id	sid	tid	token	lemma	pos
ap-1785	1	1	acta	acta	PROPN
ap-1785	1	2	polytechnica	polytechnica	PROPN
ap-1785	1	3	acta	acta	PROPN
ap-1785	1	4	polytechnica	polytechnica	PROPN
ap-1785	1	5	53(2):75–78	53(2):75–78	NUM
ap-1785	1	6	,	,	PUNCT
ap-1785	1	7	2013	2013	NUM
ap-1785	1	8	©	©	PROPN
ap-1785	1	9	czech	czech	PROPN
ap-1785	1	10	technical	technical	PROPN
ap-1785	1	11	university	university	PROPN
ap-1785	1	12	in	in	ADP
ap-1785	1	13	prague	prague	PROPN
ap-1785	1	14	,	,	PUNCT
ap-1785	1	15	2013	2013	NUM
ap-1785	1	16	available	available	ADJ
ap-1785	1	17	online	online	ADV
ap-1785	1	18	at	at	ADP
ap-1785	1	19	http://ctn.cvut.cz/ap/	http://ctn.cvut.cz/ap/	PROPN
ap-1785	1	20	fractal	fractal	ADJ
ap-1785	1	21	dimension	dimension	NOUN
ap-1785	1	22	estimation	estimation	NOUN
ap-1785	1	23	in	in	ADP
ap-1785	1	24	diagnosing	diagnose	VERB
ap-1785	1	25	alzheimer	alzheimer	PROPN
ap-1785	1	26	’s	’s	PART
ap-1785	1	27	disease	disease	PROPN
ap-1785	1	28	václav	václav	PROPN
ap-1785	1	29	hubata	hubata	PROPN
ap-1785	1	30	-	-	PUNCT
ap-1785	1	31	vaceka,∗	vaceka,∗	PROPN
ap-1785	1	32	,	,	PUNCT
ap-1785	1	33	jaromír	jaromír	NOUN
ap-1785	1	34	kukala	kukala	PROPN
ap-1785	1	35	,	,	PUNCT
ap-1785	1	36	robert	robert	PROPN
ap-1785	1	37	rusinab	rusinab	PROPN
ap-1785	1	38	,	,	PUNCT
ap-1785	1	39	marie	marie	PROPN
ap-1785	1	40	buncovác	buncovác	PROPN
ap-1785	1	41	a	a	DET
ap-1785	1	42	ctu	ctu	NOUN
ap-1785	1	43	,	,	PUNCT
ap-1785	1	44	faculty	faculty	NOUN
ap-1785	1	45	of	of	ADP
ap-1785	1	46	nuclear	nuclear	ADJ
ap-1785	1	47	sciences	science	NOUN
ap-1785	1	48	and	and	CCONJ
ap-1785	1	49	physical	physical	ADJ
ap-1785	1	50	engineering	engineering	NOUN
ap-1785	1	51	,	,	PUNCT
ap-1785	1	52	department	department	NOUN
ap-1785	1	53	of	of	ADP
ap-1785	1	54	software	software	NOUN
ap-1785	1	55	engineering	engineering	NOUN
ap-1785	1	56	in	in	ADP
ap-1785	1	57	economics	economic	NOUN
ap-1785	1	58	,	,	PUNCT
ap-1785	1	59	břehová	břehová	VERB
ap-1785	1	60	7	7	NUM
ap-1785	1	61	,	,	PUNCT
ap-1785	1	62	115	115	NUM
ap-1785	1	63	19	19	NUM
ap-1785	1	64	praha	praha	NOUN
ap-1785	1	65	1	1	NUM
ap-1785	1	66	,	,	PUNCT
ap-1785	1	67	czech	czech	PROPN
ap-1785	1	68	republic	republic	PROPN
ap-1785	1	69	b	b	PROPN
ap-1785	1	70	thomayer	thomayer	PROPN
ap-1785	1	71	’s	’s	PART
ap-1785	1	72	hospital	hospital	NOUN
ap-1785	1	73	,	,	PUNCT
ap-1785	1	74	vídeňská	vídeňská	NOUN
ap-1785	1	75	800	800	NUM
ap-1785	1	76	,	,	PUNCT
ap-1785	1	77	140	140	NUM
ap-1785	1	78	59	59	NUM
ap-1785	1	79	praha	praha	NOUN
ap-1785	1	80	4	4	NUM
ap-1785	1	81	–	–	PUNCT
ap-1785	1	82	krč	krč	NOUN
ap-1785	1	83	,	,	PUNCT
ap-1785	1	84	czech	czech	PROPN
ap-1785	1	85	republic	republic	PROPN
ap-1785	1	86	c	c	PROPN
ap-1785	1	87	institute	institute	PROPN
ap-1785	1	88	for	for	ADP
ap-1785	1	89	clinical	clinical	ADJ
ap-1785	1	90	and	and	CCONJ
ap-1785	1	91	experimental	experimental	ADJ
ap-1785	1	92	medicine	medicine	NOUN
ap-1785	1	93	,	,	PUNCT
ap-1785	1	94	vídeňská	vídeňská	ADJ
ap-1785	1	95	1958/9	1958/9	NUM
ap-1785	1	96	,	,	PUNCT
ap-1785	1	97	140	140	NUM
ap-1785	1	98	21	21	NUM
ap-1785	1	99	praha	praha	NOUN
ap-1785	1	100	4	4	NUM
ap-1785	1	101	–	–	PUNCT
ap-1785	1	102	krč	krč	NOUN
ap-1785	1	103	,	,	PUNCT
ap-1785	1	104	czech	czech	PROPN
ap-1785	1	105	republic	republic	NOUN
ap-1785	1	106	∗	∗	NOUN
ap-1785	1	107	corresponding	correspond	VERB
ap-1785	1	108	author	author	NOUN
ap-1785	1	109	:	:	PUNCT
ap-1785	1	110	hubatvac@fjfi.cvut.cz	hubatvac@fjfi.cvut.cz	NOUN
ap-1785	1	111	abstract	abstract	NOUN
ap-1785	1	112	.	.	PUNCT
ap-1785	2	1	estimated	estimate	VERB
ap-1785	2	2	entropies	entropy	NOUN
ap-1785	2	3	from	from	ADP
ap-1785	2	4	a	a	DET
ap-1785	2	5	limited	limited	ADJ
ap-1785	2	6	data	datum	NOUN
ap-1785	2	7	set	set	VERB
ap-1785	2	8	are	be	AUX
ap-1785	2	9	always	always	ADV
ap-1785	2	10	biased	biased	ADJ
ap-1785	2	11	.	.	PUNCT
ap-1785	3	1	consequently	consequently	ADV
ap-1785	3	2	,	,	PUNCT
ap-1785	3	3	it	it	PRON
ap-1785	3	4	is	be	AUX
ap-1785	3	5	not	not	PART
ap-1785	3	6	a	a	DET
ap-1785	3	7	trivial	trivial	ADJ
ap-1785	3	8	task	task	NOUN
ap-1785	3	9	to	to	PART
ap-1785	3	10	calculate	calculate	VERB
ap-1785	3	11	the	the	DET
ap-1785	3	12	entropy	entropy	NOUN
ap-1785	3	13	in	in	ADP
ap-1785	3	14	real	real	ADJ
ap-1785	3	15	tasks	task	NOUN
ap-1785	3	16	.	.	PUNCT
ap-1785	4	1	in	in	ADP
ap-1785	4	2	this	this	DET
ap-1785	4	3	paper	paper	NOUN
ap-1785	4	4	,	,	PUNCT
ap-1785	4	5	we	we	PRON
ap-1785	4	6	used	use	VERB
ap-1785	4	7	a	a	DET
ap-1785	4	8	generalized	generalized	ADJ
ap-1785	4	9	definition	definition	NOUN
ap-1785	4	10	of	of	ADP
ap-1785	4	11	entropy	entropy	NOUN
ap-1785	4	12	to	to	PART
ap-1785	4	13	evaluate	evaluate	VERB
ap-1785	4	14	the	the	DET
ap-1785	4	15	hartley	hartley	NOUN
ap-1785	4	16	,	,	PUNCT
ap-1785	4	17	shannon	shannon	PROPN
ap-1785	4	18	,	,	PUNCT
ap-1785	4	19	and	and	CCONJ
ap-1785	4	20	collision	collision	NOUN
ap-1785	4	21	entropies	entropy	NOUN
ap-1785	4	22	.	.	PUNCT
ap-1785	5	1	moreover	moreover	ADV
ap-1785	5	2	,	,	PUNCT
ap-1785	5	3	we	we	PRON
ap-1785	5	4	applied	apply	VERB
ap-1785	5	5	the	the	DET
ap-1785	5	6	miller	miller	PROPN
ap-1785	5	7	and	and	CCONJ
ap-1785	5	8	harris	harris	PROPN
ap-1785	5	9	estimations	estimation	NOUN
ap-1785	5	10	of	of	ADP
ap-1785	5	11	shannon	shannon	PROPN
ap-1785	5	12	entropy	entropy	PROPN
ap-1785	5	13	,	,	PUNCT
ap-1785	5	14	which	which	PRON
ap-1785	5	15	are	be	AUX
ap-1785	5	16	well	well	ADV
ap-1785	5	17	known	know	VERB
ap-1785	5	18	bias	bias	NOUN
ap-1785	5	19	approaches	approach	NOUN
ap-1785	5	20	based	base	VERB
ap-1785	5	21	on	on	ADP
ap-1785	5	22	taylor	taylor	PROPN
ap-1785	5	23	series	series	PROPN
ap-1785	5	24	.	.	PUNCT
ap-1785	6	1	finally	finally	ADV
ap-1785	6	2	,	,	PUNCT
ap-1785	6	3	these	these	DET
ap-1785	6	4	estimates	estimate	NOUN
ap-1785	6	5	were	be	AUX
ap-1785	6	6	improved	improve	VERB
ap-1785	6	7	by	by	ADP
ap-1785	6	8	bayesian	bayesian	NOUN
ap-1785	6	9	estimation	estimation	NOUN
ap-1785	6	10	of	of	ADP
ap-1785	6	11	individual	individual	ADJ
ap-1785	6	12	probabilities	probability	NOUN
ap-1785	6	13	.	.	PUNCT
ap-1785	7	1	these	these	DET
ap-1785	7	2	methods	method	NOUN
ap-1785	7	3	were	be	AUX
ap-1785	7	4	tested	test	VERB
ap-1785	7	5	and	and	CCONJ
ap-1785	7	6	used	use	VERB
ap-1785	7	7	for	for	ADP
ap-1785	7	8	recognizing	recognize	VERB
ap-1785	7	9	alzheimer	alzheimer	PROPN
ap-1785	7	10	’s	’s	PART
ap-1785	7	11	disease	disease	NOUN
ap-1785	7	12	,	,	PUNCT
ap-1785	7	13	using	use	VERB
ap-1785	7	14	the	the	DET
ap-1785	7	15	relationship	relationship	NOUN
ap-1785	7	16	between	between	ADP
ap-1785	7	17	entropy	entropy	NOUN
ap-1785	7	18	and	and	CCONJ
ap-1785	7	19	the	the	DET
ap-1785	7	20	fractal	fractal	ADJ
ap-1785	7	21	dimension	dimension	NOUN
ap-1785	7	22	to	to	PART
ap-1785	7	23	obtain	obtain	VERB
ap-1785	7	24	fractal	fractal	ADJ
ap-1785	7	25	dimensions	dimension	NOUN
ap-1785	7	26	of	of	ADP
ap-1785	7	27	3d	3d	NUM
ap-1785	7	28	brain	brain	NOUN
ap-1785	7	29	scans	scan	NOUN
ap-1785	7	30	.	.	PUNCT
ap-1785	8	1	keywords	keyword	NOUN
ap-1785	8	2	:	:	PUNCT
ap-1785	8	3	entropy	entropy	PROPN
ap-1785	8	4	,	,	PUNCT
ap-1785	8	5	fractal	fractal	ADJ
ap-1785	8	6	dimension	dimension	NOUN
ap-1785	8	7	,	,	PUNCT
ap-1785	8	8	alzheimer	alzheimer	PROPN
ap-1785	8	9	’s	’s	PART
ap-1785	8	10	disease	disease	NOUN
ap-1785	8	11	,	,	PUNCT
ap-1785	8	12	boxcounting	boxcounting	ADJ
ap-1785	8	13	,	,	PUNCT
ap-1785	8	14	rényi	rényi	NOUN
ap-1785	8	15	entopy	entopy	NOUN
ap-1785	8	16	.	.	PUNCT
ap-1785	9	1	1	1	X
ap-1785	9	2	.	.	X
ap-1785	9	3	introduction	introduction	NOUN
ap-1785	9	4	before	before	ADP
ap-1785	9	5	explaning	explane	VERB
ap-1785	9	6	the	the	DET
ap-1785	9	7	relationship	relationship	NOUN
ap-1785	9	8	between	between	ADP
ap-1785	9	9	entropy	entropy	NOUN
ap-1785	9	10	and	and	CCONJ
ap-1785	9	11	dimension	dimension	NOUN
ap-1785	9	12	,	,	PUNCT
ap-1785	9	13	we	we	PRON
ap-1785	9	14	have	have	VERB
ap-1785	9	15	to	to	PART
ap-1785	9	16	introduce	introduce	VERB
ap-1785	9	17	the	the	DET
ap-1785	9	18	term	term	NOUN
ap-1785	9	19	of	of	ADP
ap-1785	9	20	dimension	dimension	NOUN
ap-1785	9	21	.	.	PUNCT
ap-1785	10	1	let	let	VERB
ap-1785	10	2	d	d	X
ap-1785	10	3	∈	∈	PROPN
ap-1785	10	4	n	n	AUX
ap-1785	10	5	be	be	AUX
ap-1785	10	6	a	a	DET
ap-1785	10	7	dimension	dimension	NOUN
ap-1785	10	8	of	of	ADP
ap-1785	10	9	euclidean	euclidean	ADJ
ap-1785	10	10	space	space	NOUN
ap-1785	10	11	where	where	SCONJ
