
app01-4029	59	27	:	:	PUNCT
app01-4029	59	28	(	(	PUNCT
app01-4029	60	1	1	1	X
app01-4029	60	2	.	.	PUNCT
app01-4029	60	3	)	)	PUNCT
app01-4029	61	1	random	random	ADJ
app01-4029	61	2	initial	initial	ADJ
app01-4029	61	3	weights	weight	NOUN
app01-4029	61	4	(	(	PUNCT
app01-4029	61	5	2	2	NUM
app01-4029	61	6	.	.	PUNCT
app01-4029	61	7	)	)	PUNCT
app01-4029	61	8	output	output	NOUN
app01-4029	61	9	with	with	ADP
app01-4029	61	10	initial	initial	ADJ
app01-4029	61	11	weights	weight	NOUN
app01-4029	61	12	for	for	ADP
app01-4029	61	13	the	the	DET
app01-4029	61	14	first	first	ADJ
app01-4029	61	15	input	input	NOUN
app01-4029	61	16	(	(	PUNCT
app01-4029	61	17	3	3	NUM
app01-4029	61	18	.	.	PUNCT
app01-4029	61	19	)	)	PUNCT
app01-4029	61	20	neurons	neuron	NOUN
app01-4029	61	21	in	in	ADP
app01-4029	61	22	higher	high	ADJ
app01-4029	61	23	layer	layer	NOUN
app01-4029	61	24	(	(	PUNCT
app01-4029	61	25	output	output	NOUN
app01-4029	61	26	neurons	neuron	NOUN
app01-4029	61	27	)	)	PUNCT
app01-4029	61	28	compute	compute	VERB
app01-4029	61	29	the	the	DET
app01-4029	61	30	utility	utility	NOUN
app01-4029	61	31	of	of	ADP
app01-4029	61	32	the	the	DET
app01-4029	61	33	reference	reference	NOUN
app01-4029	61	34	neuron	neuron	NOUN
app01-4029	61	35	and	and	CCONJ
app01-4029	61	36	set	set	VERB
app01-4029	61	37	their	their	PRON
app01-4029	61	38	input	input	NOUN
app01-4029	61	39	weights	weight	NOUN
app01-4029	61	40	accordingly	accordingly	ADV
app01-4029	61	41	.	.	PUNCT
app01-4029	62	1	if	if	SCONJ
app01-4029	62	2	they	they	PRON
app01-4029	62	3	are	be	AUX
app01-4029	62	4	satisfied	satisfied	ADJ
app01-4029	62	5	with	with	ADP
app01-4029	62	6	the	the	DET
app01-4029	62	7	output	output	NOUN
app01-4029	62	8	of	of	ADP
app01-4029	62	9	the	the	DET
app01-4029	62	10	reference	reference	NOUN
app01-4029	62	11	neuron	neuron	NOUN
app01-4029	62	12	,	,	PUNCT
app01-4029	62	13	they	they	PRON
app01-4029	62	14	increase	increase	VERB
app01-4029	62	15	their	their	PRON
app01-4029	62	16	weights	weight	NOUN
app01-4029	62	17	,	,	PUNCT
app01-4029	62	18	otherwise	otherwise	ADV
app01-4029	62	19	they	they	PRON
app01-4029	62	20	decrease	decrease	VERB
app01-4029	62	21	them	they	PRON
app01-4029	62	22	.	.	PUNCT
app01-4029	63	1	there	there	PRON
app01-4029	63	2	are	be	VERB
app01-4029	63	3	several	several	ADJ
app01-4029	63	4	ways	way	NOUN
app01-4029	63	5	how	how	SCONJ
app01-4029	63	6	to	to	PART
app01-4029	63	7	compute	compute	VERB
app01-4029	63	8	the	the	DET
app01-4029	63	9	utility	utility	NOUN
app01-4029	63	10	,	,	PUNCT
app01-4029	63	11	some	some	PRON
app01-4029	63	12	of	of	ADP
app01-4029	63	13	them	they	PRON
app01-4029	63	14	are	be	AUX
app01-4029	63	15	described	describe	VERB
app01-4029	63	16	in	in	ADP
app01-4029	63	17	eq	eq	ADP
app01-4029	63	18	.	.	PROPN
app01-4029	63	19	3	3	NUM
app01-4029	63	20	6	6	NUM
app01-4029	63	21	.	.	PUNCT
app01-4029	64	1	(	(	PUNCT
app01-4029	64	2	4	4	NUM
app01-4029	64	3	.	.	PUNCT
app01-4029	64	4	)	)	PUNCT
app01-4029	65	1	the	the	DET
app01-4029	65	2	reference	reference	NOUN
app01-4029	65	3	neuron	neuron	NOUN
app01-4029	65	4	changes	change	VERB
app01-4029	65	5	one	one	NUM
app01-4029	65	6	(	(	PUNCT
app01-4029	65	7	or	or	CCONJ
app01-4029	65	8	more	more	ADJ
app01-4029	65	9	)	)	PUNCT
app01-4029	65	10	of	of	ADP
app01-4029	65	11	its	its	PRON
app01-4029	65	12	input	input	NOUN
app01-4029	65	13	weights	weight	NOUN
app01-4029	65	14	(	(	PUNCT
app01-4029	65	15	5	5	NUM
app01-4029	65	16	.	.	PUNCT
app01-4029	65	17	)	)	PUNCT
app01-4029	66	1	the	the	DET
app01-4029	66	2	reference	reference	NOUN
app01-4029	66	3	neuron	neuron	NOUN
app01-4029	66	4	repeats	repeat	VERB
app01-4029	66	5	the	the	DET
app01-4029	66	6	forward	forward	ADJ
app01-4029	66	7	phase	phase	NOUN
app01-4029	66	8	with	with	ADP
app01-4029	66	9	the	the	DET
app01-4029	66	10	same	same	ADJ
app01-4029	66	11	data	datum	NOUN
app01-4029	66	12	but	but	CCONJ
app01-4029	66	13	with	with	ADP
app01-4029	66	14	changed	change	VERB
app01-4029	66	15	weight	weight	NOUN
app01-4029	66	16	(	(	PUNCT
app01-4029	66	17	6	6	NUM
app01-4029	66	18	.	.	PUNCT
app01-4029	66	19	)	)	PUNCT
app01-4029	67	1	the	the	DET
app01-4029	67	2	output	output	NOUN
app01-4029	67	3	neurons	neuron	NOUN
app01-4029	67	4	compute	compute	VERB
app01-4029	67	5	the	the	DET
app01-4029	67	6	utility	utility	NOUN
app01-4029	67	7	(	(	PUNCT
app01-4029	67	8	as	as	ADP
app01-4029	67	9	in	in	ADP
app01-4029	67	10	step	step	NOUN
app01-4029	67	11	3	3	NUM
app01-4029	67	12	)	)	PUNCT
app01-4029	67	13	(	(	PUNCT
app01-4029	67	14	7	7	NUM
app01-4029	67	15	.	.	PUNCT
app01-4029	67	16	)	)	PUNCT
app01-4029	68	1	the	the	DET
app01-4029	68	2	reference	reference	NOUN
app01-4029	68	3	neuron	neuron	NOUN
app01-4029	68	4	evaluates	evaluate	VERB
app01-4029	68	5	the	the	DET
app01-4029	68	6	change	change	NOUN
app01-4029	68	7	in	in	ADP
app01-4029	68	8	the	the	DET
app01-4029	68	9	step	step	NOUN
app01-4029	68	10	4	4	NUM
app01-4029	68	11	–	–	PUNCT
app01-4029	68	12	if	if	SCONJ
app01-4029	68	13	it	it	PRON
app01-4029	68	14	improves	improve	VERB
app01-4029	68	15	the	the	DET
app01-4029	68	16	utility	utility	NOUN
app01-4029	68	17	,	,	PUNCT
app01-4029	68	18	it	it	PRON
app01-4029	68	19	will	will	AUX
app01-4029	68	20	keep	keep	VERB
app01-4029	68	21	it	it	PRON
app01-4029	68	22	,	,	PUNCT
app01-4029	68	23	otherwise	otherwise	ADV
app01-4029	68	24	it	it	PRON
app01-4029	68	25	will	will	AUX
app01-4029	68	26	change	change	VERB
app01-4029	68	27	the	the	DET
app01-4029	68	28	weights	weight	NOUN
app01-4029	68	29	in	in	ADP
app01-4029	68	30	the	the	DET
app01-4029	68	31	opposite	opposite	ADJ
app01-4029	68	32	direction	direction	NOUN
app01-4029	68	33	(	(	PUNCT
app01-4029	68	34	8	8	NUM
app01-4029	68	35	.	.	PUNCT
app01-4029	68	36	)	)	PUNCT
app01-4029	68	37	neuron	neuron	NOUN
app01-4029	68	38	repeats	repeat	VERB
app01-4029	68	39	steps	step	NOUN
app01-4029	68	40	2	2	NUM
app01-4029	68	41	to	to	ADP
app01-4029	68	42	7	7	NUM
app01-4029	68	43	with	with	ADP
app01-4029	68	44	all	all	DET
app01-4029	68	45	the	the	DET
app01-4029	68	46	connections	connection	NOUN
app01-4029	68	47	and	and	CCONJ
app01-4029	68	48	all	all	DET
app01-4029	68	49	the	the	DET
app01-4029	68	50	inputs	input	NOUN
app01-4029	68	51	.	.	PUNCT
app01-4029	69	1	3	3	X
app01-4029	69	2	.	.	X
app01-4029	69	3	criterions	criterion	NOUN
app01-4029	69	4	for	for	ADP
app01-4029	69	5	optimization	optimization	NOUN
app01-4029	69	6	several	several	ADJ
app01-4029	69	7	methods	method	NOUN
app01-4029	69	8	can	can	AUX
app01-4029	69	9	be	be	AUX
app01-4029	69	10	used	use	VERB
app01-4029	69	11	for	for	ADP
app01-4029	69	12	the	the	DET
app01-4029	69	13	calculation	calculation	NOUN
app01-4029	69	14	the	the	DET
app01-4029	69	15	importance	importance	NOUN
app01-4029	69	16	of	of	ADP
app01-4029	69	17	the	the	DET
app01-4029	69	18	neuron	neuron	NOUN
app01-4029	69	19	.	.	PUNCT
app01-4029	70	1	the	the	DET
app01-4029	70	2	basic	basic	ADJ
app01-4029	70	3	difference	difference	NOUN
app01-4029	70	4	among	among	ADP
app01-4029	70	5	them	they	PRON
app01-4029	70	6	is	be	AUX
app01-4029	70	7	the	the	DET
app01-4029	70	8	number	number	NOUN
app01-4029	70	9	of	of	ADP
app01-4029	70	10	output	output	NOUN
app01-4029	70	11	neurons	neuron	NOUN
app01-4029	70	12	for	for	ADP
app01-4029	70	13	which	which	PRON
app01-4029	70	14	the	the	DET
app01-4029	70	15	reference	reference	NOUN
app01-4029	70	16	neuron	neuron	NOUN
app01-4029	70	17	is	be	AUX
app01-4029	70	18	’	'	PUNCT
app01-4029	70	19	working	work	VERB
app01-4029	70	20	’	'	PUNCT
app01-4029	70	21	.	.	PUNCT
app01-4029	71	1	the	the	DET
app01-4029	71	2	first	first	ADJ
app01-4029	71	3	extreme	extreme	NOUN
app01-4029	71	4	is	be	AUX
app01-4029	71	5	a	a	DET
app01-4029	71	6	neuron	neuron	NOUN
app01-4029	71	7	that	that	PRON
app01-4029	71	8	is	be	AUX
app01-4029	71	9	optimizing	optimize	VERB
app01-4029	71	10	its	its	PRON
app01-4029	71	11	function	function	NOUN
app01-4029	71	12	for	for	ADP
app01-4029	71	13	all	all	DET
app01-4029	71	14	output	output	NOUN
app01-4029	71	15	neurons	neuron	NOUN
app01-4029	71	16	.	.	PUNCT
app01-4029	72	1	this	this	DET
app01-4029	72	2	neuron	neuron	NOUN
app01-4029	72	3	is	be	AUX
app01-4029	72	4	’	'	PUNCT
app01-4029	72	5	reading	read	VERB
app01-4029	72	6	’	'	PUNCT
app01-4029	72	7	all	all	PRON
app01-4029	72	8	output	output	NOUN
app01-4029	72	9	weights	weight	NOUN
app01-4029	72	10	without	without	ADP
app01-4029	72	11	taking	take	VERB
app01-4029	72	12	any	any	DET
app01-4029	72	13	particular	particular	ADJ
app01-4029	72	14	weight	weight	NOUN
app01-4029	72	15	into	into	ADP
app01-4029	72	16	consideration	consideration	NOUN
app01-4029	72	17	.	.	PUNCT
app01-4029	73	1	the	the	DET
app01-4029	73	2	opposite	opposite	ADJ
app01-4029	73	3	extreme	extreme	NOUN
app01-4029	73	4	is	be	AUX
app01-4029	73	5	neuron	neuron	NOUN
app01-4029	73	6	that	that	PRON
app01-4029	73	7	works	work	VERB
app01-4029	73	8	only	only	ADV
app01-4029	73	9	for	for	ADP
app01-4029	73	10	one	one	NUM
app01-4029	73	11	neuron	neuron	NOUN
app01-4029	73	12	in	in	ADP
app01-4029	73	13	the	the	DET
app01-4029	73	14	higher	high	ADJ