ap-1785	10	12	a	a	DET
ap-1785	10	13	d	d	ADJ
ap-1785	10	14	-	-	ADJ
ap-1785	10	15	dimensional	dimensional	ADJ
ap-1785	10	16	unit	unit	NOUN
ap-1785	10	17	hypercube	hypercube	NOUN
ap-1785	10	18	is	be	AUX
ap-1785	10	19	placed	place	VERB
ap-1785	10	20	.	.	PUNCT
ap-1785	11	1	let	let	VERB
ap-1785	11	2	m	m	PRON
ap-1785	11	3	∈	∈	PROPN
ap-1785	11	4	n	n	AUX
ap-1785	11	5	be	be	AUX
ap-1785	11	6	resolution	resolution	NOUN
ap-1785	11	7	and	and	CCONJ
ap-1785	11	8	a	a	DET
ap-1785	11	9	=	=	ADJ
ap-1785	11	10	1	1	NUM
ap-1785	11	11	/	/	SYM
ap-1785	11	12	m	m	VERB
ap-1785	11	13	be	be	AUX
ap-1785	11	14	edge	edge	VERB
ap-1785	11	15	the	the	DET
ap-1785	11	16	length	length	NOUN
ap-1785	11	17	of	of	ADP
ap-1785	11	18	covering	cover	VERB
ap-1785	11	19	hypercubes	hypercube	NOUN
ap-1785	11	20	of	of	ADP
ap-1785	11	21	the	the	DET
ap-1785	11	22	same	same	ADJ
ap-1785	11	23	dimension	dimension	NOUN
ap-1785	11	24	d.	d.	PROPN
ap-1785	11	25	the	the	DET
ap-1785	11	26	number	number	NOUN
ap-1785	11	27	of	of	ADP
ap-1785	11	28	covering	cover	VERB
ap-1785	11	29	elements	element	NOUN
ap-1785	11	30	is	be	AUX
ap-1785	11	31	given	give	VERB
ap-1785	11	32	by	by	ADP
ap-1785	11	33	n	n	PROPN
ap-1785	11	34	=	=	SYM
ap-1785	11	35	n(a	n(a	PROPN
ap-1785	11	36	)	)	PUNCT
ap-1785	11	37	=	=	PUNCT
ap-1785	12	1	a−d	a−d	PROPN
ap-1785	12	2	.	.	PUNCT
ap-1785	13	1	knowledge	knowledge	NOUN
ap-1785	13	2	of	of	ADP
ap-1785	13	3	n	n	PROPN
ap-1785	13	4	for	for	SCONJ
ap-1785	13	5	fixed	fix	VERB
ap-1785	13	6	a	a	DET
ap-1785	13	7	enables	enable	NOUN
ap-1785	13	8	direct	direct	ADJ
ap-1785	13	9	calculation	calculation	NOUN
ap-1785	13	10	of	of	ADP
ap-1785	13	11	the	the	DET
ap-1785	13	12	hypercube	hypercube	ADJ
ap-1785	13	13	dimension	dimension	NOUN
ap-1785	13	14	according	accord	VERB
ap-1785	13	15	to	to	ADP
ap-1785	13	16	ln	ln	PROPN
ap-1785	13	17	n(a	n(a	NOUN
ap-1785	13	18	)	)	PUNCT
ap-1785	14	1	=	=	VERB
ap-1785	14	2	−d	−d	VERB
ap-1785	14	3	ln	ln	ADV
ap-1785	14	4	a	a	DET
ap-1785	14	5	d	d	X
ap-1785	14	6	=	=	SYM
ap-1785	14	7	ln	ln	PROPN
ap-1785	14	8	n(a	n(a	PROPN
ap-1785	14	9	)	)	PUNCT
ap-1785	14	10	ln	ln	ADV
ap-1785	14	11	1	1	NUM
ap-1785	14	12	a	a	NOUN
ap-1785	14	13	.	.	PUNCT
ap-1785	15	1	(	(	PUNCT
ap-1785	15	2	1	1	X
ap-1785	15	3	)	)	PUNCT
ap-1785	15	4	the	the	DET
ap-1785	15	5	very	very	ADV
ap-1785	15	6	popular	popular	ADJ
ap-1785	15	7	boxcounting	boxcounting	ADJ
ap-1785	15	8	method	method	NOUN
ap-1785	15	9	[	[	X
ap-1785	15	10	1	1	NUM
ap-1785	15	11	]	]	PUNCT
ap-1785	15	12	is	be	AUX
ap-1785	15	13	based	base	VERB
ap-1785	15	14	on	on	ADP
ap-1785	15	15	the	the	DET
ap-1785	15	16	generalization	generalization	NOUN
ap-1785	15	17	of	of	ADP
ap-1785	15	18	(	(	PUNCT
ap-1785	15	19	1	1	NUM
ap-1785	15	20	)	)	PUNCT
ap-1785	15	21	to	to	ADP
ap-1785	15	22	the	the	DET
ap-1785	15	23	form	form	NOUN
ap-1785	15	24	ln	ln	ADP
ap-1785	15	25	n(a	n(a	NOUN
ap-1785	15	26	)	)	PUNCT
ap-1785	15	27	=	=	SYM
ap-1785	15	28	a0	a0	PROPN
ap-1785	16	1	−d0	−d0	PROPN
ap-1785	16	2	ln	ln	PROPN
ap-1785	16	3	a	a	PROPN
ap-1785	16	4	and	and	CCONJ
ap-1785	16	5	its	its	PRON
ap-1785	16	6	application	application	NOUN
ap-1785	16	7	to	to	ADP
ap-1785	16	8	the	the	DET
ap-1785	16	9	boundary	boundary	NOUN
ap-1785	16	10	of	of	ADP
ap-1785	16	11	any	any	DET
ap-1785	16	12	set	set	NOUN
ap-1785	17	1	f	f	PROPN
ap-1785	17	2	⊂	⊂	PROPN
ap-1785	17	3	rd	rd	PROPN
ap-1785	17	4	.	.	PROPN
ap-1785	18	1	as	as	SCONJ
ap-1785	18	2	will	will	AUX
ap-1785	18	3	be	be	AUX
ap-1785	18	4	shown	show	VERB
ap-1785	18	5	in	in	ADP
ap-1785	18	6	the	the	DET
ap-1785	18	7	next	next	ADJ
ap-1785	18	8	section	section	NOUN
ap-1785	18	9	,	,	PUNCT
ap-1785	18	10	the	the	DET
ap-1785	18	11	quantity	quantity	NOUN
ap-1785	18	12	ln	ln	ADP
ap-1785	18	13	n(a	n(a	PROPN
ap-1785	18	14	)	)	PUNCT
ap-1785	18	15	is	be	AUX
ap-1785	18	16	an	an	DET
ap-1785	18	17	estimate	estimate	NOUN
ap-1785	18	18	of	of	ADP
ap-1785	18	19	the	the	DET
ap-1785	18	20	hartley	hartley	PROPN
ap-1785	18	21	entropy	entropy	PROPN
ap-1785	18	22	.	.	PUNCT
ap-1785	19	1	2	2	X
ap-1785	19	2	.	.	X
ap-1785	19	3	rényi	rényi	PROPN
ap-1785	19	4	entropy	entropy	PROPN
ap-1785	19	5	using	use	VERB
ap-1785	19	6	a	a	DET
ap-1785	19	7	natural	natural	ADJ
ap-1785	19	8	logarithm	logarithm	NOUN
ap-1785	19	9	instead	instead	ADV
ap-1785	19	10	of	of	ADP
ap-1785	19	11	a	a	DET
ap-1785	19	12	binary	binary	ADJ
ap-1785	19	13	logarithm	logarithm	NOUN
ap-1785	19	14	,	,	PUNCT
ap-1785	19	15	we	we	PRON
ap-1785	19	16	can	can	AUX
ap-1785	19	17	follow	follow	VERB
ap-1785	19	18	in	in	ADP
ap-1785	19	19	the	the	DET
ap-1785	19	20	definition	definition	NOUN
ap-1785	19	21	of	of	ADP
ap-1785	19	22	rényi	rényi	PROPN
ap-1785	19	23	entropy	entropy	PROPN
ap-1785	19	24	.	.	PUNCT
ap-1785	20	1	let	let	VERB
ap-1785	20	2	k	k	PROPN
ap-1785	20	3	∈	∈	PROPN
ap-1785	20	4	n	n	AUX
ap-1785	20	5	be	be	AUX
ap-1785	20	6	number	number	NOUN
ap-1785	20	7	of	of	ADP
ap-1785	20	8	events	event	NOUN
ap-1785	20	9	,	,	PUNCT
ap-1785	20	10	pj	pj	PROPN
ap-1785	20	11	>	>	X
ap-1785	20	12	0	0	PUNCT
ap-1785	20	13	be	be	AUX
ap-1785	20	14	their	their	PRON
ap-1785	20	15	probabilities	probability	NOUN
ap-1785	20	16	for	for	ADP
ap-1785	20	17	j	j	PROPN
ap-1785	20	18	=	=	SYM
ap-1785	20	19	1	1	PROPN
ap-1785	20	20	,	,	PUNCT
ap-1785	20	21	.	.	PUNCT
ap-1785	20	22	.	.	PUNCT
ap-1785	21	1	.	.	PUNCT
ap-1785	22	1	,	,	PUNCT
ap-1785	22	2	k	k	PROPN
ap-1785	22	3	satisfying	satisfy	VERB
ap-1785	22	4	∑k	∑k	PROPN
ap-1785	22	5	j=1	j=1	PROPN
ap-1785	22	6	pj	pj	PROPN
ap-1785	22	7	=	=	SYM
ap-1785	22	8	1	1	PROPN
ap-1785	22	9	,	,	PUNCT
ap-1785	22	10	and	and	CCONJ
ap-1785	22	11	q	q	PROPN
ap-1785	22	12	∈	∈	PROPN
ap-1785	22	13	r.	r.	NOUN
ap-1785	22	14	we	we	PRON
ap-1785	22	15	can	can	AUX
ap-1785	22	16	define	define	VERB
ap-1785	22	17	rényi	rényi	NOUN
ap-1785	22	18	entropy	entropy	NOUN
ap-1785	23	1	[	[	X
ap-1785	23	2	2	2	NUM
ap-1785	23	3	]	]	PUNCT
ap-1785	23	4	as	as	ADP
ap-1785	23	5	hq	hq	NOUN
ap-1785	23	6	=	=	PROPN
ap-1785	23	7	ln	ln	PROPN
ap-1785	23	8	∑k	∑k	PROPN
ap-1785	24	1	j=1	j=1	PROPN
ap-1785	24	2	p	p	X
ap-1785	24	3	q	q	X
ap-1785	24	4	j	j	PROPN
ap-1785	24	5	1−	1−	NUM
ap-1785	24	6	q	q	NOUN
ap-1785	24	7	,	,	PUNCT
ap-1785	24	8	which	which	PRON
ap-1785	24	9	is	be	AUX
ap-1785	24	10	a	a	DET
ap-1785	24	11	generalization	generalization	NOUN
ap-1785	24	12	of	of	ADP
ap-1785	24	13	shannon	shannon	PROPN
ap-1785	24	14	entropy	entropy	PROPN
ap-1785	24	15	.	.	PUNCT
ap-1785	25	1	in	in	ADP
ap-1785	25	2	respect	respect	NOUN
ap-1785	25	3	of	of	ADP
ap-1785	25	4	q	q	NOUN
ap-1785	25	5	,	,	PUNCT
ap-1785	25	6	we	we	PRON
ap-1785	25	7	obtain	obtain	VERB
ap-1785	25	8	the	the	DET
ap-1785	25	9	specific	specific	ADJ
ap-1785	25	10	entropies	entropy	NOUN
ap-1785	25	11	:	:	PUNCT
ap-1785	25	12	•	•	NUM
ap-1785	25	13	hartley	hartley	PROPN
ap-1785	25	14	entropy	entropy	PROPN
ap-1785	26	1	[	[	X
ap-1785	26	2	3	3	X
ap-1785	26	3	]	]	PUNCT
ap-1785	26	4	for	for	ADP
ap-1785	26	5	q	q	NOUN
ap-1785	26	6	=	=	SYM
ap-1785	26	7	0	0	PUNCT
ap-1785	26	8	as	as	ADP
ap-1785	26	9	h0	h0	NOUN
ap-1785	26	10	=	=	PROPN
ap-1785	26	11	ln	ln	ADJ
ap-1785	26	12	∑	∑	PUNCT
ap-1785	26	13	pj>0	pj>0	PROPN
ap-1785	26	14	1	1	NUM
ap-1785	26	15	=	=	SYM
ap-1785	26	16	ln	ln	PROPN
ap-1785	26	17	k∑	k∑	PROPN
ap-1785	26	18	j>0	j>0	PROPN
ap-1785	26	19	1	1	NUM
ap-1785	26	20	=	=	SYM
ap-1785	26	21	ln	ln	NOUN
ap-1785	26	22	k	k	NOUN
ap-1785	26	23	=	=	PUNCT
ap-1785	26	24	ln	ln	PROPN
ap-1785	26	25	n(a	n(a	NOUN
ap-1785	26	26	)	)	PUNCT
ap-1785	26	27	;	;	PUNCT
ap-1785	26	28	•	•	NUM
ap-1785	26	29	shannon	shannon	PROPN
ap-1785	26	30	entropy	entropy	PROPN
ap-1785	27	1	[	[	X
ap-1785	27	2	4	4	NUM
ap-1785	27	3	]	]	PUNCT
ap-1785	27	4	for	for	ADP
ap-1785	27	5	q	q	NOUN
ap-1785	27	6	→	→	SYM
ap-1785	27	7	1	1	NUM
ap-1785	27	8	as	as	ADP
ap-1785	27	9	h1	h1	PROPN
ap-1785	27	10	=	=	PROPN
ap-1785	27	11	lim	lim	PROPN
ap-1785	27	12	q→1	q→1	PROPN
ap-1785	27	13	hq	hq	PROPN
ap-1785	28	1	=	=	PUNCT
ap-1785	29	1	−	−	PROPN
ap-1785	30	1	∑	∑	INTJ
ap-1785	30	2	j=1	j=1	PROPN
ap-1785	30	3	pj	pj	PROPN
ap-1785	30	4	ln	ln	PROPN
ap-1785	30	5	pj	pj	PROPN
ap-1785	30	6	;	;	PUNCT
ap-1785	30	7	•	•	NUM
ap-1785	30	8	collision	collision	NOUN
ap-1785	30	9	entropy	entropy	NOUN
ap-1785	31	1	[	[	X
ap-1785	31	2	2	2	NUM
ap-1785	31	3	]	]	PUNCT
ap-1785	31	4	for	for	ADP
ap-1785	31	5	q	q	NOUN
ap-1785	31	6	=	=	SYM
ap-1785	31	7	2	2	NUM
ap-1785	31	8	as	as	ADP
ap-1785	31	9	h2	h2	NOUN