app01-4029	73	15	layer	layer	NOUN
app01-4029	73	16	;	;	PUNCT
app01-4029	73	17	in	in	ADP
app01-4029	73	18	other	other	ADJ
app01-4029	73	19	words	word	NOUN
app01-4029	73	20	is	be	AUX
app01-4029	73	21	optimizing	optimize	VERB
app01-4029	73	22	its	its	PRON
app01-4029	73	23	function	function	NOUN
app01-4029	73	24	to	to	PART
app01-4029	73	25	improve	improve	VERB
app01-4029	73	26	its	its	PRON
app01-4029	73	27	utility	utility	NOUN
app01-4029	73	28	for	for	ADP
app01-4029	73	29	this	this	DET
app01-4029	73	30	particular	particular	ADJ
app01-4029	73	31	neuron	neuron	NOUN
app01-4029	73	32	.	.	PUNCT
app01-4029	74	1	apart	apart	ADV
app01-4029	74	2	from	from	ADP
app01-4029	74	3	these	these	DET
app01-4029	74	4	options	option	NOUN
app01-4029	74	5	,	,	PUNCT
app01-4029	74	6	many	many	ADJ
app01-4029	74	7	other	other	ADJ
app01-4029	74	8	compromise	compromise	NOUN
app01-4029	74	9	criterions	criterion	NOUN
app01-4029	74	10	can	can	AUX
app01-4029	74	11	be	be	AUX
app01-4029	74	12	defined	define	VERB
app01-4029	74	13	.	.	PUNCT
app01-4029	75	1	100	100	NUM
app01-4029	75	2	vol	vol	NOUN
app01-4029	75	3	.	.	PUNCT
app01-4029	76	1	12/2017	12/2017	NUM
app01-4029	76	2	artificial	artificial	ADJ
app01-4029	76	3	neural	neural	ADJ
app01-4029	76	4	network	network	NOUN
app01-4029	76	5	for	for	ADP
app01-4029	76	6	models	model	NOUN
app01-4029	76	7	of	of	ADP
app01-4029	76	8	human	human	ADJ
app01-4029	76	9	operator	operator	NOUN
app01-4029	76	10	figure	figure	NOUN
app01-4029	76	11	1	1	NUM
app01-4029	76	12	.	.	PUNCT
app01-4029	76	13	wide	wide	ADJ
app01-4029	76	14	figure[4	figure[4	NOUN
app01-4029	76	15	,	,	PUNCT
app01-4029	76	16	5	5	NUM
app01-4029	76	17	]	]	PUNCT
app01-4029	76	18	.	.	PUNCT
app01-4029	77	1	101	101	NUM
app01-4029	77	2	martin	martin	PROPN
app01-4029	77	3	růžek	růžek	PROPN
app01-4029	77	4	acta	acta	PROPN
app01-4029	77	5	polytechnica	polytechnica	PROPN
app01-4029	77	6	ctu	ctu	NOUN
app01-4029	77	7	proceedings	proceeding	NOUN
app01-4029	77	8	this	this	DET
app01-4029	77	9	first	first	ADJ
app01-4029	77	10	idea	idea	NOUN
app01-4029	77	11	corresponds	correspond	VERB
app01-4029	77	12	to	to	ADP
app01-4029	77	13	a	a	DET
app01-4029	77	14	neuron	neuron	NOUN
app01-4029	77	15	that	that	PRON
app01-4029	77	16	is	be	AUX
app01-4029	77	17	finding	find	VERB
app01-4029	77	18	such	such	DET
app01-4029	77	19	a	a	DET
app01-4029	77	20	weight	weight	NOUN
app01-4029	77	21	vector	vector	NOUN
app01-4029	77	22	∧	∧	PROPN
app01-4029	77	23	=	=	SYM
app01-4029	77	24	w1	w1	PROPN
app01-4029	77	25	,	,	PUNCT
app01-4029	77	26	w2	w2	NOUN
app01-4029	77	27	,	,	PUNCT
app01-4029	77	28	...	...	PUNCT
app01-4029	77	29	,	,	PUNCT
app01-4029	77	30	wn	wn	INTJ
app01-4029	77	31	for	for	ADP
app01-4029	77	32	which	which	PRON
app01-4029	77	33	the	the	DET
app01-4029	77	34	sum	sum	NOUN
app01-4029	77	35	of	of	ADP
app01-4029	77	36	the	the	DET
app01-4029	77	37	absolute	absolute	ADJ
app01-4029	77	38	values	value	NOUN
app01-4029	77	39	of	of	ADP
app01-4029	77	40	the	the	DET
app01-4029	77	41	output	output	NOUN
app01-4029	77	42	weights	weight	NOUN
app01-4029	77	43	is	be	AUX
app01-4029	77	44	maximal	maximal	ADJ
app01-4029	77	45	.	.	PUNCT
app01-4029	78	1	this	this	DET
app01-4029	78	2	idea	idea	NOUN
app01-4029	78	3	corresponds	correspond	VERB
app01-4029	78	4	firmly	firmly	ADV
app01-4029	78	5	to	to	ADP
app01-4029	78	6	the	the	DET
app01-4029	78	7	biological	biological	ADJ
app01-4029	78	8	reality	reality	NOUN
app01-4029	78	9	because	because	SCONJ
app01-4029	78	10	the	the	DET
app01-4029	78	11	neuron	neuron	NOUN
app01-4029	78	12	has	have	VERB
app01-4029	78	13	only	only	ADV
app01-4029	78	14	one	one	NUM
app01-4029	78	15	axon	axon	NOUN
app01-4029	78	16	and	and	CCONJ
app01-4029	78	17	therefore	therefore	ADV
app01-4029	78	18	it	it	PRON
app01-4029	78	19	can	can	AUX
app01-4029	78	20	only	only	ADV
app01-4029	78	21	be	be	AUX
app01-4029	78	22	aware	aware	ADJ
app01-4029	78	23	of	of	ADP
app01-4029	78	24	the	the	DET
app01-4029	78	25	total	total	ADJ
app01-4029	78	26	amount	amount	NOUN
app01-4029	78	27	of	of	ADP
app01-4029	78	28	the	the	DET
app01-4029	78	29	signal	signal	NOUN
app01-4029	78	30	that	that	PRON
app01-4029	78	31	is	be	AUX
app01-4029	78	32	accepted	accept	VERB
app01-4029	78	33	by	by	ADP
app01-4029	78	34	other	other	ADJ
app01-4029	78	35	neurons	neuron	NOUN
app01-4029	78	36	,	,	PUNCT
app01-4029	78	37	not	not	PART
app01-4029	78	38	of	of	ADP
app01-4029	78	39	the	the	DET
app01-4029	78	40	particular	particular	ADJ
app01-4029	78	41	weights	weight	NOUN
app01-4029	78	42	.	.	PUNCT
app01-4029	79	1	in	in	ADP
app01-4029	79	2	the	the	DET
app01-4029	79	3	case	case	NOUN
app01-4029	79	4	of	of	ADP
app01-4029	79	5	the	the	DET
app01-4029	79	6	artificial	artificial	ADJ
app01-4029	79	7	neuron	neuron	NOUN
app01-4029	79	8	we	we	PRON
app01-4029	79	9	also	also	ADV
app01-4029	79	10	expect	expect	VERB
app01-4029	79	11	negative	negative	ADJ
app01-4029	79	12	weights	weight	NOUN
app01-4029	79	13	;	;	PUNCT
app01-4029	79	14	therefore	therefore	ADV
app01-4029	79	15	the	the	DET
app01-4029	79	16	neuron	neuron	NOUN
app01-4029	79	17	sums	sum	VERB
app01-4029	79	18	the	the	DET
app01-4029	79	19	absolute	absolute	ADJ
app01-4029	79	20	or	or	CCONJ
app01-4029	79	21	square	square	ADJ
app01-4029	79	22	values	value	NOUN
app01-4029	79	23	.	.	PUNCT
app01-4029	80	1	the	the	DET
app01-4029	80	2	utility	utility	NOUN
app01-4029	80	3	q	q	PUNCT
app01-4029	80	4	is	be	AUX
app01-4029	80	5	:	:	PUNCT
app01-4029	80	6	q	q	PROPN
app01-4029	80	7	=	=	SYM
app01-4029	80	8	n∑	n∑	NOUN
app01-4029	80	9	j=1	j=1	PROPN
app01-4029	80	10	|woj	|woj	PROPN
app01-4029	81	1	|	|	ADV
app01-4029	81	2	(	(	PUNCT
app01-4029	81	3	3	3	NUM
app01-4029	81	4	)	)	PUNCT
app01-4029	81	5	respectively	respectively	ADV
app01-4029	81	6	:	:	PUNCT
app01-4029	81	7	q	q	X
app01-4029	82	1	=	=	SYM
app01-4029	82	2	n∑	n∑	ADJ
app01-4029	82	3	j=1	j=1	PROPN
app01-4029	82	4	(	(	PUNCT
app01-4029	82	5	woj	woj	PROPN
app01-4029	82	6	)	)	PUNCT
app01-4029	82	7	2	2	NUM
app01-4029	82	8	(	(	PUNCT
app01-4029	82	9	4	4	NUM
app01-4029	82	10	)	)	PUNCT
app01-4029	82	11	eq	eq	NOUN
app01-4029	82	12	.	.	NOUN
app01-4029	82	13	4	4	NUM
app01-4029	82	14	puts	put	VERB
app01-4029	82	15	stress	stress	NOUN
app01-4029	82	16	on	on	ADP
app01-4029	82	17	great	great	ADJ
app01-4029	82	18	values	value	NOUN
app01-4029	82	19	and	and	CCONJ
app01-4029	82	20	reduces	reduce	VERB
app01-4029	82	21	the	the	DET
app01-4029	82	22	importance	importance	NOUN
app01-4029	82	23	of	of	ADP
app01-4029	82	24	the	the	DET
app01-4029	82	25	small	small	ADJ
app01-4029	82	26	ones	one	NOUN
app01-4029	82	27	.	.	PUNCT
app01-4029	83	1	this	this	PRON
app01-4029	83	2	may	may	AUX
app01-4029	83	3	be	be	AUX
app01-4029	83	4	in	in	ADP
app01-4029	83	5	certain	certain	ADJ
app01-4029	83	6	cases	case	NOUN
app01-4029	83	7	advantage	advantage	NOUN
app01-4029	83	8	for	for	ADP
app01-4029	83	9	the	the	DET
app01-4029	83	10	learning	learning	NOUN
app01-4029	83	11	but	but	CCONJ
app01-4029	83	12	does	do	AUX
app01-4029	83	13	not	not	PART
app01-4029	83	14	correspond	correspond	VERB
app01-4029	83	15	to	to	ADP
app01-4029	83	16	the	the	DET
app01-4029	83	17	biological	biological	ADJ
app01-4029	83	18	reality	reality	NOUN
app01-4029	83	19	.	.	PUNCT
app01-4029	84	1	4	4	X
app01-4029	84	2	.	.	X
app01-4029	84	3	searching	search	VERB
app01-4029	84	4	the	the	DET
app01-4029	84	5	one	one	NUM
app01-4029	84	6	neuron	neuron	NOUN
app01-4029	84	7	maximum	maximum	ADJ
app01-4029	84	8	–	–	PUNCT
app01-4029	84	9	the	the	DET
app01-4029	84	10	second	second	ADJ
app01-4029	84	11	extreme	extreme	NOUN
app01-4029	84	12	the	the	DET
app01-4029	84	13	other	other	ADJ
app01-4029	84	14	type	type	NOUN
app01-4029	84	15	of	of	ADP
app01-4029	84	16	training	training	NOUN
app01-4029	84	17	is	be	AUX
app01-4029	84	18	based	base	VERB
app01-4029	84	19	on	on	ADP
app01-4029	84	20	the	the	DET
app01-4029	84	21	presumption	presumption	NOUN
app01-4029	84	22	that	that	SCONJ
app01-4029	84	23	the	the	DET
app01-4029	84	24	neuron	neuron	NOUN
app01-4029	84	25	is	be	AUX
app01-4029	84	26	increasing	increase	VERB
app01-4029	84	27	its	its	PRON
app01-4029	84	28	importance	importance	NOUN
app01-4029	84	29	to	to	ADP
app01-4029	84	30	only	only	ADV
app01-4029	84	31	one	one	NUM
app01-4029	84	32	neuron	neuron	NOUN
app01-4029	84	33	in	in	ADP
app01-4029	84	34	the	the	DET
app01-4029	84	35	higher	high	ADJ
app01-4029	84	36	layer	layer	NOUN
app01-4029	84	37	,	,	PUNCT
app01-4029	84	38	therefore	therefore	ADV
app01-4029	84	39	it	it	PRON
app01-4029	84	40	maximizes	maximize	VERB
app01-4029	84	41	the	the	DET
app01-4029	84	42	function	function	NOUN
app01-4029	84	43	:	:	PUNCT
app01-4029	84	44	q	q	X
app01-4029	85	1	=	=	X
app01-4029	85	2	max|woj	max|woj	ADV
app01-4029	85	3	|	|	ADV
app01-4029	85	4	;	;	PUNCT
app01-4029	85	5	j	j	PROPN
app01-4029	85	6	∈	∈	PROPN
app01-4029	86	1	[	[	X
app01-4029	86	2	0	0	NUM
app01-4029	86	3	,	,	PUNCT
app01-4029	86	4	1	1	NUM
app01-4029	86	5	,	,	PUNCT
app01-4029	86	6	...	...	PUNCT
app01-4029	86	7	n	n	CCONJ
app01-4029	86	8	]	]	X
app01-4029	86	9	(	(	PUNCT