ap-1785	31	10	=	=	PUNCT
ap-1785	31	11	−	−	PROPN
ap-1785	31	12	ln	ln	ADJ
ap-1785	31	13	∑	∑	PUNCT
ap-1785	31	14	pj>0	pj>0	PROPN
ap-1785	31	15	p2	p2	PROPN
ap-1785	31	16	j	j	PROPN
ap-1785	31	17	;	;	PUNCT
ap-1785	31	18	the	the	DET
ap-1785	31	19	resulting	result	VERB
ap-1785	31	20	theoretical	theoretical	ADJ
ap-1785	31	21	entropies	entropy	NOUN
ap-1785	31	22	can	can	AUX
ap-1785	31	23	be	be	AUX
ap-1785	31	24	used	use	VERB
ap-1785	31	25	for	for	ADP
ap-1785	31	26	defining	define	VERB
ap-1785	31	27	the	the	DET
ap-1785	31	28	rényi	rényi	NOUN
ap-1785	31	29	dimension	dimension	NOUN
ap-1785	32	1	[	[	X
ap-1785	32	2	2	2	X
ap-1785	32	3	]	]	PUNCT
ap-1785	32	4	as	as	ADP
ap-1785	32	5	dq	dq	PROPN
ap-1785	32	6	=	=	PROPN
ap-1785	32	7	lim	lim	PROPN
ap-1785	32	8	a→0	a→0	PROPN
ap-1785	32	9	+	+	NUM
ap-1785	32	10	hq	hq	PROPN
ap-1785	32	11	ln	ln	ADJ
ap-1785	32	12	1	1	NUM
ap-1785	32	13	a	a	PRON
ap-1785	32	14	,	,	PUNCT
ap-1785	32	15	which	which	PRON
ap-1785	32	16	corresponds	correspond	VERB
ap-1785	32	17	to	to	ADP
ap-1785	32	18	the	the	DET
ap-1785	32	19	relationship	relationship	NOUN
ap-1785	32	20	hq	hq	INTJ
ap-1785	33	1	≈	≈	PROPN
ap-1785	33	2	aq	aq	NOUN
ap-1785	33	3	−dq	−dq	PROPN
ap-1785	33	4	ln	ln	PROPN
ap-1785	33	5	a	a	DET
ap-1785	33	6	(	(	PUNCT
ap-1785	33	7	2	2	NUM
ap-1785	33	8	)	)	PUNCT
ap-1785	33	9	for	for	ADP
ap-1785	33	10	small	small	ADJ
ap-1785	33	11	covering	covering	NOUN
ap-1785	33	12	size	size	NOUN
ap-1785	33	13	a	a	PRON
ap-1785	33	14	>	>	X
ap-1785	33	15	0	0	NUM
ap-1785	33	16	.	.	NOUN
ap-1785	33	17	3	3	X
ap-1785	33	18	.	.	X
ap-1785	33	19	entropy	entropy	PROPN
ap-1785	33	20	estimates	estimate	VERB
ap-1785	33	21	there	there	PRON
ap-1785	33	22	are	be	VERB
ap-1785	33	23	several	several	ADJ
ap-1785	33	24	approaches	approach	NOUN
ap-1785	33	25	to	to	PART
ap-1785	33	26	entropy	entropy	VERB
ap-1785	33	27	estimation	estimation	NOUN
ap-1785	33	28	from	from	ADP
ap-1785	33	29	experimental	experimental	ADJ
ap-1785	33	30	data	datum	NOUN
ap-1785	33	31	sets	set	NOUN
ap-1785	33	32	.	.	PUNCT
ap-1785	34	1	assuming	assume	VERB
ap-1785	34	2	that	that	SCONJ
ap-1785	34	3	the	the	DET
ap-1785	34	4	number	number	NOUN
ap-1785	34	5	of	of	ADP
ap-1785	34	6	experiments	experiment	NOUN
ap-1785	34	7	n	n	PRON
ap-1785	34	8	∈	∈	NOUN
ap-1785	34	9	n	n	NOUN
ap-1785	34	10	is	be	AUX
ap-1785	34	11	finite	finite	ADJ
ap-1785	34	12	,	,	PUNCT
ap-1785	34	13	we	we	PRON
ap-1785	34	14	can	can	AUX
ap-1785	34	15	count	count	VERB
ap-1785	34	16	the	the	DET
ap-1785	34	17	75	75	NUM
ap-1785	34	18	http://ctn.cvut.cz/ap/	http://ctn.cvut.cz/ap/	PROPN
ap-1785	34	19	v.	v.	ADP
ap-1785	34	20	hubata	hubata	PROPN
ap-1785	34	21	-	-	PUNCT
ap-1785	34	22	vacek	vacek	PROPN
ap-1785	34	23	,	,	PUNCT
ap-1785	34	24	j.	j.	PROPN
ap-1785	34	25	kukal	kukal	PROPN
ap-1785	34	26	,	,	PUNCT
ap-1785	34	27	r.	r.	PROPN
ap-1785	34	28	rusina	rusina	PROPN
ap-1785	34	29	,	,	PUNCT
ap-1785	34	30	m.	m.	NOUN
ap-1785	34	31	buncová	buncová	PROPN
ap-1785	34	32	acta	acta	PROPN
ap-1785	34	33	polytechnica	polytechnica	NOUN
ap-1785	34	34	events	event	NOUN
ap-1785	34	35	and	and	CCONJ
ap-1785	34	36	obtain	obtain	VERB
ap-1785	34	37	nj	nj	PROPN
ap-1785	34	38	∈	∈	PROPN
ap-1785	34	39	n0	n0	PROPN
ap-1785	34	40	as	as	ADP
ap-1785	34	41	the	the	DET
ap-1785	34	42	event	event	NOUN
ap-1785	34	43	frequencies	frequency	NOUN
ap-1785	34	44	for	for	ADP
ap-1785	34	45	j	j	PROPN
ap-1785	34	46	=	=	SYM
ap-1785	34	47	1	1	PROPN
ap-1785	34	48	,	,	PUNCT
ap-1785	34	49	.	.	PUNCT
ap-1785	34	50	.	.	PUNCT
ap-1785	35	1	.	.	PUNCT
ap-1785	36	1	,	,	PUNCT
ap-1785	36	2	k.	k.	PROPN
ap-1785	36	3	the	the	DET
ap-1785	36	4	first	first	ADJ
ap-1785	36	5	approach	approach	NOUN
ap-1785	36	6	to	to	ADP
ap-1785	36	7	entropy	entropy	NOUN
ap-1785	36	8	estimation	estimation	NOUN
ap-1785	36	9	is	be	AUX
ap-1785	36	10	naive	naive	ADJ
ap-1785	36	11	estimation	estimation	NOUN
ap-1785	36	12	.	.	PUNCT
ap-1785	37	1	we	we	PRON
ap-1785	37	2	directly	directly	ADV
ap-1785	37	3	estimate	estimate	VERB
ap-1785	37	4	k	k	NOUN
ap-1785	37	5	and	and	CCONJ
ap-1785	37	6	pj	pj	PROPN
ap-1785	37	7	as	as	ADP
ap-1785	37	8	kn	kn	PROPN
ap-1785	37	9	=	=	PROPN
ap-1785	37	10	∑	∑	PUNCT
ap-1785	37	11	nj>0	nj>0	PROPN
ap-1785	37	12	1	1	NUM
ap-1785	37	13	≤	≤	PROPN
ap-1785	37	14	k	k	PROPN
ap-1785	37	15	,	,	PUNCT
ap-1785	37	16	pj	pj	PROPN
ap-1785	37	17	,	,	PUNCT
ap-1785	37	18	n	n	PROPN
ap-1785	37	19	=	=	SYM
ap-1785	37	20	nj	nj	PROPN
ap-1785	37	21	n	n	PROPN
ap-1785	37	22	.	.	PUNCT
ap-1785	38	1	these	these	DET
ap-1785	38	2	biased	biased	ADJ
ap-1785	38	3	estimates	estimate	NOUN
ap-1785	38	4	also	also	ADV
ap-1785	38	5	produce	produce	VERB
ap-1785	38	6	biased	biased	ADJ
ap-1785	38	7	entropy	entropy	NOUN
ap-1785	38	8	estimates	estimate	VERB
ap-1785	38	9	h0,n	h0,n	PROPN
ap-1785	38	10	=	=	SYM
ap-1785	38	11	ln	ln	PROPN
ap-1785	38	12	kn	kn	PROPN
ap-1785	38	13	,	,	PUNCT
ap-1785	38	14	h1,n	h1,n	PROPN
ap-1785	38	15	=	=	PUNCT
ap-1785	39	1	−	−	PROPN
ap-1785	39	2	∑	∑	PUNCT
ap-1785	39	3	nj>0	nj>0	PROPN
ap-1785	39	4	pj	pj	PROPN
ap-1785	39	5	,	,	PUNCT
ap-1785	39	6	n	n	PROPN
ap-1785	39	7	ln	ln	PROPN
ap-1785	39	8	pj	pj	PROPN
ap-1785	39	9	,	,	PUNCT
ap-1785	39	10	n	n	CCONJ
ap-1785	39	11	,	,	PUNCT
ap-1785	39	12	h2,n	h2,n	PROPN
ap-1785	39	13	=	=	SYM
ap-1785	39	14	−	−	PROPN
ap-1785	39	15	ln	ln	INTJ
ap-1785	39	16	∑	∑	PROPN
ap-1785	39	17	nj>0	nj>0	PROPN
ap-1785	39	18	p2	p2	PROPN
ap-1785	39	19	j	j	PROPN
ap-1785	39	20	,	,	PUNCT
ap-1785	39	21	n.	n.	NOUN
ap-1785	39	22	the	the	DET
ap-1785	39	23	second	second	ADJ
ap-1785	39	24	approach	approach	NOUN
ap-1785	39	25	is	be	AUX
ap-1785	39	26	based	base	VERB
ap-1785	39	27	on	on	ADP
ap-1785	39	28	bayesian	bayesian	NOUN
ap-1785	39	29	estimation	estimation	NOUN
ap-1785	39	30	of	of	ADP
ap-1785	39	31	probabilities	probability	NOUN
ap-1785	39	32	pj	pj	PROPN
ap-1785	39	33	as	as	ADP
ap-1785	39	34	pj	pj	PROPN
ap-1785	39	35	,	,	PUNCT
ap-1785	39	36	b	b	PROPN
ap-1785	39	37	=	=	SYM
ap-1785	39	38	nj	nj	PROPN
ap-1785	40	1	+	+	CCONJ
ap-1785	40	2	1	1	NUM
ap-1785	40	3	n+	n+	PUNCT
ap-1785	40	4	kn	kn	PROPN
ap-1785	40	5	.	.	PUNCT
ap-1785	41	1	this	this	DET
ap-1785	41	2	technique	technique	NOUN
ap-1785	41	3	is	be	AUX
ap-1785	41	4	called	call	VERB
ap-1785	41	5	here	here	ADV
ap-1785	41	6	semi	semi	ADJ
ap-1785	41	7	-	-	ADJ
ap-1785	41	8	bayesian	bayesian	ADJ
ap-1785	41	9	estimation	estimation	NOUN
ap-1785	41	10	.	.	PUNCT
ap-1785	42	1	we	we	PRON
ap-1785	42	2	obtain	obtain	VERB
ap-1785	42	3	other	other	ADJ
ap-1785	42	4	,	,	PUNCT
ap-1785	42	5	but	but	CCONJ
ap-1785	42	6	also	also	ADV
ap-1785	42	7	biased	bias	VERB
ap-1785	42	8	,	,	PUNCT
ap-1785	42	9	entropy	entropy	PROPN
ap-1785	42	10	estimates	estimate	VERB
ap-1785	42	11	h1,s	h1,s	PROPN
ap-1785	42	12	=	=	SYM
ap-1785	42	13	−	−	PROPN
ap-1785	42	14	∑	∑	PUNCT
ap-1785	42	15	nj>0	nj>0	PROPN
ap-1785	42	16	pj	pj	PROPN
ap-1785	42	17	,	,	PUNCT
ap-1785	42	18	b	b	PROPN
ap-1785	42	19	ln	ln	PROPN
ap-1785	42	20	pj	pj	PROPN
ap-1785	42	21	,	,	PUNCT
ap-1785	42	22	b	b	PROPN
ap-1785	42	23	,	,	PUNCT
ap-1785	42	24	h2,s	h2,s	PROPN
ap-1785	42	25	=	=	SYM
ap-1785	42	26	−	−	PROPN
ap-1785	42	27	ln	ln	INTJ
ap-1785	42	28	∑	∑	PROPN
ap-1785	42	29	nj>0	nj>0	PROPN
ap-1785	42	30	p2	p2	PROPN
ap-1785	42	31	j	j	PROPN
ap-1785	42	32	,	,	PUNCT
ap-1785	42	33	b.	b.	PROPN
ap-1785	43	1	the	the	DET
ap-1785	43	2	estimate	estimate	NOUN
ap-1785	43	3	h2,s	h2,s	PROPN
ap-1785	43	4	can	can	AUX
ap-1785	43	5	be	be	AUX
ap-1785	43	6	improved	improve	VERB
ap-1785	43	7	as	as	ADP
ap-1785	43	8	h2,s2	h2,s2	PROPN
ap-1785	43	9	=	=	SYM
ap-1785	43	10	−	−	PROPN
ap-1785	43	11	ln	ln	INTJ
ap-1785	43	12	∑	∑	PROPN
ap-1785	43	13	nj>0	nj>0	PROPN
ap-1785	43	14	uj	uj	PROPN
ap-1785	43	15	,	,	PUNCT
ap-1785	43	16	where	where	SCONJ
ap-1785	43	17	uj	uj	PROPN
ap-1785	43	18	=	=	SYM
ap-1785	43	19	(	(	PUNCT
ap-1785	43	20	nj+2)(nj+1	nj+2)(nj+1	NOUN
ap-1785	43	21	)	)	PUNCT
ap-1785	43	22	(	(	PUNCT
ap-1785	43	23	n+kn+1)(n+kn	n+kn+1)(n+kn	ADV
ap-1785	43	24	)	)	PUNCT
ap-1785	43	25	is	be	AUX
ap-1785	43	26	a	a	DET
ap-1785	43	27	bayesian	bayesian	NOUN
ap-1785	43	28	estimate	estimate	NOUN
ap-1785	43	29	of	of	ADP
ap-1785	43	30	p2	p2	PROPN
ap-1785	43	31	j	j	PROPN
ap-1785	43	32	.	.	PUNCT
ap-1785	44	1	a	a	DET
ap-1785	44	2	direct	direct	ADJ
ap-1785	44	3	bayesian	bayesian	NOUN
ap-1785	44	4	estimate	estimate	NOUN
ap-1785	44	5	of	of	ADP
ap-1785	44	6	h1	h1	PROPN
ap-1785	44	7	was	be	AUX
ap-1785	44	8	also	also	ADV
ap-1785	44	9	calculated	calculate	VERB
ap-1785	44	10	as	as	ADP
ap-1785	44	11	h1,b	h1,b	PROPN
ap-1785	44	12	=	=	PUNCT
ap-1785	45	1	−	−	PROPN
ap-1785	45	2	kn∑	kn∑	PROPN
ap-1785	45	3	i=1	i=1	PROPN
ap-1785	45	4	ni	ni	PROPN
ap-1785	45	5	+	+	PROPN
ap-1785	45	6	1	1	NUM
ap-1785	45	7	n+	n+	PUNCT
ap-1785	45	8	kn	kn	PROPN
ap-1785	45	9	(	(	PUNCT
ap-1785	45	10	ψ(ni	ψ(ni	PROPN
ap-1785	45	11	+	+	PROPN
ap-1785	45	12	2)−	2)−	NUM
ap-1785	45	13	ψ(n+	ψ(n+	NOUN
ap-1785	45	14	kn	kn	NOUN
ap-1785	45	15	+	+	CCONJ
ap-1785	45	16	1	1	NUM
ap-1785	45	17	)	)	PUNCT
ap-1785	45	18	)	)	PUNCT
ap-1785	45	19	,	,	PUNCT
ap-1785	45	20	where	where	SCONJ
ap-1785	45	21	ψ	ψ	NOUN
ap-1785	45	22	is	be	AUX
ap-1785	45	23	the	the	DET
ap-1785	45	24	digamma	digamma	PROPN
ap-1785	45	25	function	function	NOUN
ap-1785	45	26	.	.	PUNCT
ap-1785	46	1	4	4	X
ap-1785	46	2	.	.	X
ap-1785	46	3	bias	bias	NOUN
ap-1785	46	4	reduction	reduction	NOUN
ap-1785	46	5	miller	miller	NOUN
ap-1785	47	1	[	[	X
ap-1785	47	2	5	5	NUM
ap-1785	47	3	]	]	PUNCT
ap-1785	47	4	modified	modify	VERB
ap-1785	47	5	the	the	DET
ap-1785	47	6	naive	naive	ADJ
ap-1785	47	7	estimate	estimate	NOUN
ap-1785	47	8	h1,n	h1,n	PROPN
ap-1785	47	9	using	use	VERB
ap-1785	47	10	first	first	ADJ
ap-1785	47	11	order	order	NOUN
ap-1785	47	12	taylor	taylor	PROPN
ap-1785	47	13	expansion	expansion	NOUN
ap-1785	47	14	,	,	PUNCT
ap-1785	47	15	which	which	PRON
ap-1785	47	16	produces	produce	VERB
ap-1785	47	17	h1,m	h1,m	PROPN
ap-1785	47	18	=	=	PROPN
ap-1785	47	19	h1,n	h1,n	PROPN
ap-1785	47	20	+	+	CCONJ
ap-1785	47	21	kn	kn	PROPN
ap-1785	47	22	−	−	PROPN
ap-1785	47	23	1	1	NUM
ap-1785	47	24	2n	2n	NUM
ap-1785	47	25	.	.	PUNCT
ap-1785	48	1	lately	lately	ADV
ap-1785	48	2	,	,	PUNCT
ap-1785	48	3	harris	harris	PROPN
ap-1785	49	1	[	[	X
ap-1785	49	2	5	5	NUM
ap-1785	49	3	]	]	PUNCT
ap-1785	49	4	improved	improve	VERB
ap-1785	49	5	the	the	DET
ap-1785	49	6	formula	formula	NOUN
ap-1785	49	7	to	to	ADP
ap-1785	49	8	h1,h	h1,h	NOUN
ap-1785	49	9	=	=	PUNCT
ap-1785	49	10	h1,n	h1,n	PROPN
ap-1785	50	1	+	+	CCONJ
ap-1785	50	2	kn	kn	PROPN
ap-1785	50	3	−	−	NUM
ap-1785	50	4	1	1	NUM
ap-1785	50	5	2n	2n	NUM
ap-1785	51	1	+	+	CCONJ
ap-1785	51	2	1	1	NUM
ap-1785	51	3	12n2	12n2	NUM
ap-1785	51	4	(	(	PUNCT
ap-1785	51	5	1−	1−	NUM
ap-1785	51	6	∑	∑	ADP
ap-1785	51	7	pj>0	pj>0	PROPN
ap-1785	51	8	1	1	NUM
ap-1785	51	9	pj	pj	PROPN
ap-1785	51	10	)	)	PUNCT
ap-1785	51	11	from	from	ADP
ap-1785	51	12	the	the	DET
ap-1785	51	13	theoretical	theoretical	ADJ
ap-1785	51	14	point	point	NOUN
ap-1785	51	15	of	of	ADP
ap-1785	51	16	view	view	NOUN
ap-1785	51	17	,	,	PUNCT
ap-1785	51	18	it	it	PRON
ap-1785	51	19	is	be	AUX
ap-1785	51	20	prohibited	prohibit	VERB
ap-1785	51	21	to	to	PART
ap-1785	51	22	estimate	estimate	VERB
ap-1785	51	23	pj	pj	PROPN
ap-1785	51	24	by	by	ADP
ap-1785	51	25	its	its	PRON
ap-1785	51	26	estimates	estimate	NOUN
ap-1785	51	27	.	.	PUNCT
ap-1785	52	1	however	however	ADV
ap-1785	52	2	we	we	PRON
ap-1785	52	3	are	be	AUX
ap-1785	52	4	trying	try	VERB
ap-1785	52	5	to	to	PART
ap-1785	52	6	investigate	investigate	VERB
ap-1785	52	7	biased	biased	ADJ
ap-1785	52	8	estimates	estimate	NOUN
ap-1785	52	9	of	of	ADP
ap-1785	52	10	h1	h1	NOUN
ap-1785	52	11	in	in	ADP
ap-1785	52	12	the	the	DET
ap-1785	52	13	forms	form	NOUN
ap-1785	52	14	h1,hn	h1,hn	ADP
ap-1785	52	15	=	=	PROPN
ap-1785	52	16	h1,n	h1,n	PROPN
ap-1785	53	1	+	+	CCONJ
ap-1785	53	2	kn	kn	PROPN
ap-1785	53	3	−	−	NUM
ap-1785	53	4	1	1	NUM
ap-1785	53	5	2n	2n	NUM
ap-1785	54	1	+	+	CCONJ
ap-1785	54	2	1	1	NUM
ap-1785	54	3	12n2	12n2	NUM
ap-1785	54	4	(	(	PUNCT
ap-1785	54	5	1−	1−	NUM
ap-1785	54	6	∑	∑	PUNCT
ap-1785	54	7	nj>0	nj>0	PROPN
ap-1785	54	8	1	1	NUM
ap-1785	54	9	pj	pj	PROPN
ap-1785	54	10	,	,	PUNCT
ap-1785	54	11	n	n	PROPN
ap-1785	54	12	)	)	PUNCT
ap-1785	54	13	,	,	PUNCT
ap-1785	54	14	h1,hs	h1,hs	PROPN
ap-1785	54	15	=	=	PUNCT
ap-1785	55	1	h1,n	h1,n	PROPN
ap-1785	56	1	+	+	CCONJ
ap-1785	56	2	kn	kn	PROPN
ap-1785	56	3	−	−	NUM
ap-1785	56	4	1	1	NUM
ap-1785	56	5	2n	2n	NUM
ap-1785	57	1	+	+	CCONJ
ap-1785	57	2	1	1	NUM
ap-1785	57	3	12n2	12n2	NUM
ap-1785	57	4	(	(	PUNCT
ap-1785	57	5	1−	1−	NUM
ap-1785	57	6	∑	∑	PUNCT
ap-1785	57	7	nj>0	nj>0	PROPN
ap-1785	57	8	1	1	NUM
ap-1785	57	9	pj	pj	PROPN
ap-1785	57	10	,	,	PUNCT
ap-1785	57	11	b	b	PROPN
ap-1785	57	12	)	)	PUNCT
ap-1785	57	13	,	,	PUNCT
ap-1785	57	14	h1,hb	h1,hb	NOUN
ap-1785	58	1	=	=	SYM
ap-1785	58	2	h1,n	h1,n	PROPN
ap-1785	59	1	+	+	CCONJ
ap-1785	59	2	kn	kn	PROPN
ap-1785	59	3	−	−	NUM
ap-1785	59	4	1	1	NUM
ap-1785	59	5	2n	2n	NUM
ap-1785	60	1	+	+	CCONJ
ap-1785	60	2	1	1	NUM
ap-1785	60	3	12n2	12n2	NUM
ap-1785	60	4	(	(	PUNCT
ap-1785	60	5	1−	1−	NUM
ap-1785	60	6	∑	∑	PROPN
ap-1785	60	7	nj>0	nj>0	PROPN
ap-1785	60	8	rj	rj	PROPN
ap-1785	60	9	)	)	PUNCT
ap-1785	60	10	,	,	PUNCT
ap-1785	60	11	where	where	SCONJ
ap-1785	60	12	rj	rj	PROPN
ap-1785	60	13	=	=	SYM
ap-1785	60	14	n+kn−1	n+kn−1	PROPN
ap-1785	60	15	nj	nj	PROPN
ap-1785	60	16	is	be	AUX
ap-1785	60	17	bayesian	bayesian	NOUN
ap-1785	60	18	estimate	estimate	NOUN
ap-1785	60	19	of	of	ADP
ap-1785	60	20	1	1	NUM
ap-1785	60	21	pj	pj	NOUN
ap-1785	60	22	.	.	PUNCT
ap-1785	61	1	5	5	X
ap-1785	61	2	.	.	X
ap-1785	61	3	estimation	estimation	NOUN
ap-1785	61	4	methodology	methodology	NOUN
ap-1785	61	5	naive	naive	ADJ
ap-1785	61	6	,	,	PUNCT
ap-1785	61	7	semi	semi	ADJ
ap-1785	61	8	-	-	ADJ
ap-1785	61	9	bayesian	bayesian	ADJ
ap-1785	61	10	,	,	PUNCT
ap-1785	61	11	bayesian	bayesian	NOUN
ap-1785	61	12	and	and	CCONJ
ap-1785	61	13	corrected	correct	VERB
ap-1785	61	14	entropy	entropy	NOUN
ap-1785	61	15	estimates	estimate	NOUN
ap-1785	61	16	were	be	AUX
ap-1785	61	17	subjected	subject	VERB
ap-1785	61	18	of	of	ADP
ap-1785	61	19	testing	test	VERB
ap-1785	61	20	on	on	ADP
ap-1785	61	21	2d	2d	NUM
ap-1785	61	22	and	and	CCONJ
ap-1785	61	23	3d	3d	NUM
ap-1785	61	24	structures	structure	NOUN
ap-1785	61	25	with	with	ADP
ap-1785	61	26	known	know	VERB
ap-1785	61	27	hausdorff	hausdorff	NOUN
ap-1785	61	28	dimension	dimension	NOUN
ap-1785	61	29	.	.	PUNCT
ap-1785	62	1	the	the	DET
ap-1785	62	2	list	list	NOUN
ap-1785	62	3	of	of	ADP
ap-1785	62	4	involved	involved	ADJ
ap-1785	62	5	estimates	estimate	NOUN
ap-1785	62	6	is	be	AUX
ap-1785	62	7	included	include	VERB
ap-1785	62	8	in	in	ADP
ap-1785	62	9	tab	tab	NOUN
ap-1785	62	10	.	.	PUNCT
ap-1785	63	1	1	1	X
ap-1785	63	2	.	.	X
ap-1785	63	3	a	a	DET
ap-1785	63	4	sierpinski	sierpinski	ADJ
ap-1785	63	5	carpet	carpet	NOUN
ap-1785	63	6	with	with	ADP
ap-1785	63	7	dq	dq	NOUN
ap-1785	63	8	=	=	NOUN
ap-1785	63	9	1.8928	1.8928	NUM
ap-1785	63	10	for	for	ADP
ap-1785	63	11	any	any	DET
ap-1785	63	12	q	q	ADJ
ap-1785	63	13	≥	≥	NOUN
ap-1785	63	14	0	0	NUM
ap-1785	63	15	of	of	ADP
ap-1785	63	16	size	size	NOUN
ap-1785	63	17	81×81	81×81	NUM
ap-1785	63	18	is	be	AUX
ap-1785	63	19	a	a	DET
ap-1785	63	20	typical	typical	ADJ
ap-1785	63	21	2d	2d	NUM
ap-1785	63	22	fractal	fractal	ADJ
ap-1785	63	23	set	set	NOUN
ap-1785	63	24	model	model	NOUN
ap-1785	63	25	.	.	PUNCT
ap-1785	64	1	using	use	VERB
ap-1785	64	2	the	the	DET
ap-1785	64	3	estimates	estimate	NOUN
ap-1785	64	4	from	from	ADP
ap-1785	64	5	tab	tab	PROPN
ap-1785	64	6	.	.	PROPN
ap-1785	65	1	1	1	NUM
ap-1785	65	2	and	and	CCONJ
ap-1785	65	3	a	a	DET
ap-1785	65	4	linear	linear	ADJ
ap-1785	65	5	regression	regression	NOUN
ap-1785	65	6	model	model	NOUN
ap-1785	65	7	(	(	PUNCT
ap-1785	65	8	2	2	NUM
ap-1785	65	9	)	)	PUNCT
ap-1785	66	1	,	,	PUNCT
ap-1785	66	2	we	we	PRON
ap-1785	66	3	estimated	estimate	VERB
ap-1785	66	4	the	the	DET
ap-1785	66	5	rényi	rényi	NOUN
ap-1785	66	6	dimensions	dimension	NOUN
ap-1785	66	7	d̂q	d̂q	X
ap-1785	66	8	and	and	CCONJ
ap-1785	66	9	then	then	ADV
ap-1785	66	10	evaluated	evaluate	VERB
ap-1785	66	11	its	its	PRON
ap-1785	66	12	zscore	zscore	NOUN
ap-1785	66	13	as	as	ADP
ap-1785	66	14	a	a	DET
ap-1785	66	15	relative	relative	ADJ
ap-1785	66	16	measure	measure	NOUN
ap-1785	66	17	of	of	ADP
ap-1785	66	18	bias	bias	NOUN
ap-1785	66	19	zscore	zscore	NOUN
ap-1785	67	1	=	=	PUNCT
ap-1785	68	1	d̂q	d̂q	NUM
ap-1785	68	2	−dq	−dq	PROPN
ap-1785	68	3	sdq	sdq	NOUN
ap-1785	68	4	.	.	PUNCT
ap-1785	69	1	the	the	DET
ap-1785	69	2	results	result	NOUN
ap-1785	69	3	are	be	AUX
ap-1785	69	4	included	include	VERB
ap-1785	69	5	in	in	ADP
ap-1785	69	6	tab	tab	NOUN
ap-1785	69	7	.	.	PUNCT
ap-1785	70	1	2	2	X
ap-1785	70	2	.	.	X
ap-1785	70	3	the	the	DET