app01-4029	86	10	5	5	X
app01-4029	86	11	)	)	PUNCT
app01-4029	86	12	the	the	DET
app01-4029	86	13	problem	problem	NOUN
app01-4029	86	14	is	be	AUX
app01-4029	86	15	that	that	SCONJ
app01-4029	86	16	if	if	SCONJ
app01-4029	86	17	max|wo|	max|wo|	ADJ
app01-4029	86	18	=	=	SYM
app01-4029	86	19	1	1	NUM
app01-4029	86	20	,	,	PUNCT
app01-4029	86	21	no	no	DET
app01-4029	86	22	further	further	ADJ
app01-4029	86	23	improvement	improvement	NOUN
app01-4029	86	24	is	be	AUX
app01-4029	86	25	possible	possible	ADJ
app01-4029	86	26	and	and	CCONJ
app01-4029	86	27	the	the	DET
app01-4029	86	28	training	training	NOUN
app01-4029	86	29	stops	stop	VERB
app01-4029	86	30	.	.	PUNCT
app01-4029	87	1	in	in	ADP
app01-4029	87	2	a	a	DET
app01-4029	87	3	real	real	ADJ
app01-4029	87	4	situation	situation	NOUN
app01-4029	87	5	,	,	PUNCT
app01-4029	87	6	we	we	PRON
app01-4029	87	7	expect	expect	VERB
app01-4029	87	8	networks	network	NOUN
app01-4029	87	9	with	with	ADP
app01-4029	87	10	many	many	ADJ
app01-4029	87	11	neurons	neuron	NOUN
app01-4029	87	12	where	where	SCONJ
app01-4029	87	13	this	this	DET
app01-4029	87	14	value	value	NOUN
app01-4029	87	15	will	will	AUX
app01-4029	87	16	be	be	AUX
app01-4029	87	17	reached	reach	VERB
app01-4029	87	18	very	very	ADV
app01-4029	87	19	soon	soon	ADV
app01-4029	87	20	and	and	CCONJ
app01-4029	87	21	then	then	ADV
app01-4029	87	22	the	the	DET
app01-4029	87	23	learning	learning	NOUN
app01-4029	87	24	stops	stop	VERB
app01-4029	87	25	.	.	PUNCT
app01-4029	88	1	this	this	PRON
app01-4029	88	2	is	be	AUX
app01-4029	88	3	not	not	PART
app01-4029	88	4	the	the	DET
app01-4029	88	5	desired	desire	VERB
app01-4029	88	6	behavior	behavior	NOUN
app01-4029	88	7	;	;	PUNCT
app01-4029	88	8	therefore	therefore	ADV
app01-4029	88	9	in	in	ADP
app01-4029	88	10	that	that	DET
app01-4029	88	11	case	case	NOUN
app01-4029	88	12	there	there	PRON
app01-4029	88	13	should	should	AUX
app01-4029	88	14	be	be	AUX
app01-4029	88	15	used	use	VERB
app01-4029	88	16	an	an	DET
app01-4029	88	17	additional	additional	ADJ
app01-4029	88	18	condition	condition	NOUN
app01-4029	88	19	that	that	PRON
app01-4029	88	20	ensures	ensure	VERB
app01-4029	88	21	the	the	DET
app01-4029	88	22	continuation	continuation	NOUN
app01-4029	88	23	of	of	ADP
app01-4029	88	24	the	the	DET
app01-4029	88	25	training	training	NOUN
app01-4029	88	26	.	.	PUNCT
app01-4029	89	1	the	the	DET
app01-4029	89	2	solution	solution	NOUN
app01-4029	89	3	of	of	ADP
app01-4029	89	4	this	this	DET
app01-4029	89	5	problem	problem	NOUN
app01-4029	89	6	is	be	AUX
app01-4029	89	7	to	to	PART
app01-4029	89	8	use	use	VERB
app01-4029	89	9	a	a	DET
app01-4029	89	10	compromise	compromise	NOUN
app01-4029	89	11	that	that	PRON
app01-4029	89	12	takes	take	VERB
app01-4029	89	13	into	into	ADP
app01-4029	89	14	consideration	consideration	NOUN
app01-4029	89	15	more	more	ADJ
app01-4029	89	16	than	than	ADP
app01-4029	89	17	one	one	NUM
app01-4029	89	18	output	output	NOUN
app01-4029	89	19	neuron	neuron	NOUN
app01-4029	89	20	but	but	CCONJ
app01-4029	89	21	not	not	PART
app01-4029	89	22	all	all	PRON
app01-4029	89	23	of	of	ADP
app01-4029	89	24	them	they	PRON
app01-4029	89	25	.	.	PUNCT
app01-4029	90	1	this	this	PRON
app01-4029	90	2	can	can	AUX
app01-4029	90	3	be	be	AUX
app01-4029	90	4	done	do	VERB
app01-4029	90	5	by	by	ADP
app01-4029	90	6	optimization	optimization	NOUN
app01-4029	90	7	of	of	ADP
app01-4029	90	8	some	some	DET
app01-4029	90	9	given	give	VERB
app01-4029	90	10	number	number	NOUN
app01-4029	90	11	of	of	ADP
app01-4029	90	12	maximal	maximal	ADJ
app01-4029	90	13	output	output	NOUN
app01-4029	90	14	weights	weight	NOUN
app01-4029	90	15	:	:	PUNCT
app01-4029	90	16	u	u	NOUN
app01-4029	90	17	=	=	NOUN
app01-4029	90	18	max(|wo|	max(|wo|	PRON
app01-4029	90	19	)	)	PUNCT
app01-4029	91	1	+	+	ADP
app01-4029	91	2	max(wo	max(wo	PROPN
app01-4029	91	3	−max(wo	−max(wo	PROPN
app01-4029	91	4	)	)	PUNCT
app01-4029	91	5	)	)	PUNCT
app01-4029	92	1	+	+	CCONJ
app01-4029	92	2	...	...	PUNCT
app01-4029	92	3	;	;	PUNCT
app01-4029	92	4	(	(	PUNCT
app01-4029	92	5	6	6	X
app01-4029	92	6	)	)	PUNCT
app01-4029	92	7	where	where	SCONJ
app01-4029	92	8	w	w	NOUN
app01-4029	92	9	=	=	PRON
app01-4029	92	10	{	{	PUNCT
app01-4029	92	11	w0	w0	PROPN
app01-4029	92	12	,	,	PUNCT
app01-4029	92	13	...	...	PUNCT
app01-4029	92	14	,	,	PUNCT
app01-4029	92	15	wn−1	wn−1	PROPN
app01-4029	92	16	}	}	PUNCT
app01-4029	92	17	.	.	PUNCT
app01-4029	93	1	5	5	X
app01-4029	93	2	.	.	X
app01-4029	93	3	variants	variant	NOUN
app01-4029	93	4	of	of	ADP
app01-4029	93	5	homeostatical	homeostatical	ADJ
app01-4029	93	6	neural	neural	ADJ
app01-4029	93	7	network	network	NOUN
app01-4029	93	8	apart	apart	ADV
app01-4029	93	9	from	from	ADP
app01-4029	93	10	the	the	DET
app01-4029	93	11	above	above	ADJ
app01-4029	93	12	mentioned	mention	VERB
app01-4029	93	13	variant	variant	NOUN
app01-4029	93	14	,	,	PUNCT
app01-4029	93	15	several	several	ADJ
app01-4029	93	16	other	other	ADJ
app01-4029	93	17	options	option	NOUN
app01-4029	93	18	must	must	AUX
app01-4029	93	19	be	be	AUX
app01-4029	93	20	defined	define	VERB
app01-4029	93	21	.	.	PUNCT
app01-4029	94	1	first	first	ADV
app01-4029	94	2	of	of	ADP
app01-4029	94	3	all	all	PRON
app01-4029	94	4	,	,	PUNCT
app01-4029	94	5	the	the	DET
app01-4029	94	6	question	question	NOUN
app01-4029	94	7	of	of	ADP
app01-4029	94	8	the	the	DET
app01-4029	94	9	weight	weight	NOUN
app01-4029	94	10	range	range	NOUN
app01-4029	94	11	arises	arise	VERB
app01-4029	94	12	at	at	ADV
app01-4029	94	13	least	least	ADV
app01-4029	94	14	three	three	NUM
app01-4029	94	15	options	option	NOUN
app01-4029	94	16	.	.	PUNCT
app01-4029	95	1	the	the	DET
app01-4029	95	2	most	most	ADV
app01-4029	95	3	biologically	biologically	ADV
app01-4029	95	4	plausible	plausible	ADJ
app01-4029	95	5	is	be	AUX
app01-4029	95	6	to	to	PART
app01-4029	95	7	limit	limit	VERB
app01-4029	95	8	the	the	DET
app01-4029	95	9	weights	weight	NOUN
app01-4029	95	10	to	to	ADP
app01-4029	95	11	interval	interval	NOUN
app01-4029	95	12	between	between	ADP
app01-4029	95	13	0	0	NUM
app01-4029	95	14	and	and	CCONJ
app01-4029	95	15	1	1	NUM
app01-4029	95	16	.	.	PUNCT
app01-4029	96	1	that	that	PRON
app01-4029	96	2	means	mean	VERB
app01-4029	96	3	that	that	SCONJ
app01-4029	96	4	the	the	DET
app01-4029	96	5	weights	weight	NOUN
app01-4029	96	6	can	can	AUX
app01-4029	96	7	not	not	PART
app01-4029	96	8	change	change	VERB
app01-4029	96	9	the	the	DET
app01-4029	96	10	polarity	polarity	NOUN
app01-4029	96	11	of	of	ADP
app01-4029	96	12	the	the	DET
app01-4029	96	13	signal	signal	NOUN
app01-4029	96	14	and	and	CCONJ
app01-4029	96	15	no	no	DET
app01-4029	96	16	gain	gain	NOUN
app01-4029	96	17	of	of	ADP
app01-4029	96	18	the	the	DET
app01-4029	96	19	output	output	NOUN
app01-4029	96	20	energy	energy	NOUN
app01-4029	96	21	is	be	AUX
app01-4029	96	22	allowed	allow	VERB
app01-4029	96	23	.	.	PUNCT
app01-4029	97	1	this	this	DET
app01-4029	97	2	option	option	NOUN
app01-4029	97	3	is	be	AUX
app01-4029	97	4	the	the	DET
app01-4029	97	5	most	most	ADV
app01-4029	97	6	biologically	biologically	ADV
app01-4029	97	7	plausible	plausible	ADJ
app01-4029	97	8	as	as	SCONJ
app01-4029	97	9	the	the	DET
app01-4029	97	10	axon	axon	NOUN
app01-4029	97	11	,	,	PUNCT
app01-4029	97	12	synapse	synapse	NOUN
app01-4029	97	13	and	and	CCONJ
app01-4029	97	14	dendrites	dendrite	NOUN
app01-4029	97	15	are	be	AUX
app01-4029	97	16	mostly	mostly	ADV
app01-4029	97	17	working	work	VERB
app01-4029	97	18	only	only	ADV
app01-4029	97	19	as	as	ADP
app01-4029	97	20	transmitters	transmitter	NOUN
app01-4029	97	21	of	of	ADP
app01-4029	97	22	the	the	DET
app01-4029	97	23	signal	signal	NOUN
app01-4029	97	24	.	.	PUNCT
app01-4029	98	1	on	on	ADP
app01-4029	98	2	the	the	DET
app01-4029	98	3	other	other	ADJ
app01-4029	98	4	hand	hand	NOUN
app01-4029	98	5	,	,	PUNCT
app01-4029	98	6	some	some	DET
app01-4029	98	7	operation	operation	NOUN
app01-4029	98	8	with	with	ADP
app01-4029	98	9	the	the	DET
app01-4029	98	10	signal	signal	NOUN
app01-4029	98	11	may	may	AUX
app01-4029	98	12	be	be	AUX
app01-4029	98	13	done	do	VERB
app01-4029	98	14	also	also	ADV
app01-4029	98	15	on	on	ADP
app01-4029	98	16	the	the	DET
app01-4029	98	17	level	level	NOUN
app01-4029	98	18	of	of	ADP
app01-4029	98	19	the	the	DET
app01-4029	98	20	axon	axon	NOUN
app01-4029	98	21	dendrit	dendrit	NOUN
app01-4029	98	22	transmission	transmission	NOUN
app01-4029	98	23	,	,	PUNCT
app01-4029	98	24	for	for	ADP
app01-4029	98	25	example	example	NOUN
app01-4029	98	26	the	the	DET
app01-4029	98	27	inhibitory	inhibitory	ADJ
app01-4029	98	28	weights	weight	NOUN
app01-4029	98	29	can	can	AUX
app01-4029	98	30	reduce	reduce	VERB
app01-4029	98	31	the	the	DET
app01-4029	98	32	neuron	neuron	NOUN
app01-4029	98	33	potential	potential	NOUN
app01-4029	98	34	.	.	PUNCT
app01-4029	99	1	this	this	PRON
app01-4029	99	2	leads	lead	VERB
app01-4029	99	3	to	to	ADP
app01-4029	99	4	the	the	DET
app01-4029	99	5	second	second	ADJ
app01-4029	99	6	idea	idea	NOUN
app01-4029	99	7	,	,	PUNCT
app01-4029	99	8	to	to	PART
app01-4029	99	9	limit	limit	VERB
app01-4029	99	10	the	the	DET
app01-4029	99	11	weights	weight	NOUN
app01-4029	99	12	to	to	ADP
app01-4029	99	13	interval	interval	NOUN
app01-4029	99	14	〈	〈	PROPN
app01-4029	99	15	−1	−1	NOUN
app01-4029	99	16	;	;	PUNCT
app01-4029	99	17	1	1	NUM
app01-4029	99	18	〉	〉	NUM
app01-4029	99	19	.	.	PUNCT
app01-4029	100	1	the	the	DET
app01-4029	100	2	last	last	ADJ
app01-4029	100	3	option	option	NOUN
app01-4029	100	4	is	be	AUX
app01-4029	100	5	not	not	PART
app01-4029	100	6	to	to	PART
app01-4029	100	7	limit	limit	VERB
app01-4029	100	8	the	the	DET
app01-4029	100	9	weights	weight	NOUN
app01-4029	100	10	at	at	ADV
app01-4029	100	11	all	all	ADV
app01-4029	100	12	,	,	PUNCT
app01-4029	100	13	that	that	PRON
app01-4029	100	14	means	mean	VERB
app01-4029	100	15	the	the	DET
app01-4029	100	16	signal	signal	NOUN
app01-4029	100	17	can	can	AUX
app01-4029	100	18	be	be	AUX
app01-4029	100	19	multiplied	multiply	VERB
app01-4029	100	20	by	by	ADP
app01-4029	100	21	any	any	DET
app01-4029	100	22	real	real	ADJ
app01-4029	100	23	number	number	NOUN
app01-4029	100	24	.	.	PUNCT
app01-4029	101	1	this	this	PRON
app01-4029	101	2	is	be	AUX
app01-4029	101	3	the	the	DET
app01-4029	101	4	least	least	ADJ
app01-4029	101	5	biologically	biologically	ADV
app01-4029	101	6	plausible	plausible	ADJ
app01-4029	101	7	method	method	NOUN
app01-4029	101	8	;	;	PUNCT
app01-4029	101	9	on	on	ADP
app01-4029	101	10	the	the	DET
app01-4029	101	11	other	other	ADJ
app01-4029	101	12	hand	hand	NOUN
app01-4029	101	13	it	it	PRON
app01-4029	101	14	will	will	AUX
app01-4029	101	15	bring	bring	VERB
app01-4029	101	16	the	the	DET
app01-4029	101	17	highest	high	ADJ
app01-4029	101	18	computational	computational	ADJ
app01-4029	101	19	power	power	NOUN
app01-4029	101	20	.	.	PUNCT
app01-4029	102	1	the	the	DET
app01-4029	102	2	other	other	ADJ
app01-4029	102	3	question	question	NOUN
app01-4029	102	4	is	be	AUX
app01-4029	102	5	how	how	SCONJ
app01-4029	102	6	to	to	PART
app01-4029	102	7	choose	choose	VERB
app01-4029	102	8	the	the	DET
app01-4029	102	9	weights	weight	NOUN
app01-4029	102	10	that	that	PRON
app01-4029	102	11	should	should	AUX
app01-4029	102	12	be	be	AUX
app01-4029	102	13	updated	update	VERB
app01-4029	102	14	.	.	PUNCT
app01-4029	103	1	the	the	DET
app01-4029	103	2	first	first	ADJ
app01-4029	103	3	option	option	NOUN
app01-4029	103	4	that	that	PRON
app01-4029	103	5	comes	come	VERB
app01-4029	103	6	to	to	ADP
app01-4029	103	7	mind	mind	NOUN
app01-4029	103	8	is	be	AUX
app01-4029	103	9	to	to	PART
app01-4029	103	10	update	update	VERB
app01-4029	103	11	the	the	DET
app01-4029	103	12	weight	weight	NOUN
app01-4029	103	13	that	that	PRON
app01-4029	103	14	has	have	VERB
app01-4029	103	15	the	the	DET
app01-4029	103	16	greatest	great	ADJ
app01-4029	103	17	influence	influence	NOUN
app01-4029	103	18	on	on	ADP
app01-4029	103	19	the	the	DET
app01-4029	103	20	result	result	NOUN
app01-4029	103	21	;	;	PUNCT
app01-4029	103	22	that	that	PRON
app01-4029	103	23	means	mean	VERB
app01-4029	103	24	the	the	DET
app01-4029	103	25	most	most	ADV
app01-4029	103	26	sensitive	sensitive	ADJ
app01-4029	103	27	weight	weight	NOUN
app01-4029	103	28	.	.	PUNCT
app01-4029	104	1	this	this	PRON
app01-4029	104	2	will	will	AUX
app01-4029	104	3	lead	lead	VERB
app01-4029	104	4	to	to	ADP
app01-4029	104	5	highest	high	ADJ
app01-4029	104	6	increase	increase	NOUN
app01-4029	104	7	of	of	ADP
app01-4029	104	8	the	the	DET
app01-4029	104	9	utility	utility	NOUN
app01-4029	104	10	of	of	ADP
app01-4029	104	11	the	the	DET
app01-4029	104	12	neuron	neuron	NOUN
app01-4029	104	13	in	in	ADP
app01-4029	104	14	the	the	DET
app01-4029	104	15	next	next	ADJ
app01-4029	104	16	step	step	NOUN
app01-4029	104	17	,	,	PUNCT
app01-4029	104	18	however	however	ADV
app01-4029	104	19	it	it	PRON
app01-4029	104	20	may	may	AUX
app01-4029	104	21	not	not	PART
app01-4029	104	22	be	be	AUX
app01-4029	104	23	the	the	DET
app01-4029	104	24	best	good	ADJ
app01-4029	104	25	option	option	NOUN
app01-4029	104	26	from	from	ADP
app01-4029	104	27	the	the	DET
app01-4029	104	28	global	global	ADJ
app01-4029	104	29	point	point	NOUN
app01-4029	104	30	of	of	ADP
app01-4029	104	31	view	view	NOUN
app01-4029	104	32	.	.	PUNCT
app01-4029	105	1	making	make	VERB
app01-4029	105	2	the	the	DET
app01-4029	105	3	step	step	NOUN
app01-4029	105	4	always	always	ADV
app01-4029	105	5	in	in	ADP
app01-4029	105	6	the	the	DET
app01-4029	105	7	direction	direction	NOUN
app01-4029	105	8	of	of	ADP
app01-4029	105	9	the	the	DET
app01-4029	105	10	highest	high	ADJ
app01-4029	105	11	gradient	gradient	NOUN
app01-4029	105	12	may	may	AUX
app01-4029	105	13	lead	lead	VERB
app01-4029	105	14	to	to	ADP
app01-4029	105	15	falling	fall	VERB
app01-4029	105	16	into	into	ADP
app01-4029	105	17	local	local	ADJ
app01-4029	105	18	extreme	extreme	NOUN
app01-4029	105	19	.	.	PUNCT
app01-4029	106	1	also	also	ADV
app01-4029	106	2	,	,	PUNCT
app01-4029	106	3	to	to	PART
app01-4029	106	4	find	find	VERB
app01-4029	106	5	the	the	DET
app01-4029	106	6	most	most	ADV
app01-4029	106	7	sensitive	sensitive	ADJ
app01-4029	106	8	weight	weight	NOUN
app01-4029	106	9	consumes	consume	VERB
app01-4029	106	10	a	a	DET
app01-4029	106	11	lot	lot	NOUN
app01-4029	106	12	of	of	ADP
app01-4029	106	13	computational	computational	ADJ
app01-4029	106	14	power	power	NOUN
app01-4029	106	15	.	.	PUNCT
app01-4029	107	1	alternative	alternative	ADJ
app01-4029	107	2	option	option	NOUN
app01-4029	107	3	is	be	AUX
app01-4029	107	4	to	to	PART
app01-4029	107	5	choose	choose	VERB
app01-4029	107	6	the	the	DET
app01-4029	107	7	updated	update	VERB
app01-4029	107	8	weight	weight	NOUN
app01-4029	107	9	randomly	randomly	ADV
app01-4029	107	10	or	or	CCONJ
app01-4029	107	11	in	in	ADP
app01-4029	107	12	given	give	VERB
app01-4029	107	13	order	order	NOUN
app01-4029	107	14	.	.	PUNCT
app01-4029	108	1	these	these	DET
app01-4029	108	2	two	two	NUM
app01-4029	108	3	options	option	NOUN
app01-4029	108	4	lead	lead	VERB
app01-4029	108	5	to	to	ADP
app01-4029	108	6	similar	similar	ADJ
app01-4029	108	7	results	result	NOUN
app01-4029	108	8	.	.	PUNCT
app01-4029	109	1	it	it	PRON
app01-4029	109	2	is	be	AUX
app01-4029	109	3	also	also	ADV
app01-4029	109	4	possible	possible	ADJ
app01-4029	109	5	to	to	PART
app01-4029	109	6	imagine	imagine	VERB
app01-4029	109	7	the	the	DET
app01-4029	109	8	combination	combination	NOUN
app01-4029	109	9	of	of	ADP
app01-4029	109	10	these	these	DET
app01-4029	109	11	algorithms	algorithm	NOUN
app01-4029	109	12	,	,	PUNCT
app01-4029	109	13	for	for	ADP
app01-4029	109	14	example	example	NOUN
app01-4029	109	15	by	by	ADP
app01-4029	109	16	using	use	VERB
app01-4029	109	17	several	several	ADJ
app01-4029	109	18	steps	step	NOUN
app01-4029	109	19	to	to	PART
app01-4029	109	20	update	update	VERB
app01-4029	109	21	of	of	ADP
app01-4029	109	22	the	the	DET
app01-4029	109	23	most	most	ADV
app01-4029	109	24	sensitive	sensitive	ADJ
app01-4029	109	25	weights	weight	NOUN
app01-4029	109	26	which	which	PRON
app01-4029	109	27	may	may	AUX
app01-4029	109	28	be	be	AUX
app01-4029	109	29	followed	follow	VERB
app01-4029	109	30	by	by	ADP
app01-4029	109	31	randomly	randomly	ADV
app01-4029	109	32	chosen	choose	VERB
app01-4029	109	33	weights	weight	NOUN
app01-4029	109	34	.	.	PUNCT
app01-4029	110	1	because	because	SCONJ
app01-4029	110	2	of	of	ADP
app01-4029	110	3	the	the	DET
app01-4029	110	4	complex	complex	ADJ
app01-4029	110	5	nature	nature	NOUN
app01-4029	110	6	of	of	ADP
app01-4029	110	7	the	the	DET
app01-4029	110	8	neural	neural	ADJ
app01-4029	110	9	networks	network	NOUN
app01-4029	110	10	,	,	PUNCT
app01-4029	110	11	it	it	PRON
app01-4029	110	12	is	be	AUX
app01-4029	110	13	not	not	PART
app01-4029	110	14	possible	possible	ADJ
app01-4029	110	15	to	to	PART
app01-4029	110	16	say	say	VERB
app01-4029	110	17	which	which	DET
app01-4029	110	18	method	method	NOUN
app01-4029	110	19	is	be	AUX
app01-4029	110	20	the	the	DET
app01-4029	110	21	best	good	ADJ
app01-4029	110	22	for	for	ADP
app01-4029	110	23	arbitrary	arbitrary	ADJ
app01-4029	110	24	data	datum	NOUN
app01-4029	110	25	.	.	PUNCT
app01-4029	111	1	6	6	X
app01-4029	111	2	.	.	X
app01-4029	111	3	problems	problem	NOUN
app01-4029	111	4	of	of	ADP
app01-4029	111	5	the	the	DET
app01-4029	111	6	idea	idea	NOUN
app01-4029	111	7	of	of	ADP
app01-4029	111	8	homeostatical	homeostatical	ADJ
app01-4029	111	9	learning	learn	VERB
app01-4029	111	10	the	the	DET
app01-4029	111	11	described	describe	VERB
app01-4029	111	12	idea	idea	NOUN
app01-4029	111	13	has	have	VERB
app01-4029	111	14	two	two	NUM
app01-4029	111	15	principal	principal	ADJ
app01-4029	111	16	limitations	limitation	NOUN
app01-4029	111	17	.	.	PUNCT
app01-4029	112	1	the	the	DET
app01-4029	112	2	first	first	ADJ
app01-4029	112	3	one	one	NUM
app01-4029	112	4	is	be	AUX
app01-4029	112	5	the	the	DET
app01-4029	112	6	learning	learning	NOUN
app01-4029	112	7	of	of	ADP
app01-4029	112	8	the	the	DET
app01-4029	112	9	highest	high	ADJ
app01-4029	112	10	layer	layer	NOUN
app01-4029	112	11	.	.	PUNCT
app01-4029	113	1	the	the	DET
app01-4029	113	2	idea	idea	NOUN