ap-1785	70	4	best	good	ADJ
ap-1785	70	5	estimations	estimation	NOUN
ap-1785	70	6	with	with	ADP
ap-1785	70	7	|zscore|	|zscore|	NOUN
ap-1785	70	8	≤	≤	NUM
ap-1785	70	9	1.960	1.960	NUM
ap-1785	70	10	are	be	AUX
ap-1785	70	11	h1,m	h1,m	PROPN
ap-1785	70	12	followed	follow	VERB
ap-1785	70	13	by	by	ADP
ap-1785	70	14	harris	harris	PROPN
ap-1785	70	15	estimations	estimation	NOUN
ap-1785	70	16	h1,hn	h1,hn	PROPN
ap-1785	70	17	,	,	PUNCT
ap-1785	70	18	h1,hs	h1,hs	PROPN
ap-1785	70	19	,	,	PUNCT
ap-1785	70	20	h1,hb	h1,hb	PROPN
ap-1785	70	21	.	.	PUNCT
ap-1785	71	1	a	a	DET
ap-1785	71	2	structure	structure	NOUN
ap-1785	71	3	of	of	ADP
ap-1785	71	4	dq	dq	NOUN
ap-1785	71	5	=	=	NOUN
ap-1785	71	6	2.3219	2.3219	NUM
ap-1785	71	7	and	and	CCONJ
ap-1785	71	8	size	size	NOUN
ap-1785	71	9	128	128	NUM
ap-1785	71	10	×	×	NOUN
ap-1785	71	11	128	128	NUM
ap-1785	71	12	×	×	NOUN
ap-1785	71	13	128	128	NUM
ap-1785	71	14	was	be	AUX
ap-1785	71	15	then	then	ADV
ap-1785	71	16	used	use	VERB
ap-1785	71	17	for	for	ADP
ap-1785	71	18	3d	3d	NUM
ap-1785	71	19	testing	testing	NOUN
ap-1785	71	20	and	and	CCONJ
ap-1785	71	21	the	the	DET
ap-1785	71	22	results	result	NOUN
ap-1785	71	23	are	be	AUX
ap-1785	71	24	also	also	ADV
ap-1785	71	25	included	include	VERB
ap-1785	71	26	in	in	ADP
ap-1785	71	27	tab	tab	NOUN
ap-1785	71	28	.	.	PUNCT
ap-1785	72	1	2	2	X
ap-1785	72	2	.	.	X
ap-1785	72	3	the	the	DET
ap-1785	72	4	best	good	ADJ
ap-1785	72	5	estimators	estimator	NOUN
ap-1785	72	6	are	be	AUX
ap-1785	72	7	h1,hs	h1,hs	NOUN
ap-1785	72	8	,	,	PUNCT
ap-1785	72	9	h1,hn	h1,hn	ADP
ap-1785	72	10	,	,	PUNCT
ap-1785	72	11	h1,hb	h1,hb	PROPN
ap-1785	72	12	,	,	PUNCT
ap-1785	72	13	h1,m	h1,m	PROPN
ap-1785	72	14	,	,	PUNCT
ap-1785	72	15	h2,s	h2,s	PROPN
ap-1785	72	16	.	.	PUNCT
ap-1785	73	1	6	6	NUM
ap-1785	73	2	.	.	X
ap-1785	73	3	alzheimer	alzheimer	PROPN
ap-1785	73	4	’s	’s	PART
ap-1785	73	5	disease	disease	NOUN
ap-1785	73	6	diagnosis	diagnosis	NOUN
ap-1785	73	7	from	from	ADP
ap-1785	73	8	fractal	fractal	ADJ
ap-1785	73	9	dimension	dimension	NOUN
ap-1785	73	10	estimates	estimate	VERB
ap-1785	73	11	alzheimer	alzheimer	PROPN
ap-1785	73	12	’s	’s	PART
ap-1785	73	13	disease	disease	NOUN
ap-1785	73	14	(	(	PUNCT
ap-1785	73	15	ad	ad	NOUN
ap-1785	73	16	)	)	PUNCT
ap-1785	73	17	is	be	AUX
ap-1785	73	18	the	the	DET
ap-1785	73	19	most	most	ADV
ap-1785	73	20	common	common	ADJ
ap-1785	73	21	form	form	NOUN
ap-1785	73	22	of	of	ADP
ap-1785	73	23	dementia	dementia	NOUN
ap-1785	73	24	,	,	PUNCT
ap-1785	73	25	and	and	CCONJ
ap-1785	73	26	is	be	AUX
ap-1785	73	27	characterised	characterise	VERB
ap-1785	73	28	by	by	ADP
ap-1785	73	29	loss	loss	NOUN
ap-1785	73	30	of	of	ADP
ap-1785	73	31	neurons	neuron	NOUN
ap-1785	73	32	and	and	CCONJ
ap-1785	73	33	their	their	PRON
ap-1785	73	34	synapses	synapsis	NOUN
ap-1785	73	35	.	.	PUNCT
ap-1785	74	1	this	this	DET
ap-1785	74	2	loss	loss	NOUN
ap-1785	74	3	is	be	AUX
ap-1785	74	4	caused	cause	VERB
ap-1785	74	5	by	by	ADP
ap-1785	74	6	an	an	DET
ap-1785	74	7	accumulation	accumulation	NOUN
ap-1785	74	8	of	of	ADP
ap-1785	74	9	amyloid	amyloid	NOUN
ap-1785	74	10	plaques	plaque	NOUN
ap-1785	74	11	between	between	ADP
ap-1785	74	12	nerve	nerve	NOUN
ap-1785	74	13	cells	cell	NOUN
ap-1785	74	14	in	in	ADP
ap-1785	74	15	the	the	DET
ap-1785	74	16	brain	brain	NOUN
ap-1785	74	17	.	.	PUNCT
ap-1785	75	1	morphologically	morphologically	ADV
ap-1785	75	2	,	,	PUNCT
ap-1785	75	3	the	the	DET
ap-1785	75	4	affected	affect	VERB
ap-1785	75	5	areas	area	NOUN
ap-1785	75	6	produce	produce	VERB
ap-1785	75	7	rounded	rounded	ADJ
ap-1785	75	8	clusters	cluster	NOUN
ap-1785	75	9	of	of	ADP
ap-1785	75	10	destroyed	destroy	VERB
ap-1785	75	11	brain	brain	NOUN
ap-1785	75	12	cells	cell	NOUN
ap-1785	75	13	,	,	PUNCT
ap-1785	75	14	which	which	PRON
ap-1785	75	15	are	be	AUX
ap-1785	75	16	visible	visible	ADJ
ap-1785	75	17	on	on	ADP
ap-1785	75	18	brain	brain	NOUN
ap-1785	75	19	scans	scan	NOUN
ap-1785	75	20	.	.	PUNCT
ap-1785	76	1	on	on	ADP
ap-1785	76	2	the	the	DET
ap-1785	76	3	other	other	ADJ
ap-1785	76	4	hand	hand	NOUN
ap-1785	76	5	,	,	PUNCT
ap-1785	76	6	amyotrophic	amyotrophic	ADJ
ap-1785	76	7	lateral	lateral	ADJ
ap-1785	76	8	sclerosis	sclerosis	NOUN
ap-1785	76	9	(	(	PUNCT
ap-1785	76	10	als	als	NOUN
ap-1785	76	11	)	)	PUNCT
ap-1785	76	12	is	be	AUX
ap-1785	76	13	a	a	DET
ap-1785	76	14	disease	disease	NOUN
ap-1785	76	15	of	of	ADP
ap-1785	76	16	the	the	DET
ap-1785	76	17	motor	motor	NOUN
ap-1785	76	18	neurons	neuron	NOUN
ap-1785	76	19	,	,	PUNCT
ap-1785	76	20	and	and	CCONJ
ap-1785	76	21	it	it	PRON
ap-1785	76	22	is	be	AUX
ap-1785	76	23	not	not	PART
ap-1785	76	24	visible	visible	ADJ
ap-1785	76	25	on	on	ADP
ap-1785	76	26	brain	brain	NOUN
ap-1785	76	27	scans	scan	NOUN
ap-1785	76	28	.	.	PUNCT
ap-1785	77	1	in	in	ADP
ap-1785	77	2	this	this	DET
ap-1785	77	3	sense	sense	NOUN
ap-1785	77	4	,	,	PUNCT
ap-1785	77	5	brain	brain	NOUN
ap-1785	77	6	scans	scan	NOUN
ap-1785	77	7	of	of	ADP
ap-1785	77	8	als	als	NOUN
ap-1785	77	9	patien	patien	PROPN
ap-1785	77	10	’s	’s	PART
ap-1785	77	11	look	look	VERB
ap-1785	77	12	like	like	ADP
ap-1785	77	13	brain	brain	NOUN
ap-1785	77	14	scans	scan	NOUN
ap-1785	77	15	of	of	ADP
ap-1785	77	16	healthy	healthy	ADJ
ap-1785	77	17	patients	patient	NOUN
ap-1785	77	18	.	.	PUNCT
ap-1785	78	1	these	these	DET
ap-1785	78	2	entropy	entropy	NOUN
ap-1785	78	3	estimators	estimator	NOUN
ap-1785	78	4	were	be	AUX
ap-1785	78	5	used	use	VERB
ap-1785	78	6	for	for	ADP
ap-1785	78	7	diagnosing	diagnose	VERB
ap-1785	78	8	alzheimer	alzheimer	PROPN
ap-1785	78	9	’s	’s	PART
ap-1785	78	10	disease	disease	NOUN
ap-1785	78	11	.	.	PUNCT
ap-1785	79	1	we	we	PRON
ap-1785	79	2	tried	try	VERB
ap-1785	79	3	to	to	PART
ap-1785	79	4	separate	separate	VERB
ap-1785	79	5	two	two	NUM
ap-1785	79	6	different	different	ADJ
ap-1785	79	7	groups	group	NOUN
ap-1785	79	8	of	of	ADP
ap-1785	79	9	samples	sample	NOUN
ap-1785	79	10	of	of	ADP
ap-1785	79	11	human	human	ADJ
ap-1785	79	12	brains	brain	NOUN
ap-1785	79	13	.	.	PUNCT
ap-1785	80	1	in	in	ADP
ap-1785	80	2	the	the	DET
ap-1785	80	3	first	first	ADJ
ap-1785	80	4	group	group	NOUN
ap-1785	80	5	,	,	PUNCT
ap-1785	80	6	there	there	PRON
ap-1785	80	7	were	be	VERB
ap-1785	80	8	brain	brain	NOUN
ap-1785	80	9	scans	scan	NOUN
ap-1785	80	10	of	of	ADP
ap-1785	80	11	patients	patient	NOUN
ap-1785	80	12	with	with	ADP
ap-1785	80	13	alzheimer	alzheimer	PROPN
ap-1785	80	14	’s	’s	PART
ap-1785	80	15	disease	disease	NOUN
ap-1785	80	16	(	(	PUNCT
ap-1785	80	17	ad	ad	NOUN
ap-1785	80	18	)	)	PUNCT
ap-1785	80	19	and	and	CCONJ
ap-1785	80	20	in	in	ADP
ap-1785	80	21	the	the	DET
ap-1785	80	22	second	second	ADJ
ap-1785	80	23	group	group	NOUN
ap-1785	80	24	brain	brain	NOUN
ap-1785	80	25	scans	scan	NOUN
ap-1785	80	26	of	of	ADP
ap-1785	80	27	patients	patient	NOUN
ap-1785	80	28	with	with	ADP
ap-1785	80	29	amyotrophic	amyotrophic	ADJ
ap-1785	80	30	lateral	lateral	ADJ
ap-1785	80	31	sclerosis	sclerosis	NOUN
ap-1785	80	32	(	(	PUNCT
ap-1785	80	33	als	als	NOUN
ap-1785	80	34	)	)	PUNCT
ap-1785	80	35	.	.	PUNCT
ap-1785	81	1	we	we	PRON
ap-1785	81	2	carried	carry	VERB
ap-1785	81	3	out	out	ADP
ap-1785	81	4	tests	test	NOUN
ap-1785	81	5	on	on	ADP
ap-1785	81	6	21	21	NUM
ap-1785	81	7	samples	sample	NOUN
ap-1785	81	8	(	(	PUNCT
ap-1785	81	9	11	11	NUM
ap-1785	81	10	for	for	ADP
ap-1785	81	11	ad	ad	NOUN
ap-1785	81	12	and	and	CCONJ
ap-1785	81	13	10	10	NUM
ap-1785	81	14	for	for	ADP
ap-1785	81	15	als	al	NOUN
ap-1785	81	16	)	)	PUNCT
ap-1785	81	17	,	,	PUNCT
ap-1785	81	18	represented	represent	VERB
ap-1785	81	19	by	by	ADP
ap-1785	81	20	128	128	NUM
ap-1785	81	21	×	×	NOUN
ap-1785	81	22	128	128	NUM
ap-1785	81	23	×	×	NOUN
ap-1785	81	24	128	128	NUM
ap-1785	81	25	matrices	matrix	NOUN
ap-1785	81	26	of	of	ADP
ap-1785	81	27	thresholded	thresholde	VERB
ap-1785	81	28	images	image	NOUN
ap-1785	81	29	(	(	PUNCT
ap-1785	81	30	θ	θ	NOUN
ap-1785	81	31	=	=	SYM
ap-1785	81	32	40	40	NUM
ap-1785	81	33	%	%	NOUN
ap-1785	81	34	)	)	PUNCT
ap-1785	81	35	.	.	PUNCT
ap-1785	82	1	we	we	PRON
ap-1785	82	2	used	use	VERB
ap-1785	82	3	a	a	DET
ap-1785	82	4	twosample	twosample	ADJ
ap-1785	82	5	t	t	NOUN
ap-1785	82	6	-	-	PUNCT
ap-1785	82	7	test	test	NOUN
ap-1785	82	8	for	for	ADP
ap-1785	82	9	null	null	ADJ
ap-1785	82	10	hypotheses	hypothesis	NOUN
ap-1785	82	11	,	,	PUNCT
ap-1785	82	12	and	and	CCONJ
ap-1785	82	13	the	the	DET
ap-1785	82	14	alternative	alternative	ADJ