app01-4029	113	3	of	of	ADP
app01-4029	113	4	a	a	DET
app01-4029	113	5	learning	learning	NOUN
app01-4029	113	6	algorithm	algorithm	NOUN
app01-4029	113	7	is	be	AUX
app01-4029	113	8	that	that	SCONJ
app01-4029	113	9	neurons	neuron	NOUN
app01-4029	113	10	in	in	ADP
app01-4029	113	11	certain	certain	ADJ
app01-4029	113	12	layers	layer	NOUN
app01-4029	113	13	are	be	AUX
app01-4029	113	14	updating	update	VERB
app01-4029	113	15	their	their	PRON
app01-4029	113	16	weights	weight	NOUN
app01-4029	113	17	according	accord	VERB
app01-4029	113	18	to	to	ADP
app01-4029	113	19	the	the	DET
app01-4029	113	20	higher	high	ADJ
app01-4029	113	21	layer	layer	NOUN
app01-4029	113	22	.	.	PUNCT
app01-4029	114	1	this	this	PRON
app01-4029	114	2	can	can	AUX
app01-4029	114	3	be	be	AUX
app01-4029	114	4	used	use	VERB
app01-4029	114	5	for	for	ADP
app01-4029	114	6	all	all	DET
app01-4029	114	7	layers	layer	NOUN
app01-4029	114	8	except	except	SCONJ
app01-4029	114	9	for	for	ADP
app01-4029	114	10	the	the	DET
app01-4029	114	11	highest	high	ADJ
app01-4029	114	12	as	as	SCONJ
app01-4029	114	13	it	it	PRON
app01-4029	114	14	does	do	AUX
app01-4029	114	15	not	not	PART
app01-4029	114	16	have	have	VERB
app01-4029	114	17	any	any	DET
app01-4029	114	18	output	output	NOUN
app01-4029	114	19	neuron	neuron	NOUN
app01-4029	114	20	.	.	PUNCT
app01-4029	115	1	the	the	DET
app01-4029	115	2	solution	solution	NOUN
app01-4029	115	3	for	for	ADP
app01-4029	115	4	practical	practical	ADJ
app01-4029	115	5	simulation	simulation	NOUN
app01-4029	115	6	and	and	CCONJ
app01-4029	115	7	testing	testing	NOUN
app01-4029	115	8	is	be	AUX
app01-4029	115	9	that	that	SCONJ
app01-4029	115	10	the	the	DET
app01-4029	115	11	highest	high	ADJ
app01-4029	115	12	layer	layer	NOUN
app01-4029	115	13	was	be	AUX
app01-4029	115	14	not	not	PART
app01-4029	115	15	trained	train	VERB
app01-4029	115	16	by	by	ADP
app01-4029	115	17	the	the	DET
app01-4029	115	18	homeostatic	homeostatic	ADJ
app01-4029	115	19	learning	learning	NOUN
app01-4029	115	20	algorithm	algorithm	NOUN
app01-4029	115	21	,	,	PUNCT
app01-4029	115	22	but	but	CCONJ
app01-4029	115	23	by	by	ADP
app01-4029	115	24	the	the	DET
app01-4029	115	25	back	back	ADJ
app01-4029	115	26	propagation	propagation	NOUN
app01-4029	115	27	.	.	PUNCT
app01-4029	116	1	this	this	PRON
app01-4029	116	2	is	be	AUX
app01-4029	116	3	of	of	ADP
app01-4029	116	4	course	course	NOUN
app01-4029	116	5	is	be	AUX
app01-4029	116	6	an	an	DET
app01-4029	116	7	alteration	alteration	NOUN
app01-4029	116	8	of	of	ADP
app01-4029	116	9	the	the	DET
app01-4029	116	10	original	original	ADJ
app01-4029	116	11	idea	idea	NOUN
app01-4029	116	12	,	,	PUNCT
app01-4029	116	13	but	but	CCONJ
app01-4029	116	14	for	for	ADP
app01-4029	116	15	the	the	DET
app01-4029	116	16	sake	sake	NOUN
app01-4029	116	17	of	of	ADP
app01-4029	116	18	the	the	DET
app01-4029	116	19	practical	practical	ADJ
app01-4029	116	20	realization	realization	NOUN
app01-4029	116	21	it	it	PRON
app01-4029	116	22	is	be	AUX
app01-4029	116	23	the	the	DET
app01-4029	116	24	easiest	easy	ADJ
app01-4029	116	25	way	way	NOUN
app01-4029	116	26	how	how	SCONJ
app01-4029	116	27	to	to	PART
app01-4029	116	28	program	program	VERB
app01-4029	116	29	the	the	DET
app01-4029	116	30	homeostatic	homeostatic	ADJ
app01-4029	116	31	learning	learning	NOUN
app01-4029	116	32	for	for	ADP
app01-4029	116	33	the	the	DET
app01-4029	116	34	rest	rest	NOUN
app01-4029	116	35	of	of	ADP
app01-4029	116	36	the	the	DET
app01-4029	116	37	network	network	NOUN
app01-4029	116	38	.	.	PUNCT
app01-4029	117	1	in	in	ADP
app01-4029	117	2	the	the	DET
app01-4029	117	3	case	case	NOUN
app01-4029	117	4	of	of	ADP
app01-4029	117	5	practical	practical	ADJ
app01-4029	117	6	application	application	NOUN
app01-4029	117	7	,	,	PUNCT
app01-4029	117	8	for	for	ADP
app01-4029	117	9	example	example	NOUN
app01-4029	117	10	in	in	ADP
app01-4029	117	11	robot	robot	NOUN
app01-4029	117	12	,	,	PUNCT
app01-4029	117	13	this	this	DET
app01-4029	117	14	problem	problem	NOUN
app01-4029	117	15	will	will	AUX
app01-4029	117	16	be	be	AUX
app01-4029	117	17	solvable	solvable	ADJ
app01-4029	117	18	in	in	ADP
app01-4029	117	19	a	a	DET
app01-4029	117	20	natural	natural	ADJ
app01-4029	117	21	way	way	NOUN
app01-4029	117	22	because	because	SCONJ
app01-4029	117	23	the	the	DET
app01-4029	117	24	network	network	NOUN
app01-4029	117	25	will	will	AUX
app01-4029	117	26	be	be	AUX
app01-4029	117	27	part	part	NOUN
app01-4029	117	28	of	of	ADP
app01-4029	117	29	a	a	DET
app01-4029	117	30	closed	closed	ADJ
app01-4029	117	31	loop	loop	NOUN
app01-4029	117	32	.	.	PUNCT
app01-4029	118	1	the	the	DET
app01-4029	118	2	second	second	ADJ
app01-4029	118	3	problem	problem	NOUN
app01-4029	118	4	is	be	AUX
app01-4029	118	5	the	the	DET
app01-4029	118	6	delay	delay	NOUN
app01-4029	118	7	question	question	NOUN
app01-4029	118	8	.	.	PUNCT
app01-4029	119	1	the	the	DET
app01-4029	119	2	reference	reference	NOUN
app01-4029	119	3	neuron	neuron	NOUN
app01-4029	119	4	is	be	AUX
app01-4029	119	5	updating	update	VERB
app01-4029	119	6	its	its	PRON
app01-4029	119	7	input	input	NOUN
app01-4029	119	8	weights	weight	NOUN
app01-4029	119	9	accord102	accord102	PROPN
app01-4029	119	10	vol	vol	NOUN
app01-4029	119	11	.	.	PUNCT
app01-4029	120	1	12/2017	12/2017	NUM
app01-4029	120	2	artificial	artificial	ADJ
app01-4029	120	3	neural	neural	ADJ
app01-4029	120	4	network	network	NOUN
app01-4029	120	5	for	for	ADP
app01-4029	120	6	models	model	NOUN
app01-4029	120	7	of	of	ADP
app01-4029	120	8	human	human	ADJ
app01-4029	120	9	operator	operator	NOUN
app01-4029	120	10	ing	e	VERB
app01-4029	120	11	to	to	ADP
app01-4029	120	12	its	its	PRON
app01-4029	120	13	output	output	NOUN
app01-4029	120	14	weights	weight	NOUN
app01-4029	120	15	,	,	PUNCT
app01-4029	120	16	but	but	CCONJ
app01-4029	120	17	in	in	ADP
app01-4029	120	18	each	each	DET
app01-4029	120	19	neural	neural	ADJ
app01-4029	120	20	cell	cell	NOUN
app01-4029	120	21	the	the	DET
app01-4029	120	22	output	output	NOUN
app01-4029	120	23	calculation	calculation	NOUN
app01-4029	120	24	takes	take	VERB
app01-4029	120	25	some	some	DET
app01-4029	120	26	time	time	NOUN
app01-4029	120	27	.	.	PUNCT
app01-4029	121	1	,	,	PUNCT
app01-4029	121	2	meanwhile	meanwhile	ADV
app01-4029	121	3	the	the	DET
app01-4029	121	4	inputs	input	NOUN
app01-4029	121	5	are	be	AUX
app01-4029	121	6	changing	change	VERB
app01-4029	121	7	this	this	DET
app01-4029	121	8	means	mean	VERB
app01-4029	121	9	that	that	SCONJ
app01-4029	121	10	the	the	DET
app01-4029	121	11	forward	forward	ADJ
app01-4029	121	12	information	information	NOUN
app01-4029	121	13	will	will	AUX
app01-4029	121	14	not	not	PART
app01-4029	121	15	’	'	PUNCT
app01-4029	121	16	meet	meet	VERB
app01-4029	121	17	’	'	PUNCT
app01-4029	121	18	the	the	DET
app01-4029	121	19	information	information	NOUN
app01-4029	121	20	about	about	ADP
app01-4029	121	21	the	the	DET
app01-4029	121	22	utility	utility	NOUN
app01-4029	121	23	in	in	ADP
app01-4029	121	24	the	the	DET
app01-4029	121	25	same	same	ADJ
app01-4029	121	26	time	time	NOUN
app01-4029	121	27	.	.	PUNCT
app01-4029	122	1	this	this	DET
app01-4029	122	2	problem	problem	NOUN
app01-4029	122	3	has	have	VERB
app01-4029	122	4	two	two	NUM
app01-4029	122	5	solutions	solution	NOUN
app01-4029	122	6	.	.	PUNCT
app01-4029	123	1	the	the	DET
app01-4029	123	2	first	first	ADJ
app01-4029	123	3	is	be	AUX
app01-4029	123	4	to	to	PART
app01-4029	123	5	set	set	VERB
app01-4029	123	6	the	the	DET
app01-4029	123	7	dynamics	dynamic	NOUN
app01-4029	123	8	of	of	ADP
app01-4029	123	9	inputs	input	NOUN
app01-4029	123	10	to	to	ADP
app01-4029	123	11	a	a	DET
app01-4029	123	12	lower	low	ADJ
app01-4029	123	13	level	level	NOUN
app01-4029	123	14	,	,	PUNCT
app01-4029	123	15	so	so	SCONJ
app01-4029	123	16	that	that	SCONJ
app01-4029	123	17	the	the	DET
app01-4029	123	18	speed	speed	NOUN
app01-4029	123	19	of	of	ADP
app01-4029	123	20	information	information	NOUN
app01-4029	123	21	processing	processing	NOUN
app01-4029	123	22	in	in	ADP
app01-4029	123	23	the	the	DET
app01-4029	123	24	whole	whole	ADJ
app01-4029	123	25	system	system	NOUN
app01-4029	123	26	is	be	AUX
app01-4029	123	27	significantly	significantly	ADV
app01-4029	123	28	higher	high	ADJ
app01-4029	123	29	than	than	ADP
app01-4029	123	30	the	the	DET
app01-4029	123	31	changes	change	NOUN
app01-4029	123	32	of	of	ADP
app01-4029	123	33	the	the	DET
app01-4029	123	34	input	input	NOUN
app01-4029	123	35	signals	signal	NOUN
app01-4029	123	36	.	.	PUNCT
app01-4029	124	1	the	the	DET
app01-4029	124	2	other	other	ADJ
app01-4029	124	3	possibility	possibility	NOUN
app01-4029	124	4	is	be	AUX
app01-4029	124	5	to	to	PART
app01-4029	124	6	equip	equip	VERB
app01-4029	124	7	the	the	DET
app01-4029	124	8	neurons	neuron	NOUN
app01-4029	124	9	with	with	ADP
app01-4029	124	10	a	a	DET
app01-4029	124	11	memory	memory	NOUN
app01-4029	124	12	that	that	PRON
app01-4029	124	13	stores	store	VERB
app01-4029	124	14	the	the	DET
app01-4029	124	15	previous	previous	ADJ
app01-4029	124	16	inputs	input	NOUN