ap-1785	82	15	76	76	NUM
ap-1785	82	16	vol	vol	NOUN
ap-1785	82	17	.	.	PUNCT
ap-1785	83	1	53	53	NUM
ap-1785	83	2	no	no	NOUN
ap-1785	83	3	.	.	PUNCT
ap-1785	84	1	2/2013	2/2013	NUM
ap-1785	84	2	fractal	fractal	ADJ
ap-1785	84	3	dimension	dimension	NOUN
ap-1785	84	4	estimation	estimation	NOUN
ap-1785	84	5	in	in	ADP
ap-1785	84	6	diagnosing	diagnose	VERB
ap-1785	84	7	alzheimer	alzheimer	PROPN
ap-1785	84	8	’s	’s	PART
ap-1785	84	9	disease	disease	NOUN
ap-1785	84	10	estimate	estimate	VERB
ap-1785	84	11	sierpinski	sierpinski	ADJ
ap-1785	84	12	carpet	carpet	NOUN
ap-1785	84	13	dq	dq	PROPN
ap-1785	84	14	=	=	NOUN
ap-1785	84	15	1.8928	1.8928	NUM
ap-1785	84	16	five	five	NUM
ap-1785	84	17	box	box	NOUN
ap-1785	84	18	fractal	fractal	NOUN
ap-1785	84	19	dq	dq	NOUN
ap-1785	84	20	=	=	NOUN
ap-1785	84	21	2.3219	2.3219	NUM
ap-1785	84	22	d̂q	d̂q	NUM
ap-1785	84	23	sdq	sdq	NOUN
ap-1785	84	24	zscore	zscore	NOUN
ap-1785	84	25	d̂q	d̂q	X
ap-1785	84	26	sdq	sdq	NOUN
ap-1785	84	27	zscore	zscore	NOUN
ap-1785	84	28	h0,n	h0,n	PROPN
ap-1785	84	29	1.8158	1.8158	NUM
ap-1785	84	30	0.0064	0.0064	NUM
ap-1785	84	31	−12.0577	−12.0577	PROPN
ap-1785	85	1	2.0897	2.0897	NUM
ap-1785	85	2	0.0284	0.0284	NUM
ap-1785	85	3	−8.1757	−8.1757	PRON
ap-1785	85	4	h1,n	h1,n	PROPN
ap-1785	85	5	1.8472	1.8472	NUM
ap-1785	85	6	0.0059	0.0059	NUM
ap-1785	85	7	−7.7116	−7.7116	NUM
ap-1785	85	8	2.1853	2.1853	NUM
ap-1785	85	9	0.0320	0.0320	NUM
ap-1785	85	10	−4.2690	−4.2690	NOUN
ap-1785	85	11	h2,n	h2,n	ADV
ap-1785	85	12	1.8578	1.8578	NUM
ap-1785	85	13	0.0076	0.0076	NUM
ap-1785	85	14	−4.6212	−4.6212	NUM
ap-1785	85	15	2.1949	2.1949	NUM
ap-1785	85	16	0.0298	0.0298	NUM
ap-1785	85	17	−4.2568	−4.2568	ADP
ap-1785	85	18	h1,s	h1,s	PROPN
ap-1785	85	19	1.8515	1.8515	NUM
ap-1785	85	20	0.0058	0.0058	NUM
ap-1785	85	21	−7.0853	−7.0853	NUM
ap-1785	85	22	2.2367	2.2367	NUM
ap-1785	85	23	0.0315	0.0315	NUM
ap-1785	85	24	−2.7012	−2.7012	NOUN
ap-1785	85	25	h2,s	h2,s	PROPN
ap-1785	85	26	1.8657	1.8657	NUM
ap-1785	85	27	0.0072	0.0072	NUM
ap-1785	85	28	−3.7494	−3.7494	ADP
ap-1785	85	29	2.2927	2.2927	NUM
ap-1785	85	30	0.0298	0.0298	NUM
ap-1785	85	31	−0.9798	−0.9798	NUM
ap-1785	86	1	h2,s2	h2,s2	PROPN
ap-1785	86	2	1.7898	1.7898	NUM
ap-1785	86	3	0.0077	0.0077	NUM
ap-1785	86	4	−13.4269	−13.4269	PROPN
ap-1785	86	5	2.1189	2.1189	NUM
ap-1785	86	6	0.0268	0.0268	NUM
ap-1785	86	7	−7.5904	−7.5904	VERB
ap-1785	86	8	h1,b	h1,b	PROPN
ap-1785	86	9	1.8170	1.8170	NUM
ap-1785	86	10	0.0060	0.0060	NUM
ap-1785	86	11	−12.6863	−12.6863	NUM
ap-1785	86	12	2.1654	2.1654	NUM
ap-1785	86	13	0.0297	0.0297	NUM
ap-1785	86	14	−5.2638	−5.2638	NOUN
ap-1785	86	15	h1,m	h1,m	PROPN
ap-1785	86	16	1.8930	1.8930	NUM
ap-1785	86	17	0.0059	0.0059	NUM
ap-1785	86	18	0.0306	0.0306	NUM
ap-1785	86	19	2.3315	2.3315	NUM
ap-1785	86	20	0.0349	0.0349	NUM
ap-1785	86	21	0.2730	0.2730	NUM
ap-1785	86	22	h1,hn	h1,hn	ADP
ap-1785	86	23	1.8921	1.8921	NUM
ap-1785	86	24	0.0059	0.0059	NUM
ap-1785	86	25	−0.1203	−0.1203	ADP
ap-1785	86	26	2.3208	2.3208	NUM
ap-1785	86	27	0.0347	0.0347	NUM
ap-1785	86	28	−0.0332	−0.0332	NOUN
ap-1785	86	29	h1,hs	h1,hs	PROPN
ap-1785	86	30	1.8921	1.8921	NUM
ap-1785	86	31	0.0059	0.0059	NUM
ap-1785	86	32	−0.1164	−0.1164	NOUN
ap-1785	86	33	2.3226	2.3226	NUM
ap-1785	86	34	0.0347	0.0347	NUM
ap-1785	86	35	0.0196	0.0196	NUM
ap-1785	86	36	h1,hb	h1,hb	NOUN
ap-1785	86	37	1.8920	1.8920	NUM
ap-1785	86	38	0.0059	0.0059	NUM
ap-1785	86	39	−0.1328	−0.1328	NUM
ap-1785	86	40	2.3182	2.3182	NUM
ap-1785	86	41	0.0346	0.0346	NUM
ap-1785	86	42	−0.1084	−0.1084	NUM
ap-1785	86	43	table	table	NOUN
ap-1785	86	44	2	2	NUM
ap-1785	86	45	.	.	PUNCT
ap-1785	86	46	dimension	dimension	NOUN
ap-1785	86	47	estimates	estimate	NOUN
ap-1785	86	48	via	via	ADP
ap-1785	86	49	various	various	ADJ
ap-1785	86	50	entropy	entropy	NOUN
ap-1785	86	51	estimates	estimate	NOUN
ap-1785	86	52	.	.	PUNCT
ap-1785	87	1	method	method	PROPN
ap-1785	87	2	h0	h0	PROPN
ap-1785	87	3	h1	h1	PROPN
ap-1785	87	4	h2	h2	PROPN
ap-1785	87	5	naive	naive	ADJ
ap-1785	87	6	h0,n	h0,n	PROPN
ap-1785	87	7	h1,n	h1,n	PROPN
ap-1785	87	8	h2,n	h2,n	ADV
ap-1785	87	9	semibayesian	semibayesian	NOUN
ap-1785	87	10	(	(	PUNCT
ap-1785	87	11	pj	pj	PROPN
ap-1785	87	12	)	)	PUNCT
ap-1785	87	13	*	*	PUNCT
ap-1785	88	1	h1,s	h1,s	PROPN
ap-1785	88	2	h2,s	h2,s	PROPN
ap-1785	88	3	semibayesian	semibayesian	NOUN
ap-1785	88	4	(	(	PUNCT
ap-1785	88	5	p2	p2	PROPN
ap-1785	88	6	j	j	PROPN
ap-1785	88	7	)	)	PUNCT
ap-1785	88	8	*	*	PUNCT
ap-1785	89	1	*	*	PUNCT
ap-1785	89	2	h2,s2	h2,s2	PROPN
ap-1785	89	3	bayesian	bayesian	NOUN
ap-1785	89	4	*	*	PUNCT
ap-1785	90	1	h1,b	h1,b	PROPN
ap-1785	90	2	*	*	PUNCT
ap-1785	90	3	miller	miller	PROPN
ap-1785	90	4	*	*	PUNCT
ap-1785	91	1	h1,m	h1,m	PROPN
ap-1785	91	2	*	*	PUNCT
ap-1785	91	3	harris	harris	PROPN
ap-1785	91	4	*	*	PUNCT
ap-1785	91	5	h1,hn	h1,hn	PROPN
ap-1785	91	6	*	*	PUNCT
ap-1785	91	7	harris	harris	PROPN
ap-1785	91	8	semibayesian	semibayesian	PROPN
ap-1785	91	9	(	(	PUNCT
ap-1785	91	10	pj	pj	PROPN
ap-1785	91	11	)	)	PUNCT
ap-1785	91	12	*	*	PUNCT
ap-1785	92	1	h1,hs	h1,hs	PROPN
ap-1785	92	2	*	*	PUNCT
ap-1785	92	3	harris	harris	PROPN
ap-1785	92	4	bayesian	bayesian	PROPN
ap-1785	92	5	(	(	PUNCT
ap-1785	92	6	1	1	NUM
ap-1785	92	7	/	/	SYM
ap-1785	92	8	pj	pj	PROPN
ap-1785	92	9	)	)	PUNCT
ap-1785	92	10	*	*	PUNCT
ap-1785	93	1	h1,hb	h1,hb	NOUN
ap-1785	93	2	*	*	PUNCT
ap-1785	93	3	table	table	NOUN
ap-1785	93	4	1	1	NUM
ap-1785	93	5	.	.	PUNCT
ap-1785	93	6	entropy	entropy	PROPN
ap-1785	93	7	estimates	estimate	NOUN
ap-1785	93	8	.	.	PUNCT
ap-1785	94	1	hypotheses	hypothesis	NOUN
ap-1785	94	2	were	be	AUX
ap-1785	94	3	h0	h0	NOUN
ap-1785	94	4	:	:	PUNCT
ap-1785	94	5	ed̂q(ad	ed̂q(ad	NUM
ap-1785	94	6	)	)	PUNCT
ap-1785	94	7	=	=	SYM
ap-1785	94	8	ed̂q(als	ed̂q(al	NOUN
ap-1785	94	9	)	)	PUNCT
ap-1785	94	10	,	,	PUNCT
ap-1785	94	11	ha	ha	INTJ
ap-1785	94	12	:	:	PUNCT
ap-1785	94	13	ed̂q(ad	ed̂q(ad	PROPN
ap-1785	94	14	)	)	PUNCT
ap-1785	94	15	6=	6=	ADP
ap-1785	94	16	ed̂q(als	ed̂q(al	NOUN
ap-1785	94	17	)	)	PUNCT
ap-1785	94	18	.	.	PUNCT
ap-1785	95	1	the	the	DET
ap-1785	95	2	results	result	NOUN
ap-1785	95	3	are	be	AUX
ap-1785	95	4	included	include	VERB
ap-1785	95	5	in	in	ADP
ap-1785	95	6	tab	tab	NOUN
ap-1785	95	7	.	.	PUNCT
ap-1785	96	1	3	3	X
ap-1785	96	2	.	.	X
ap-1785	96	3	the	the	DET
ap-1785	96	4	most	most	ADV
ap-1785	96	5	significant	significant	ADJ
ap-1785	96	6	differences	difference	NOUN
ap-1785	96	7	between	between	ADP
ap-1785	96	8	ad	ad	NOUN
ap-1785	96	9	and	and	CCONJ
ap-1785	96	10	als	als	NOUN
ap-1785	96	11	were	be	AUX
ap-1785	96	12	observed	observe	VERB
ap-1785	96	13	for	for	ADP
ap-1785	96	14	h0,n	h0,n	PROPN
ap-1785	96	15	,	,	PUNCT
ap-1785	96	16	h1,s	h1,s	PROPN
ap-1785	96	17	,	,	PUNCT
ap-1785	96	18	h1,b	h1,b	PROPN
ap-1785	96	19	.	.	PUNCT
ap-1785	97	1	7	7	NUM
ap-1785	97	2	.	.	X
ap-1785	97	3	conclusion	conclusion	NOUN
ap-1785	97	4	in	in	ADP
ap-1785	97	5	this	this	DET
ap-1785	97	6	paper	paper	NOUN
ap-1785	97	7	we	we	PRON
ap-1785	97	8	tested	test	VERB
ap-1785	97	9	estimates	estimate	NOUN
ap-1785	97	10	for	for	ADP
ap-1785	97	11	hartley	hartley	PROPN
ap-1785	97	12	,	,	PUNCT
ap-1785	97	13	shannon	shannon	PROPN
ap-1785	97	14	and	and	CCONJ
ap-1785	97	15	collision	collision	NOUN
ap-1785	97	16	entropy	entropy	NOUN
ap-1785	97	17	.	.	PUNCT
ap-1785	98	1	these	these	DET
ap-1785	98	2	estimates	estimate	NOUN
ap-1785	98	3	were	be	AUX
ap-1785	98	4	improved	improve	VERB
ap-1785	98	5	by	by	ADP
ap-1785	98	6	bayesian	bayesian	NOUN
ap-1785	98	7	estimation	estimation	NOUN
ap-1785	98	8	and	and	CCONJ
ap-1785	98	9	tested	test	VERB
ap-1785	98	10	on	on	ADP
ap-1785	98	11	fractals	fractal	NOUN
ap-1785	98	12	with	with	ADP
ap-1785	98	13	known	know	VERB
ap-1785	98	14	fractal	fractal	ADJ
ap-1785	98	15	dimensions	dimension	NOUN
ap-1785	98	16	.	.	PUNCT
ap-1785	99	1	finally	finally	ADV
ap-1785	99	2	,	,	PUNCT
ap-1785	99	3	these	these	DET
ap-1785	99	4	estimates	estimate	NOUN
ap-1785	99	5	were	be	AUX
ap-1785	99	6	used	use	VERB
ap-1785	99	7	on	on	ADP
ap-1785	99	8	two	two	NUM
ap-1785	99	9	groups	group	NOUN
ap-1785	99	10	of	of	ADP
ap-1785	99	11	samples	sample	NOUN
ap-1785	99	12	of	of	ADP
ap-1785	99	13	brain	brain	NOUN
ap-1785	99	14	scans	scan	NOUN
ap-1785	99	15	,	,	PUNCT
ap-1785	99	16	in	in	ADP
ap-1785	99	17	order	order	NOUN
ap-1785	99	18	to	to	PART
ap-1785	99	19	obtain	obtain	VERB
ap-1785	99	20	the	the	DET