app01-4029	124	17	so	so	SCONJ
app01-4029	124	18	that	that	SCONJ
app01-4029	124	19	it	it	PRON
app01-4029	124	20	is	be	AUX
app01-4029	124	21	possible	possible	ADJ
app01-4029	124	22	to	to	PART
app01-4029	124	23	recall	recall	VERB
app01-4029	124	24	them	they	PRON
app01-4029	124	25	when	when	SCONJ
app01-4029	124	26	the	the	DET
app01-4029	124	27	information	information	NOUN
app01-4029	124	28	about	about	ADP
app01-4029	124	29	the	the	DET
app01-4029	124	30	utility	utility	NOUN
app01-4029	124	31	reaches	reach	VERB
app01-4029	124	32	the	the	DET
app01-4029	124	33	neuron	neuron	NOUN
app01-4029	124	34	.	.	PUNCT
app01-4029	125	1	7	7	X
app01-4029	125	2	.	.	X
app01-4029	125	3	conclusions	conclusion	NOUN
app01-4029	125	4	in	in	ADP
app01-4029	125	5	this	this	DET
app01-4029	125	6	paper	paper	NOUN
app01-4029	125	7	,	,	PUNCT
app01-4029	125	8	the	the	DET
app01-4029	125	9	idea	idea	NOUN
app01-4029	125	10	of	of	ADP
app01-4029	125	11	a	a	DET
app01-4029	125	12	new	new	ADJ
app01-4029	125	13	learning	learning	NOUN
app01-4029	125	14	algorithm	algorithm	NOUN
app01-4029	125	15	for	for	ADP
app01-4029	125	16	neural	neural	ADJ
app01-4029	125	17	networks	network	NOUN
app01-4029	125	18	is	be	AUX
app01-4029	125	19	presented	present	VERB
app01-4029	125	20	.	.	PUNCT
app01-4029	126	1	this	this	DET
app01-4029	126	2	algorithm	algorithm	NOUN
app01-4029	126	3	can	can	AUX
app01-4029	126	4	cope	cope	VERB
app01-4029	126	5	with	with	ADP
app01-4029	126	6	some	some	DET
app01-4029	126	7	disadvantages	disadvantage	NOUN
app01-4029	126	8	that	that	SCONJ
app01-4029	126	9	the	the	DET
app01-4029	126	10	classical	classical	ADJ
app01-4029	126	11	neural	neural	ADJ
app01-4029	126	12	networks	network	NOUN
app01-4029	126	13	paradigms	paradigm	NOUN
app01-4029	126	14	have	have	AUX
app01-4029	126	15	.	.	PUNCT
app01-4029	127	1	the	the	DET
app01-4029	127	2	proposed	propose	VERB
app01-4029	127	3	algorithm	algorithm	NOUN
app01-4029	127	4	has	have	VERB
app01-4029	127	5	several	several	ADJ
app01-4029	127	6	variants	variant	NOUN
app01-4029	127	7	;	;	PUNCT
app01-4029	127	8	from	from	ADP
app01-4029	127	9	the	the	DET
app01-4029	127	10	point	point	NOUN
app01-4029	127	11	of	of	ADP
app01-4029	127	12	view	view	NOUN
app01-4029	127	13	of	of	ADP
app01-4029	127	14	the	the	DET
app01-4029	127	15	optimization	optimization	NOUN
app01-4029	127	16	criterion	criterion	NOUN
app01-4029	127	17	it	it	PRON
app01-4029	127	18	is	be	AUX
app01-4029	127	19	optimization	optimization	NOUN
app01-4029	127	20	for	for	ADP
app01-4029	127	21	all	all	DET
app01-4029	127	22	input	input	NOUN
app01-4029	127	23	weights	weight	NOUN
app01-4029	127	24	vs.	vs.	ADP
app01-4029	127	25	optimization	optimization	NOUN
app01-4029	127	26	for	for	ADP
app01-4029	127	27	only	only	ADV
app01-4029	127	28	one	one	NUM
app01-4029	127	29	input	input	NOUN
app01-4029	127	30	weights	weight	NOUN
app01-4029	127	31	,	,	PUNCT
app01-4029	127	32	and	and	CCONJ
app01-4029	127	33	many	many	ADJ
app01-4029	127	34	compromising	compromising	ADJ
app01-4029	127	35	solutions	solution	NOUN
app01-4029	127	36	.	.	PUNCT
app01-4029	128	1	from	from	ADP
app01-4029	128	2	the	the	DET
app01-4029	128	3	point	point	NOUN
app01-4029	128	4	of	of	ADP
app01-4029	128	5	view	view	NOUN
app01-4029	128	6	of	of	ADP
app01-4029	128	7	the	the	DET
app01-4029	128	8	weight	weight	NOUN
app01-4029	128	9	update	update	NOUN
app01-4029	128	10	,	,	PUNCT
app01-4029	128	11	the	the	DET
app01-4029	128	12	possible	possible	ADJ
app01-4029	128	13	variants	variant	NOUN
app01-4029	128	14	are	be	AUX
app01-4029	128	15	the	the	DET
app01-4029	128	16	update	update	NOUN
app01-4029	128	17	of	of	ADP
app01-4029	128	18	the	the	DET
app01-4029	128	19	weight	weight	NOUN
app01-4029	128	20	with	with	ADP
app01-4029	128	21	the	the	DET
app01-4029	128	22	highest	high	ADJ
app01-4029	128	23	sensitivity	sensitivity	NOUN
app01-4029	128	24	to	to	ADP
app01-4029	128	25	the	the	DET
app01-4029	128	26	change	change	NOUN
app01-4029	128	27	,	,	PUNCT
app01-4029	128	28	of	of	ADP
app01-4029	128	29	randomly	randomly	ADV
app01-4029	128	30	chosen	choose	VERB
app01-4029	128	31	weight	weight	NOUN
app01-4029	128	32	of	of	ADP
app01-4029	128	33	consequently	consequently	ADV
app01-4029	128	34	chosen	choose	VERB
app01-4029	128	35	weight	weight	NOUN
app01-4029	128	36	.	.	PUNCT
app01-4029	129	1	from	from	ADP
app01-4029	129	2	the	the	DET
app01-4029	129	3	point	point	NOUN
app01-4029	129	4	of	of	ADP
app01-4029	129	5	view	view	NOUN
app01-4029	129	6	of	of	ADP
app01-4029	129	7	the	the	DET
app01-4029	129	8	weight	weight	NOUN
app01-4029	129	9	range	range	NOUN
app01-4029	129	10	,	,	PUNCT
app01-4029	129	11	it	it	PRON
app01-4029	129	12	is	be	AUX
app01-4029	129	13	possible	possible	ADJ
app01-4029	129	14	to	to	PART
app01-4029	129	15	define	define	VERB
app01-4029	129	16	weights	weight	NOUN
app01-4029	129	17	as	as	ADP
app01-4029	129	18	positive	positive	ADJ
app01-4029	129	19	numbers	number	NOUN
app01-4029	129	20	smaller	small	ADJ
app01-4029	129	21	than	than	ADP
app01-4029	129	22	1	1	NUM
app01-4029	129	23	,	,	PUNCT
app01-4029	129	24	as	as	ADP
app01-4029	129	25	either	either	CCONJ
app01-4029	129	26	positive	positive	ADJ
app01-4029	129	27	or	or	CCONJ
app01-4029	129	28	a	a	DET
app01-4029	129	29	negative	negative	ADJ
app01-4029	129	30	number	number	NOUN
app01-4029	129	31	in	in	ADP
app01-4029	129	32	absolute	absolute	ADJ
app01-4029	129	33	value	value	NOUN
app01-4029	129	34	smaller	small	ADJ
app01-4029	129	35	than	than	ADP
app01-4029	129	36	1	1	NUM
app01-4029	129	37	,	,	PUNCT
app01-4029	129	38	or	or	CCONJ
app01-4029	129	39	as	as	ADP
app01-4029	129	40	real	real	ADJ
app01-4029	129	41	numbers	number	NOUN
app01-4029	129	42	.	.	PUNCT
app01-4029	130	1	every	every	DET
app01-4029	130	2	variant	variant	NOUN
app01-4029	130	3	has	have	VERB
app01-4029	130	4	its	its	PRON
app01-4029	130	5	pros	pro	NOUN
app01-4029	130	6	and	and	CCONJ
app01-4029	130	7	cons	con	NOUN
app01-4029	130	8	.	.	PUNCT
app01-4029	131	1	due	due	ADP
app01-4029	131	2	to	to	ADP
app01-4029	131	3	the	the	DET
app01-4029	131	4	high	high	ADJ
app01-4029	131	5	number	number	NOUN
app01-4029	131	6	of	of	ADP
app01-4029	131	7	variants	variant	NOUN
app01-4029	131	8	which	which	PRON
app01-4029	131	9	is	be	AUX
app01-4029	131	10	even	even	ADV
app01-4029	131	11	multiplied	multiply	VERB
app01-4029	131	12	by	by	ADP
app01-4029	131	13	the	the	DET
app01-4029	131	14	amount	amount	NOUN
app01-4029	131	15	of	of	ADP
app01-4029	131	16	data	datum	NOUN
app01-4029	131	17	(	(	PUNCT
app01-4029	131	18	for	for	ADP
app01-4029	131	19	neural	neural	ADJ
app01-4029	131	20	networks	network	NOUN
app01-4029	131	21	as	as	ADP
app01-4029	131	22	for	for	ADP
app01-4029	131	23	data	datum	NOUN
app01-4029	131	24	driven	drive	VERB
app01-4029	131	25	method	method	NOUN
app01-4029	131	26	it	it	PRON
app01-4029	131	27	is	be	AUX
app01-4029	131	28	important	important	ADJ
app01-4029	131	29	which	which	DET
app01-4029	131	30	data	datum	NOUN
app01-4029	131	31	is	be	AUX
app01-4029	131	32	fed	feed	VERB
app01-4029	131	33	into	into	ADP
app01-4029	131	34	the	the	DET
app01-4029	131	35	network	network	NOUN
app01-4029	131	36	.	.	PUNCT
app01-4029	132	1	the	the	DET
app01-4029	132	2	same	same	ADJ
app01-4029	132	3	network	network	NOUN
app01-4029	132	4	can	can	AUX
app01-4029	132	5	work	work	VERB
app01-4029	132	6	well	well	ADV
app01-4029	132	7	with	with	ADP
app01-4029	132	8	one	one	NUM
app01-4029	132	9	data	datum	NOUN
app01-4029	132	10	and	and	CCONJ
app01-4029	132	11	wrongly	wrongly	ADV
app01-4029	132	12	with	with	ADP
app01-4029	132	13	another	another	PRON
app01-4029	132	14	)	)	PUNCT
app01-4029	132	15	it	it	PRON
app01-4029	132	16	is	be	AUX
app01-4029	132	17	difficult	difficult	ADJ
app01-4029	132	18	to	to	PART
app01-4029	132	19	decide	decide	VERB
app01-4029	132	20	which	which	DET
app01-4029	132	21	variants	variant	NOUN
app01-4029	132	22	is	be	AUX
app01-4029	132	23	the	the	DET
app01-4029	132	24	most	most	ADV
app01-4029	132	25	promising	promising	ADJ
app01-4029	132	26	.	.	PUNCT
app01-4029	133	1	larger	large	ADJ
app01-4029	133	2	testing	testing	NOUN
app01-4029	133	3	is	be	AUX
app01-4029	133	4	needed	need	VERB
app01-4029	133	5	to	to	PART
app01-4029	133	6	understand	understand	VERB
app01-4029	133	7	the	the	DET
app01-4029	133	8	quality	quality	NOUN
app01-4029	133	9	of	of	ADP
app01-4029	133	10	the	the	DET
app01-4029	133	11	methods	method	NOUN
app01-4029	133	12	.	.	PUNCT
app01-4029	134	1	despite	despite	SCONJ
app01-4029	134	2	the	the	DET
app01-4029	134	3	fact	fact	NOUN
app01-4029	134	4	that	that	SCONJ
app01-4029	134	5	the	the	DET
app01-4029	134	6	initial	initial	ADJ
app01-4029	134	7	tests	test	NOUN
app01-4029	134	8	showed	show	VERB
app01-4029	134	9	that	that	SCONJ
app01-4029	134	10	the	the	DET
app01-4029	134	11	signal	signal	ADJ
app01-4029	134	12	prediction	prediction	NOUN
app01-4029	134	13	task	task	NOUN
app01-4029	134	14	is	be	AUX
app01-4029	134	15	better	well	ADV
app01-4029	134	16	fulfilled	fulfil	VERB
app01-4029	134	17	by	by	ADP
app01-4029	134	18	back	back	ADJ
app01-4029	134	19	propagation	propagation	NOUN