ap-1785	99	21	best	good	ADJ
ap-1785	99	22	separator	separator	NOUN
ap-1785	99	23	.	.	PUNCT
ap-1785	100	1	the	the	DET
ap-1785	100	2	best	good	ADJ
ap-1785	100	3	separators	separator	NOUN
ap-1785	100	4	,	,	PUNCT
ap-1785	100	5	with	with	ADP
ap-1785	100	6	regard	regard	NOUN
ap-1785	100	7	to	to	ADP
ap-1785	100	8	the	the	DET
ap-1785	100	9	experiment	experiment	NOUN
ap-1785	100	10	,	,	PUNCT
ap-1785	100	11	are	be	AUX
ap-1785	100	12	h0,n	h0,n	PROPN
ap-1785	100	13	,	,	PUNCT
ap-1785	100	14	h1,s	h1,s	PROPN
ap-1785	100	15	,	,	PUNCT
ap-1785	100	16	h1,b	h1,b	PROPN
ap-1785	100	17	,	,	PUNCT
ap-1785	100	18	and	and	CCONJ
ap-1785	100	19	they	they	PRON
ap-1785	100	20	have	have	VERB
ap-1785	100	21	a	a	DET
ap-1785	100	22	2	2	NUM
ap-1785	100	23	%	%	NOUN
ap-1785	100	24	level	level	NOUN
ap-1785	100	25	of	of	ADP
ap-1785	100	26	significance	significance	NOUN
ap-1785	100	27	.	.	PUNCT
ap-1785	101	1	the	the	DET
ap-1785	101	2	rest	rest	NOUN
ap-1785	101	3	of	of	ADP
ap-1785	101	4	the	the	DET
ap-1785	101	5	estimates	estimate	NOUN
ap-1785	101	6	also	also	ADV
ap-1785	101	7	have	have	VERB
ap-1785	101	8	results	result	NOUN
ap-1785	101	9	under	under	ADP
ap-1785	101	10	a	a	DET
ap-1785	101	11	5	5	NUM
ap-1785	101	12	%	%	NOUN
ap-1785	101	13	level	level	NOUN
ap-1785	101	14	of	of	ADP
ap-1785	101	15	significance	significance	NOUN
ap-1785	101	16	,	,	PUNCT
ap-1785	101	17	except	except	SCONJ
ap-1785	101	18	for	for	ADP
ap-1785	101	19	h2,n	h2,n	ADJ
ap-1785	101	20	,	,	PUNCT
ap-1785	101	21	estimate	estimate	NOUN
ap-1785	101	22	ed̂q(ad	ed̂q(ad	NOUN
ap-1785	101	23	)	)	PUNCT
ap-1785	101	24	ed̂q(als	ed̂q(al	NOUN
ap-1785	101	25	)	)	PUNCT
ap-1785	101	26	pvalue	pvalue	NOUN
ap-1785	102	1	h0,n	h0,n	PROPN
ap-1785	102	2	1.9745	1.9745	NUM
ap-1785	102	3	2.0315	2.0315	NUM
ap-1785	102	4	0.017486	0.017486	NUM
ap-1785	102	5	h1,n	h1,n	PROPN
ap-1785	102	6	2.0649	2.0649	NUM
ap-1785	102	7	2.1096	2.1096	NUM
ap-1785	102	8	0.025128	0.025128	NUM
ap-1785	102	9	h2,n	h2,n	ADJ
ap-1785	102	10	2.0687	2.0687	NUM
ap-1785	102	11	2.1034	2.1034	NUM
ap-1785	102	12	0.067814	0.067814	NUM
ap-1785	102	13	h1,s	h1,s	PROPN
ap-1785	102	14	2.0968	2.0968	NUM
ap-1785	102	15	2.1471	2.1471	NUM
ap-1785	102	16	0.018828	0.018828	NUM
ap-1785	102	17	h2,s	h2,s	PROPN
ap-1785	102	18	2.1458	2.1458	NUM
ap-1785	102	19	2.1903	2.1903	NUM
ap-1785	102	20	0.031375	0.031375	NUM
ap-1785	102	21	h2,s2	h2,s2	PROPN
ap-1785	102	22	1.9274	1.9274	NUM
ap-1785	102	23	1.9666	1.9666	NUM
ap-1785	102	24	0.036419	0.036419	NUM
ap-1785	102	25	h1,b	h1,b	PROPN
ap-1785	102	26	2.0011	2.0011	NUM
ap-1785	102	27	2.0506	2.0506	NUM
ap-1785	102	28	0.018873	0.018873	NUM
ap-1785	102	29	h1,m	h1,m	PROPN
ap-1785	102	30	2.2607	2.2607	NUM
ap-1785	102	31	2.3115	2.3115	NUM
ap-1785	102	32	0.041142	0.041142	NUM
ap-1785	102	33	h1,hn	h1,hn	ADP
ap-1785	102	34	2.2428	2.2428	NUM
ap-1785	102	35	2.2931	2.2931	NUM
ap-1785	102	36	0.037608	0.037608	NUM
ap-1785	102	37	h1,hs	h1,hs	PROPN
ap-1785	102	38	2.2452	2.2452	NUM
ap-1785	102	39	2.2957	2.2957	NUM
ap-1785	102	40	0.037729	0.037729	NUM
ap-1785	102	41	h1,hb	h1,hb	NOUN
ap-1785	102	42	2.2366	2.2366	NUM
ap-1785	102	43	2.2868	2.2868	NUM
ap-1785	102	44	0.035800	0.035800	NUM
ap-1785	102	45	table	table	NOUN
ap-1785	102	46	3	3	NUM
ap-1785	102	47	.	.	PUNCT
ap-1785	102	48	diagnostic	diagnostic	ADJ
ap-1785	102	49	power	power	NOUN
ap-1785	102	50	.	.	PUNCT
ap-1785	103	1	which	which	PRON
ap-1785	103	2	was	be	AUX
ap-1785	103	3	worst	bad	ADJ
ap-1785	103	4	.	.	PUNCT
ap-1785	104	1	on	on	ADP
ap-1785	104	2	hte	hte	PROPN
ap-1785	104	3	basis	basis	NOUN
ap-1785	104	4	of	of	ADP
ap-1785	104	5	these	these	DET
ap-1785	104	6	results	result	NOUN
ap-1785	104	7	,	,	PUNCT
ap-1785	104	8	entropy	entropy	PROPN
ap-1785	104	9	can	can	AUX
ap-1785	104	10	be	be	AUX
ap-1785	104	11	used	use	VERB
ap-1785	104	12	for	for	ADP
ap-1785	104	13	diagnosing	diagnose	VERB
ap-1785	104	14	alzheimer	alzheimer	PROPN
ap-1785	104	15	’s	’s	PART
ap-1785	104	16	disease	disease	NOUN
ap-1785	104	17	in	in	ADP
ap-1785	104	18	the	the	DET
ap-1785	104	19	future	future	NOUN
ap-1785	104	20	,	,	PUNCT
ap-1785	104	21	considering	consider	VERB
ap-1785	104	22	that	that	SCONJ
ap-1785	104	23	methods	method	NOUN
ap-1785	104	24	can	can	AUX
ap-1785	104	25	be	be	AUX
ap-1785	104	26	still	still	ADV
ap-1785	104	27	improved	improve	VERB
ap-1785	104	28	,	,	PUNCT
ap-1785	104	29	especially	especially	ADV
ap-1785	104	30	by	by	ADP
ap-1785	104	31	estimating	estimate	VERB
ap-1785	104	32	kn	kn	PROPN
ap-1785	104	33	or	or	CCONJ
ap-1785	104	34	by	by	ADP
ap-1785	104	35	image	image	NOUN
ap-1785	104	36	filtering	filtering	NOUN
ap-1785	104	37	.	.	PUNCT
ap-1785	105	1	acknowledgements	acknowledgement	NOUN
ap-1785	105	2	this	this	DET
ap-1785	105	3	paper	paper	NOUN
ap-1785	105	4	was	be	AUX
ap-1785	105	5	created	create	VERB
ap-1785	105	6	with	with	ADP
ap-1785	105	7	support	support	NOUN
ap-1785	105	8	from	from	ADP
ap-1785	105	9	ctu	ctu	NOUN
ap-1785	105	10	in	in	ADP
ap-1785	105	11	prague	prague	PROPN
ap-1785	105	12	grant	grant	PROPN
ap-1785	105	13	sgs11/165	sgs11/165	PROPN
ap-1785	105	14	/	/	SYM
ap-1785	105	15	ohk4/3t/14	ohk4/3t/14	PROPN
ap-1785	105	16	.	.	PUNCT
ap-1785	106	1	references	reference	NOUN
ap-1785	106	2	[	[	X
ap-1785	106	3	1	1	NUM
ap-1785	106	4	]	]	PUNCT
ap-1785	106	5	theiler	theiler	NOUN
ap-1785	106	6	,	,	PUNCT
ap-1785	106	7	j.	j.	PROPN
ap-1785	106	8	,	,	PUNCT
ap-1785	106	9	estimating	estimate	VERB
ap-1785	106	10	fractal	fractal	ADJ
ap-1785	106	11	dimension	dimension	NOUN
ap-1785	106	12	.	.	PUNCT
ap-1785	107	1	journal	journal	NOUN
ap-1785	107	2	of	of	ADP
ap-1785	107	3	the	the	DET
ap-1785	107	4	optical	optical	ADJ
ap-1785	107	5	society	society	NOUN
ap-1785	107	6	of	of	ADP
ap-1785	107	7	america	america	PROPN
ap-1785	107	8	,	,	PUNCT
ap-1785	107	9	vol	vol	NOUN
ap-1785	107	10	.	.	PROPN
ap-1785	107	11	7	7	NUM
ap-1785	107	12	,	,	PUNCT
ap-1785	107	13	no	no	INTJ
ap-1785	107	14	.	.	NOUN
ap-1785	107	15	6	6	NUM
ap-1785	107	16	1990	1990	NUM
ap-1785	107	17	,	,	PUNCT
ap-1785	107	18	pp	pp	ADJ
ap-1785	107	19	.	.	PUNCT
ap-1785	107	20	1055–1073	1055–1073	NUM
ap-1785	107	21	.	.	PUNCT
ap-1785	108	1	[	[	X
ap-1785	108	2	2	2	NUM
ap-1785	108	3	]	]	SYM
ap-1785	108	4	renyi	renyi	PROPN
ap-1785	108	5	,	,	PUNCT
ap-1785	108	6	a.	a.	NOUN
ap-1785	108	7	,	,	PUNCT
ap-1785	108	8	on	on	ADP
ap-1785	108	9	measures	measure	NOUN
ap-1785	108	10	of	of	ADP
ap-1785	108	11	entropy	entropy	NOUN
ap-1785	108	12	and	and	CCONJ
ap-1785	108	13	information	information	NOUN
ap-1785	108	14	.	.	PUNCT
ap-1785	109	1	77	77	NUM
ap-1785	109	2	v.	v.	ADP
ap-1785	109	3	hubata	hubata	PROPN
ap-1785	109	4	-	-	PUNCT
ap-1785	109	5	vacek	vacek	PROPN
ap-1785	109	6	,	,	PUNCT
ap-1785	109	7	j.	j.	PROPN
ap-1785	109	8	kukal	kukal	PROPN
ap-1785	109	9	,	,	PUNCT
ap-1785	109	10	r.	r.	PROPN
ap-1785	109	11	rusina	rusina	PROPN
ap-1785	109	12	,	,	PUNCT
ap-1785	109	13	m.	m.	NOUN
ap-1785	109	14	buncová	buncová	PROPN
ap-1785	109	15	acta	acta	PROPN
ap-1785	109	16	polytechnica	polytechnica	PROPN
ap-1785	109	17	berkeley	berkeley	PROPN
ap-1785	109	18	symposium	symposium	NOUN
ap-1785	109	19	on	on	ADP
ap-1785	109	20	mathematical	mathematical	ADJ
ap-1785	109	21	statistics	statistic	NOUN
ap-1785	109	22	and	and	CCONJ
ap-1785	109	23	probability	probability	NOUN
ap-1785	109	24	,	,	PUNCT
ap-1785	109	25	vol	vol	NOUN
ap-1785	109	26	.	.	PROPN
ap-1785	109	27	1	1	NUM
ap-1785	109	28	,	,	PUNCT
ap-1785	109	29	1961	1961	NUM
ap-1785	109	30	,	,	PUNCT
ap-1785	109	31	p.	p.	NOUN
ap-1785	109	32	547	547	NUM
ap-1785	109	33	.	.	PUNCT
ap-1785	110	1	[	[	X
ap-1785	110	2	3	3	NUM
ap-1785	110	3	]	]	X
ap-1785	110	4	hartley	hartley	NOUN
ap-1785	110	5	,	,	PUNCT
ap-1785	110	6	r.v.l	r.v.l	ADJ
ap-1785	110	7	.	.	PROPN
ap-1785	110	8	,	,	PUNCT
ap-1785	110	9	transmission	transmission	NOUN
ap-1785	110	10	of	of	ADP
ap-1785	110	11	information	information	NOUN
ap-1785	110	12	.	.	PUNCT
ap-1785	111	1	bell	bell	NOUN
ap-1785	111	2	system	system	PROPN
ap-1785	111	3	technical	technical	PROPN
ap-1785	111	4	journal	journal	PROPN
ap-1785	111	5	,	,	PUNCT
ap-1785	111	6	vol	vol	NOUN
ap-1785	111	7	.	.	PROPN
ap-1785	111	8	7	7	NUM
ap-1785	111	9	,	,	PUNCT
ap-1785	111	10	1928	1928	NUM
ap-1785	111	11	,	,	PUNCT
ap-1785	111	12	535	535	NUM
ap-1785	111	13	.	.	PUNCT
ap-1785	112	1	[	[	X
ap-1785	112	2	4	4	NUM
ap-1785	112	3	]	]	X
ap-1785	112	4	shannon	shannon	PROPN
ap-1785	112	5	,	,	PUNCT
ap-1785	112	6	c.e	c.e	PROPN
ap-1785	112	7	.	.	PROPN
ap-1785	112	8	,	,	PUNCT
ap-1785	112	9	a	a	DET
ap-1785	112	10	mathematical	mathematical	ADJ
ap-1785	112	11	theory	theory	NOUN
ap-1785	112	12	of	of	ADP
ap-1785	112	13	communication	communication	NOUN
ap-1785	112	14	.	.	PUNCT
ap-1785	113	1	bell	bell	NOUN
ap-1785	113	2	system	system	PROPN
ap-1785	113	3	technical	technical	PROPN
ap-1785	113	4	journal	journal	NOUN
ap-1785	113	5	,	,	PUNCT
ap-1785	113	6	1948	1948	NUM
ap-1785	113	7	.	.	PUNCT
ap-1785	114	1	[	[	X
ap-1785	114	2	5	5	NUM
ap-1785	114	3	]	]	X
ap-1785	114	4	harris	harris	PROPN
ap-1785	114	5	,	,	PUNCT
ap-1785	114	6	b.	b.	PROPN
ap-1785	114	7	,	,	PUNCT
ap-1785	114	8	the	the	DET
ap-1785	114	9	statistical	statistical	ADJ
ap-1785	114	10	estimation	estimation	NOUN
ap-1785	114	11	of	of	ADP
ap-1785	114	12	entropy	entropy	NOUN
ap-1785	114	13	in	in	ADP
ap-1785	114	14	the	the	DET
ap-1785	114	15	non	non	ADJ
ap-1785	114	16	-	-	ADJ
ap-1785	114	17	parametric	parametric	ADJ
ap-1785	114	18	case	case	NOUN
ap-1785	114	19	.	.	PUNCT
ap-1785	114	20	mrc	mrc	PROPN
ap-1785	114	21	technical	technical	PROPN
ap-1785	114	22	summary	summary	PROPN
ap-1785	114	23	report	report	NOUN
ap-1785	114	24	,	,	PUNCT
ap-1785	114	25	1975	1975	NUM
ap-1785	114	26	.	.	PUNCT
ap-1785	115	1	[	[	X
ap-1785	115	2	6	6	NUM
ap-1785	115	3	]	]	X
ap-1785	115	4	gomez	gomez	PROPN
ap-1785	115	5	,	,	PUNCT
ap-1785	115	6	c.	c.	PROPN
ap-1785	115	7	,	,	PUNCT
ap-1785	115	8	mediavilla	mediavilla	PROPN
ap-1785	115	9	,	,	PUNCT
ap-1785	115	10	a.	a.	NOUN
ap-1785	115	11	,	,	PUNCT
ap-1785	115	12	hornero	hornero	PROPN
ap-1785	115	13	,	,	PUNCT
ap-1785	115	14	r.	r.	PROPN
ap-1785	115	15	,	,	PUNCT
ap-1785	115	16	abasolo	abasolo	PROPN
ap-1785	115	17	,	,	PUNCT
ap-1785	115	18	d.	d.	PROPN
ap-1785	115	19	,	,	PUNCT
ap-1785	115	20	fernandez	fernandez	PROPN
ap-1785	115	21	,	,	PUNCT
ap-1785	115	22	a.	a.	NOUN
ap-1785	115	23	,	,	PUNCT
ap-1785	115	24	use	use	NOUN
ap-1785	115	25	of	of	ADP
ap-1785	115	26	the	the	DET
ap-1785	115	27	higuchi	higuchi	PROPN
ap-1785	115	28	’s	’s	PART
ap-1785	115	29	fractal	fractal	ADJ
ap-1785	115	30	dimension	dimension	NOUN
ap-1785	115	31	for	for	ADP
ap-1785	115	32	the	the	DET
ap-1785	115	33	analysis	analysis	NOUN
ap-1785	115	34	of	of	ADP
ap-1785	115	35	meg	meg	NOUN
ap-1785	115	36	recordings	recording	NOUN
ap-1785	115	37	from	from	ADP
ap-1785	115	38	alzheimer	alzheimer	PROPN
ap-1785	115	39	’s	’s	PART
ap-1785	115	40	disease	disease	NOUN
ap-1785	115	41	patients	patient	NOUN
ap-1785	115	42	.	.	PUNCT
ap-1785	116	1	medical	medical	ADJ
ap-1785	116	2	engineering	engineering	PROPN
ap-1785	116	3	&	&	CCONJ
ap-1785	116	4	physics	physics	PROPN
ap-1785	116	5	,	,	PUNCT
ap-1785	116	6	volume	volume	NOUN
ap-1785	116	7	31	31	NUM
ap-1785	116	8	,	,	PUNCT
ap-1785	116	9	issue	issue	NOUN
ap-1785	116	10	3	3	NUM
ap-1785	116	11	,	,	PUNCT
ap-1785	116	12	april	april	PROPN
ap-1785	116	13	2009	2009	NUM
ap-1785	116	14	,	,	PUNCT
ap-1785	116	15	pp	pp	ADV
ap-1785	116	16	.	.	PUNCT
ap-1785	117	1	306–313	306–313	NUM
ap-1785	117	2	.	.	PUNCT
ap-1785	118	1	[	[	X
ap-1785	118	2	7	7	NUM
ap-1785	118	3	]	]	X
ap-1785	118	4	jouny	jouny	PROPN
ap-1785	118	5	,	,	PUNCT
ap-1785	118	6	c.c	c.c	PROPN
ap-1785	118	7	.	.	PROPN
ap-1785	118	8	,	,	PUNCT
ap-1785	118	9	bergey	bergey	PROPN
ap-1785	118	10	,	,	PUNCT
ap-1785	118	11	g.k	g.k	PROPN
ap-1785	118	12	.	.	PROPN
ap-1785	118	13	,	,	PUNCT
ap-1785	118	14	characterization	characterization	NOUN
ap-1785	118	15	of	of	ADP
ap-1785	118	16	early	early	ADJ
ap-1785	118	17	partial	partial	ADJ
ap-1785	118	18	seizure	seizure	NOUN
ap-1785	118	19	onset	onset	NOUN
ap-1785	118	20	:	:	PUNCT
ap-1785	118	21	frequency	frequency	NOUN
ap-1785	118	22	,	,	PUNCT
ap-1785	118	23	complexity	complexity	NOUN
ap-1785	118	24	and	and	CCONJ
ap-1785	118	25	entropy	entropy	NOUN
ap-1785	118	26	.	.	PUNCT
ap-1785	119	1	clinical	clinical	ADJ
ap-1785	119	2	neurophysiology	neurophysiology	NOUN
ap-1785	119	3	,	,	PUNCT
ap-1785	119	4	volume	volume	NOUN
ap-1785	119	5	123	123	NUM
ap-1785	119	6	,	,	PUNCT
ap-1785	119	7	issue	issue	NOUN
ap-1785	119	8	4	4	NUM
ap-1785	119	9	,	,	PUNCT
ap-1785	119	10	april	april	PROPN
ap-1785	119	11	2012	2012	NUM
ap-1785	119	12	,	,	PUNCT
ap-1785	119	13	pp	pp	X
ap-1785	119	14	.	.	PUNCT
ap-1785	120	1	658–669	658–669	NUM
ap-1785	120	2	.	.	PUNCT
ap-1785	121	1	[	[	X
ap-1785	121	2	8	8	NUM
ap-1785	121	3	]	]	X
ap-1785	121	4	lopes	lope	NOUN
ap-1785	121	5	,	,	PUNCT
ap-1785	121	6	r.	r.	PROPN
ap-1785	121	7	,	,	PUNCT
ap-1785	121	8	betrouni	betrouni	PROPN
ap-1785	121	9	,	,	PUNCT
ap-1785	121	10	n.	n.	NOUN
ap-1785	121	11	,	,	PUNCT
ap-1785	121	12	fractal	fractal	ADJ
ap-1785	121	13	and	and	CCONJ
ap-1785	121	14	multifractal	multifractal	ADJ
ap-1785	121	15	analysis	analysis	NOUN
ap-1785	121	16	:	:	PUNCT
ap-1785	121	17	a	a	DET
ap-1785	121	18	review	review	NOUN
ap-1785	121	19	.	.	PUNCT
ap-1785	122	1	medical	medical	ADJ
ap-1785	122	2	image	image	NOUN
ap-1785	122	3	analysis	analysis	NOUN
ap-1785	122	4	,	,	PUNCT
ap-1785	122	5	volume	volume	NOUN
ap-1785	122	6	13	13	NUM
ap-1785	122	7	,	,	PUNCT
ap-1785	122	8	issue	issue	NOUN
ap-1785	122	9	4	4	NUM
ap-1785	122	10	,	,	PUNCT
ap-1785	122	11	august	august	PROPN
ap-1785	122	12	2009	2009	NUM
ap-1785	122	13	,	,	PUNCT
ap-1785	122	14	pp	pp	ADV
ap-1785	122	15	.	.	PUNCT
ap-1785	123	1	634–649	634–649	NUM
ap-1785	123	2	.	.	PUNCT
ap-1785	124	1	[	[	X
ap-1785	124	2	9	9	NUM
ap-1785	124	3	]	]	X
ap-1785	124	4	polychronaki	polychronaki	NOUN
ap-1785	124	5	,	,	PUNCT
ap-1785	124	6	g.e	g.e	PROPN
ap-1785	124	7	.	.	PROPN
ap-1785	124	8	,	,	PUNCT
ap-1785	124	9	ktonas	ktonas	PROPN
ap-1785	124	10	,	,	PUNCT
ap-1785	124	11	p.	p.	PROPN
ap-1785	124	12	y.	y.	PROPN
ap-1785	124	13	,	,	PUNCT
ap-1785	124	14	gatzonis	gatzonis	PROPN
ap-1785	124	15	,	,	PUNCT
ap-1785	124	16	s.	s.	PROPN
ap-1785	124	17	,	,	PUNCT
ap-1785	124	18	siatouni	siatouni	PROPN
ap-1785	124	19	,	,	PUNCT
ap-1785	124	20	a.	a.	NOUN
ap-1785	124	21	,	,	PUNCT
ap-1785	124	22	asvestas	asvesta	NOUN
ap-1785	124	23	,	,	PUNCT
ap-1785	124	24	p.	p.	NOUN
ap-1785	124	25	a.	a.	NOUN
ap-1785	124	26	,	,	PUNCT
ap-1785	124	27	h	h	PROPN
ap-1785	124	28	tsekou	tsekou	PROPN
ap-1785	124	29	,	,	PUNCT
ap-1785	124	30	h.	h.	PROPN
ap-1785	124	31	,	,	PUNCT
ap-1785	124	32	sakas	sakas	PROPN
ap-1785	124	33	,	,	PUNCT
ap-1785	124	34	d.	d.	PROPN
ap-1785	124	35	and	and	CCONJ
ap-1785	124	36	nikita	nikita	PROPN
ap-1785	124	37	,	,	PUNCT
ap-1785	124	38	k.s	k.s	PROPN
ap-1785	124	39	.	.	PROPN
ap-1785	124	40	,	,	PUNCT
ap-1785	124	41	comparison	comparison	NOUN
ap-1785	124	42	of	of	ADP
ap-1785	124	43	fractal	fractal	ADJ
ap-1785	124	44	dimension	dimension	NOUN
ap-1785	124	45	estimation	estimation	NOUN
ap-1785	124	46	algorithms	algorithm	NOUN
ap-1785	124	47	for	for	ADP
ap-1785	124	48	epileptic	epileptic	ADJ
ap-1785	124	49	seizure	seizure	NOUN
ap-1785	124	50	onset	onset	NOUN
ap-1785	124	51	detection	detection	NOUN
ap-1785	124	52	.	.	PUNCT
ap-1785	125	1	journal	journal	NOUN
ap-1785	125	2	of	of	ADP
ap-1785	125	3	neural	neural	ADJ
ap-1785	125	4	engineering	engineering	NOUN
ap-1785	125	5	7	7	NUM
ap-1785	125	6	(	(	PUNCT
ap-1785	125	7	2010	2010	NUM
ap-1785	125	8	)	)	PUNCT
ap-1785	125	9	.	.	PUNCT
ap-1785	126	1	78	78	NUM
ap-1785	126	2	acta	acta	PROPN
ap-1785	126	3	polytechnica	polytechnica	PROPN
ap-1785	126	4	53(2):75–78	53(2):75–78	NUM
ap-1785	126	5	,	,	PUNCT
ap-1785	126	6	2013	2013	NUM
ap-1785	126	7	1	1	NUM
ap-1785	126	8	introduction	introduction	NOUN
ap-1785	126	9	2	2	NUM
ap-1785	126	10	rényi	rényi	NOUN
ap-1785	126	11	entropy	entropy	NOUN
ap-1785	126	12	3	3	NUM
ap-1785	126	13	entropy	entropy	NOUN
ap-1785	126	14	estimates	estimate	VERB
ap-1785	126	15	4	4	NUM
ap-1785	126	16	bias	bias	NOUN
ap-1785	126	17	reduction	reduction	NOUN
ap-1785	126	18	5	5	NUM
ap-1785	126	19	estimation	estimation	NOUN
ap-1785	126	20	methodology	methodology	NOUN
ap-1785	126	21	6	6	NUM
ap-1785	126	22	alzheimer	alzheimer	NOUN
ap-1785	126	23	's	's	PART
ap-1785	126	24	disease	disease	NOUN
ap-1785	126	25	diagnosis	diagnosis	NOUN
ap-1785	126	26	from	from	ADP
ap-1785	126	27	fractal	fractal	ADJ
ap-1785	126	28	dimension	dimension	NOUN
ap-1785	126	29	estimates	estimate	VERB
ap-1785	126	30	7	7	NUM
ap-1785	126	31	conclusion	conclusion	NOUN
ap-1785	126	32	acknowledgements	acknowledgement	NOUN
ap-1785	126	33	references	reference	NOUN