app01-4029	134	20	algorithm	algorithm	NOUN
app01-4029	134	21	,	,	PUNCT
app01-4029	134	22	the	the	DET
app01-4029	134	23	homeostatic	homeostatic	ADJ
app01-4029	134	24	neural	neural	ADJ
app01-4029	134	25	network	network	NOUN
app01-4029	134	26	seems	seem	VERB
app01-4029	134	27	as	as	ADP
app01-4029	134	28	a	a	DET
app01-4029	134	29	promising	promising	ADJ
app01-4029	134	30	method	method	NOUN
app01-4029	134	31	for	for	ADP
app01-4029	134	32	modeling	modeling	NOUN
app01-4029	134	33	on	on	ADP
app01-4029	134	34	mental	mental	ADJ
app01-4029	134	35	processes	process	NOUN
app01-4029	134	36	.	.	PUNCT
app01-4029	135	1	of	of	ADP
app01-4029	135	2	course	course	NOUN
app01-4029	135	3	it	it	PRON
app01-4029	135	4	is	be	AUX
app01-4029	135	5	not	not	PART
app01-4029	135	6	possible	possible	ADJ
app01-4029	135	7	to	to	PART
app01-4029	135	8	create	create	VERB
app01-4029	135	9	a	a	DET
app01-4029	135	10	model	model	NOUN
app01-4029	135	11	of	of	ADP
app01-4029	135	12	the	the	DET
app01-4029	135	13	complete	complete	ADJ
app01-4029	135	14	consciousness	consciousness	NOUN
app01-4029	135	15	,	,	PUNCT
app01-4029	135	16	but	but	CCONJ
app01-4029	135	17	it	it	PRON
app01-4029	135	18	is	be	AUX
app01-4029	135	19	possible	possible	ADJ
app01-4029	135	20	to	to	PART
app01-4029	135	21	concentrate	concentrate	VERB
app01-4029	135	22	on	on	ADP
app01-4029	135	23	some	some	DET
app01-4029	135	24	specific	specific	ADJ
app01-4029	135	25	region	region	NOUN
app01-4029	135	26	.	.	PUNCT
app01-4029	136	1	transport	transport	NOUN
app01-4029	136	2	engineering	engineering	NOUN
app01-4029	136	3	brings	bring	VERB
app01-4029	136	4	many	many	ADJ
app01-4029	136	5	possible	possible	ADJ
app01-4029	136	6	applications	application	NOUN
app01-4029	136	7	as	as	ADP
app01-4029	136	8	the	the	DET
app01-4029	136	9	human	human	ADJ
app01-4029	136	10	factor	factor	NOUN
app01-4029	136	11	is	be	AUX
app01-4029	136	12	the	the	DET
app01-4029	136	13	most	most	ADV
app01-4029	136	14	important	important	ADJ
app01-4029	136	15	part	part	NOUN
app01-4029	136	16	in	in	ADP
app01-4029	136	17	many	many	ADJ
app01-4029	136	18	transport	transport	NOUN
app01-4029	136	19	systems	system	NOUN
app01-4029	136	20	.	.	PUNCT
app01-4029	137	1	several	several	ADJ
app01-4029	137	2	processes	process	NOUN
app01-4029	137	3	may	may	AUX
app01-4029	137	4	be	be	AUX
app01-4029	137	5	modeled	model	VERB
app01-4029	137	6	and	and	CCONJ
app01-4029	137	7	predicted	predict	VERB
app01-4029	137	8	by	by	ADP
app01-4029	137	9	the	the	DET
app01-4029	137	10	use	use	NOUN
app01-4029	137	11	of	of	ADP
app01-4029	137	12	this	this	DET
app01-4029	137	13	network	network	NOUN
app01-4029	137	14	.	.	PUNCT
app01-4029	138	1	typical	typical	ADJ
app01-4029	138	2	example	example	NOUN
app01-4029	138	3	is	be	AUX
app01-4029	138	4	a	a	DET
app01-4029	138	5	car	car	NOUN
app01-4029	138	6	driver	driver	NOUN
app01-4029	138	7	,	,	PUNCT
app01-4029	138	8	who	who	PRON
app01-4029	138	9	is	be	AUX
app01-4029	138	10	often	often	ADV
app01-4029	138	11	making	make	VERB
app01-4029	138	12	decisions	decision	NOUN
app01-4029	138	13	with	with	ADP
app01-4029	138	14	a	a	DET
app01-4029	138	15	lack	lack	NOUN
app01-4029	138	16	of	of	ADP
app01-4029	138	17	information	information	NOUN
app01-4029	138	18	and	and	CCONJ
app01-4029	138	19	with	with	ADP
app01-4029	138	20	the	the	DET
app01-4029	138	21	use	use	NOUN
app01-4029	138	22	of	of	ADP
app01-4029	138	23	prior	prior	ADJ
app01-4029	138	24	data	datum	NOUN
app01-4029	138	25	.	.	PUNCT
app01-4029	139	1	it	it	PRON
app01-4029	139	2	is	be	AUX
app01-4029	139	3	difficult	difficult	ADJ
app01-4029	139	4	to	to	PART
app01-4029	139	5	understand	understand	VERB
app01-4029	139	6	the	the	DET
app01-4029	139	7	factors	factor	NOUN
app01-4029	139	8	that	that	PRON
app01-4029	139	9	make	make	VERB
app01-4029	139	10	for	for	ADP
app01-4029	139	11	example	example	NOUN
app01-4029	139	12	the	the	DET
app01-4029	139	13	decision	decision	NOUN
app01-4029	139	14	whether	whether	SCONJ
app01-4029	139	15	to	to	PART
app01-4029	139	16	cross	cross	VERB
app01-4029	139	17	the	the	DET
app01-4029	139	18	crossroads	crossroad	NOUN
app01-4029	139	19	if	if	SCONJ
app01-4029	139	20	the	the	DET
app01-4029	139	21	traffic	traffic	NOUN
app01-4029	139	22	light	light	NOUN
app01-4029	139	23	is	be	AUX
app01-4029	139	24	orange	orange	ADJ
app01-4029	139	25	and	and	CCONJ
app01-4029	139	26	will	will	AUX
app01-4029	139	27	become	become	VERB
app01-4029	139	28	red	red	ADJ
app01-4029	139	29	in	in	ADP
app01-4029	139	30	a	a	DET
app01-4029	139	31	short	short	ADJ
app01-4029	139	32	period	period	NOUN
app01-4029	139	33	of	of	ADP
app01-4029	139	34	time	time	NOUN
app01-4029	139	35	.	.	PUNCT
app01-4029	140	1	in	in	ADP
app01-4029	140	2	such	such	ADJ
app01-4029	140	3	situations	situation	NOUN
app01-4029	140	4	some	some	DET
app01-4029	140	5	drivers	driver	NOUN
app01-4029	140	6	react	react	VERB
app01-4029	140	7	differently	differently	ADV
app01-4029	140	8	even	even	ADV
app01-4029	140	9	if	if	SCONJ
app01-4029	140	10	the	the	DET
app01-4029	140	11	conditions	condition	NOUN
app01-4029	140	12	are	be	AUX
app01-4029	140	13	the	the	DET
app01-4029	140	14	same	same	ADJ
app01-4029	140	15	.	.	PUNCT
app01-4029	141	1	the	the	DET
app01-4029	141	2	analytical	analytical	ADJ
app01-4029	141	3	way	way	NOUN
app01-4029	141	4	to	to	PART
app01-4029	141	5	explain	explain	VERB
app01-4029	141	6	such	such	ADJ
app01-4029	141	7	states	state	NOUN
app01-4029	141	8	is	be	AUX
app01-4029	141	9	quite	quite	ADV
app01-4029	141	10	complex	complex	ADJ
app01-4029	141	11	,	,	PUNCT
app01-4029	141	12	but	but	CCONJ
app01-4029	141	13	it	it	PRON
app01-4029	141	14	is	be	AUX
app01-4029	141	15	possible	possible	ADJ
app01-4029	141	16	to	to	PART
app01-4029	141	17	collect	collect	VERB
app01-4029	141	18	enough	enough	ADJ
app01-4029	141	19	data	datum	NOUN
app01-4029	141	20	(	(	PUNCT
app01-4029	141	21	either	either	CCONJ
app01-4029	141	22	from	from	ADP
app01-4029	141	23	real	real	ADJ
app01-4029	141	24	traffic	traffic	NOUN
app01-4029	141	25	or	or	CCONJ
app01-4029	141	26	from	from	ADP
app01-4029	141	27	a	a	DET
app01-4029	141	28	simulator	simulator	NOUN
app01-4029	141	29	)	)	PUNCT
app01-4029	141	30	to	to	PART
app01-4029	141	31	predict	predict	VERB
app01-4029	141	32	this	this	DET
app01-4029	141	33	type	type	NOUN
app01-4029	141	34	of	of	ADP
app01-4029	141	35	decisions	decision	NOUN
app01-4029	141	36	.	.	PUNCT
app01-4029	142	1	the	the	DET
app01-4029	142	2	neural	neural	ADJ
app01-4029	142	3	network	network	NOUN
app01-4029	142	4	is	be	AUX
app01-4029	142	5	a	a	DET
app01-4029	142	6	good	good	ADJ
app01-4029	142	7	tool	tool	NOUN
app01-4029	142	8	to	to	PART
app01-4029	142	9	process	process	VERB
app01-4029	142	10	this	this	DET
app01-4029	142	11	data	datum	NOUN
app01-4029	142	12	.	.	PUNCT
app01-4029	143	1	once	once	SCONJ
app01-4029	143	2	the	the	DET
app01-4029	143	3	network	network	NOUN
app01-4029	143	4	is	be	AUX
app01-4029	143	5	trained	train	VERB
app01-4029	143	6	for	for	ADP
app01-4029	143	7	certain	certain	ADJ
app01-4029	143	8	tasks	task	NOUN
app01-4029	143	9	in	in	ADP
app01-4029	143	10	a	a	DET
app01-4029	143	11	driver	driver	NOUN
app01-4029	143	12	’s	’s	PART
app01-4029	143	13	decision	decision	NOUN
app01-4029	143	14	making	make	VERB
app01-4029	143	15	processes	process	NOUN
app01-4029	143	16	,	,	PUNCT
app01-4029	143	17	it	it	PRON
app01-4029	143	18	can	can	AUX
app01-4029	143	19	be	be	AUX
app01-4029	143	20	used	use	VERB
app01-4029	143	21	for	for	ADP
app01-4029	143	22	the	the	DET
app01-4029	143	23	investigation	investigation	NOUN
app01-4029	143	24	of	of	ADP
app01-4029	143	25	other	other	ADJ
app01-4029	143	26	decisions	decision	NOUN
app01-4029	143	27	and	and	CCONJ
app01-4029	143	28	behavioral	behavioral	ADJ
app01-4029	143	29	predictions	prediction	NOUN
app01-4029	143	30	.	.	PUNCT
app01-4029	144	1	this	this	PRON
app01-4029	144	2	can	can	AUX
app01-4029	144	3	help	help	VERB
app01-4029	144	4	to	to	PART
app01-4029	144	5	explain	explain	VERB
app01-4029	144	6	and	and	CCONJ
app01-4029	144	7	avoid	avoid	VERB
app01-4029	144	8	danger	danger	NOUN
app01-4029	144	9	situations	situation	NOUN
app01-4029	144	10	caused	cause	VERB
app01-4029	144	11	by	by	ADP
app01-4029	144	12	aggressiveness	aggressiveness	NOUN
app01-4029	144	13	,	,	PUNCT
app01-4029	144	14	fatigue	fatigue	NOUN
app01-4029	144	15	,	,	PUNCT
app01-4029	144	16	emotions	emotion	NOUN
app01-4029	144	17	and	and	CCONJ
app01-4029	144	18	others	other	NOUN
app01-4029	144	19	.	.	PUNCT
app01-4029	145	1	references	reference	NOUN
app01-4029	145	2	[	[	X
app01-4029	145	3	1	1	NUM
app01-4029	145	4	]	]	PUNCT
app01-4029	145	5	m.	m.	NOUN
app01-4029	145	6	růžek	růžek	NOUN
app01-4029	145	7	,	,	PUNCT
app01-4029	145	8	t.	t.	PROPN
app01-4029	145	9	brandejský	brandejský	PROPN
app01-4029	145	10	.	.	PUNCT
app01-4029	146	1	model	model	NOUN
app01-4029	146	2	of	of	ADP
app01-4029	146	3	biological	biological	ADJ
app01-4029	146	4	ann	ann	PROPN
app01-4029	146	5	based	base	VERB
app01-4029	146	6	on	on	ADP
app01-4029	146	7	homeostatic	homeostatic	ADJ
app01-4029	146	8	neurons	neuron	NOUN
app01-4029	146	9	.	.	PUNCT
app01-4029	147	1	in	in	ADP
app01-4029	147	2	12th	12th	ADJ
app01-4029	147	3	wseas	wseas	PROPN
app01-4029	147	4	international	international	ADJ
app01-4029	147	5	conference	conference	NOUN
app01-4029	147	6	on	on	ADP
app01-4029	147	7	neural	neural	ADJ
app01-4029	147	8	networks	network	NOUN
app01-4029	147	9	(	(	PUNCT
app01-4029	147	10	nn’11	nn’11	NOUN
app01-4029	147	11	)	)	PUNCT
app01-4029	147	12	,	,	PUNCT
app01-4029	147	13	isbn	isbn	ADJ
app01-4029	147	14	978	978	NUM
app01-4029	147	15	-	-	SYM
app01-4029	147	16	960	960	NUM
app01-4029	147	17	-	-	PUNCT
app01-4029	147	18	474	474	NUM
app01-4029	147	19	-	-	PUNCT
app01-4029	147	20	292	292	NUM
app01-4029	147	21	-	-	SYM
app01-4029	147	22	9	9	NUM
app01-4029	147	23	,	,	PUNCT
app01-4029	147	24	athens	athens	PROPN
app01-4029	147	25	2011	2011	NUM
app01-4029	147	26	,	,	PUNCT
app01-4029	147	27	pp	pp	ADV
app01-4029	147	28	.	.	PUNCT
app01-4029	148	1	66	66	NUM
app01-4029	148	2	69	69	NUM
app01-4029	148	3	.	.	PUNCT
app01-4029	149	1	[	[	X
app01-4029	149	2	2	2	NUM
app01-4029	149	3	]	]	PUNCT
app01-4029	149	4	m.	m.	NOUN
app01-4029	149	5	růžek	růžek	PROPN
app01-4029	149	6	.	.	PUNCT
app01-4029	150	1	artificial	artificial	ADJ
app01-4029	150	2	neural	neural	ADJ
app01-4029	150	3	network	network	NOUN
app01-4029	150	4	inspired	inspire	VERB
app01-4029	150	5	by	by	ADP
app01-4029	150	6	homeostasis	homeostasis	NOUN
app01-4029	150	7	in	in	ADP
app01-4029	150	8	biological	biological	ADJ
app01-4029	150	9	networks	network	NOUN
app01-4029	150	10	.	.	PUNCT
app01-4029	151	1	in	in	ADP
app01-4029	151	2	proceedings	proceeding	NOUN
app01-4029	151	3	of	of	ADP
app01-4029	151	4	17th	17th	ADJ
app01-4029	151	5	international	international	ADJ
app01-4029	151	6	conference	conference	NOUN
app01-4029	151	7	on	on	ADP
app01-4029	151	8	soft	soft	ADJ
app01-4029	151	9	computing	computing	NOUN
app01-4029	151	10	(	(	PUNCT
app01-4029	151	11	mendel	mendel	PROPN
app01-4029	151	12	2011	2011	NUM
app01-4029	151	13	)	)	PUNCT
app01-4029	152	1	,	,	PUNCT
app01-4029	152	2	isbn	isbn	ADJ
app01-4029	152	3	978	978	NUM
app01-4029	152	4	-	-	SYM
app01-4029	152	5	80	80	NUM
app01-4029	152	6	-	-	PUNCT
app01-4029	152	7	214	214	NUM
app01-4029	152	8	-	-	PUNCT
app01-4029	152	9	4302	4302	NUM
app01-4029	152	10	-	-	SYM
app01-4029	152	11	0	0	NUM
app01-4029	152	12	,	,	PUNCT
app01-4029	152	13	pp	pp	ADJ
app01-4029	152	14	.	.	PUNCT
app01-4029	153	1	232	232	NUM
app01-4029	153	2	235	235	NUM
app01-4029	153	3	.	.	PUNCT
app01-4029	154	1	[	[	X
app01-4029	154	2	3	3	X
app01-4029	154	3	]	]	PUNCT
app01-4029	154	4	m.	m.	NOUN
app01-4029	154	5	růžek	růžek	PROPN
app01-4029	154	6	.	.	PUNCT
app01-4029	155	1	artificial	artificial	ADJ
app01-4029	155	2	neural	neural	ADJ
app01-4029	155	3	networks	network	NOUN
app01-4029	155	4	for	for	ADP
app01-4029	155	5	models	model	NOUN
app01-4029	155	6	of	of	ADP
app01-4029	155	7	driver	driver	NOUN
app01-4029	155	8	’s	’s	PART
app01-4029	155	9	brain	brain	NOUN
app01-4029	155	10	functions	function	NOUN
app01-4029	155	11	.	.	PUNCT
app01-4029	156	1	in	in	ADP
app01-4029	156	2	20th	20th	ADJ
app01-4029	156	3	anniversary	anniversary	NOUN
app01-4029	156	4	of	of	ADP
app01-4029	156	5	the	the	DET
app01-4029	156	6	faculty	faculty	NOUN
app01-4029	156	7	of	of	ADP
app01-4029	156	8	transportation	transportation	NOUN
app01-4029	156	9	sciences	science	NOUN
app01-4029	156	10	,	,	PUNCT
app01-4029	156	11	czech	czech	PROPN
app01-4029	156	12	technical	technical	PROPN
app01-4029	156	13	university	university	PROPN
app01-4029	156	14	in	in	ADP
app01-4029	156	15	prague	prague	NOUN
app01-4029	156	16	–	–	PUNCT
app01-4029	156	17	selected	select	VERB
app01-4029	156	18	papers	paper	NOUN
app01-4029	156	19	,	,	PUNCT
app01-4029	156	20	čvut	čvut	PROPN
app01-4029	156	21	v	v	NUM
app01-4029	156	22	praze	praze	NOUN
app01-4029	156	23	,	,	PUNCT
app01-4029	156	24	2013	2013	NUM
app01-4029	156	25	,	,	PUNCT
app01-4029	156	26	isbn	isbn	ADJ
app01-4029	156	27	978	978	NUM
app01-4029	156	28	-	-	SYM
app01-4029	156	29	80	80	NUM
app01-4029	156	30	-	-	PUNCT
app01-4029	156	31	01	01	NUM
app01-4029	156	32	-	-	PUNCT
app01-4029	156	33	05320	05320	NUM
app01-4029	156	34	-	-	SYM
app01-4029	156	35	1	1	NUM
app01-4029	156	36	,	,	PUNCT
app01-4029	156	37	pp	pp	ADJ
app01-4029	156	38	.	.	PUNCT
app01-4029	156	39	207	207	NUM
app01-4029	156	40	211	211	NUM
app01-4029	156	41	.	.	PUNCT
app01-4029	157	1	[	[	X
app01-4029	157	2	4	4	NUM
app01-4029	157	3	]	]	PUNCT
app01-4029	157	4	m.	m.	NOUN
app01-4029	157	5	růžek	růžek	NOUN
app01-4029	157	6	.	.	PUNCT
app01-4029	158	1	modeling	modeling	NOUN
app01-4029	158	2	of	of	ADP
app01-4029	158	3	eeg	eeg	PROPN
app01-4029	158	4	signal	signal	NOUN
app01-4029	158	5	with	with	ADP
app01-4029	158	6	homeostatic	homeostatic	ADJ
app01-4029	158	7	neural	neural	ADJ
app01-4029	158	8	network	network	NOUN
app01-4029	158	9	.	.	PUNCT
app01-4029	159	1	in	in	ADP
app01-4029	159	2	nostradamus	nostradamus	PROPN
app01-4029	159	3	2013	2013	NUM
app01-4029	159	4	:	:	PUNCT
app01-4029	159	5	prediction	prediction	NOUN
app01-4029	159	6	,	,	PUNCT
app01-4029	159	7	modeling	modeling	NOUN
app01-4029	159	8	and	and	CCONJ
app01-4029	159	9	analysis	analysis	NOUN
app01-4029	159	10	of	of	ADP
app01-4029	159	11	complex	complex	ADJ
app01-4029	159	12	systems	system	NOUN
app01-4029	159	13	,	,	PUNCT
app01-4029	159	14	ostrava	ostrava	PROPN
app01-4029	159	15	2013	2013	NUM
app01-4029	159	16	,	,	PUNCT
app01-4029	159	17	isbn	isbn	ADJ
app01-4029	159	18	978	978	NUM
app01-4029	159	19	-	-	SYM
app01-4029	159	20	3	3	NUM
app01-4029	159	21	-	-	NUM
app01-4029	159	22	319	319	NUM
app01-4029	159	23	-	-	PUNCT
app01-4029	159	24	00541	00541	NUM
app01-4029	159	25	-	-	SYM
app01-4029	159	26	6	6	NUM
app01-4029	159	27	pp	pp	NOUN
app01-4029	159	28	.	.	PUNCT
app01-4029	160	1	175	175	NUM
app01-4029	160	2	180	180	NUM
app01-4029	160	3	.	.	PUNCT
app01-4029	161	1	[	[	X
app01-4029	161	2	5	5	NUM
app01-4029	161	3	]	]	PUNCT
app01-4029	161	4	m.	m.	NOUN
app01-4029	161	5	růžek	růžek	NOUN
app01-4029	161	6	,	,	PUNCT
app01-4029	161	7	t.	t.	PROPN
app01-4029	161	8	brandejský	brandejský	PROPN
app01-4029	161	9	.	.	PUNCT
app01-4029	162	1	model	model	NOUN
app01-4029	162	2	of	of	ADP
app01-4029	162	3	homeostatic	homeostatic	ADJ
app01-4029	162	4	artificial	artificial	ADJ
app01-4029	162	5	neuron	neuron	NOUN
app01-4029	162	6	.	.	PUNCT
app01-4029	163	1	in	in	ADP
app01-4029	163	2	neural	neural	ADJ
app01-4029	163	3	networks	network	NOUN
app01-4029	163	4	,	,	PUNCT
app01-4029	163	5	fuzzy	fuzzy	ADJ
app01-4029	163	6	systems	system	NOUN
app01-4029	163	7	&	&	CCONJ
app01-4029	163	8	evolutionary	evolutionary	ADJ
app01-4029	163	9	computing	computing	NOUN
app01-4029	163	10	,	,	PUNCT
app01-4029	163	11	isbn	isbn	ADJ
app01-4029	163	12	978	978	NUM
app01-4029	163	13	-	-	SYM
app01-4029	163	14	960	960	NUM
app01-4029	163	15	-	-	PUNCT
app01-4029	163	16	474	474	NUM
app01-4029	163	17	-	-	PUNCT
app01-4029	163	18	195	195	NUM
app01-4029	163	19	-	-	PUNCT
app01-4029	163	20	3	3	NUM
app01-4029	163	21	,	,	PUNCT
app01-4029	163	22	athens	athens	PROPN
app01-4029	163	23	2010	2010	NUM
app01-4029	163	24	,	,	PUNCT
app01-4029	163	25	pp	pp	ADJ
app01-4029	163	26	.	.	PUNCT
app01-4029	163	27	145	145	NUM
app01-4029	163	28	148	148	NUM
app01-4029	163	29	.	.	PUNCT
app01-4029	163	30	103	103	NUM
app01-4029	163	31	acta	acta	PROPN
app01-4029	163	32	polytechnica	polytechnica	PROPN
app01-4029	163	33	ctu	ctu	NOUN
app01-4029	163	34	proceedings	proceeding	NOUN
app01-4029	163	35	12:99–103	12:99–103	NUM
app01-4029	163	36	,	,	PUNCT
app01-4029	163	37	2017	2017	NUM
app01-4029	163	38	1	1	NUM
app01-4029	163	39	introduction	introduction	NOUN
app01-4029	163	40	2	2	NUM
app01-4029	163	41	new	new	ADJ
app01-4029	163	42	solution	solution	NOUN
app01-4029	163	43	–	–	PUNCT
app01-4029	163	44	homeostatical	homeostatical	ADJ
app01-4029	163	45	neural	neural	ADJ
app01-4029	163	46	network	network	NOUN
app01-4029	163	47	3	3	NUM
app01-4029	163	48	criterions	criterion	NOUN
app01-4029	163	49	for	for	ADP
app01-4029	163	50	optimization	optimization	NOUN
app01-4029	163	51	4	4	NUM
app01-4029	163	52	searching	search	VERB
app01-4029	163	53	the	the	DET
app01-4029	163	54	one	one	NUM
app01-4029	163	55	neuron	neuron	NOUN
app01-4029	163	56	maximum	maximum	ADJ
app01-4029	163	57	–	–	PUNCT
app01-4029	163	58	the	the	DET
app01-4029	163	59	second	second	ADJ
app01-4029	163	60	extreme	extreme	ADJ
app01-4029	163	61	5	5	NUM
app01-4029	163	62	variants	variant	NOUN
app01-4029	163	63	of	of	ADP
app01-4029	163	64	homeostatical	homeostatical	ADJ
app01-4029	163	65	neural	neural	ADJ
app01-4029	163	66	network	network	NOUN
app01-4029	163	67	6	6	NUM
app01-4029	163	68	problems	problem	NOUN
app01-4029	163	69	of	of	ADP
app01-4029	163	70	the	the	DET
app01-4029	163	71	idea	idea	NOUN
app01-4029	163	72	of	of	ADP
app01-4029	163	73	homeostatical	homeostatical	ADJ
app01-4029	163	74	learning	learn	VERB
app01-4029	163	75	7	7	NUM
app01-4029	163	76	conclusions	conclusion	NOUN
app01-4029	163	77	references	reference	NOUN