id	sid	tid	token	lemma	pos
ispiv-92	1	1	14th	14th	ADJ
ispiv-92	1	2	international	international	ADJ
ispiv-92	1	3	symposium	symposium	NOUN
ispiv-92	1	4	on	on	ADP
ispiv-92	1	5	particle	particle	NOUN
ispiv-92	1	6	image	image	NOUN
ispiv-92	1	7	velocimetry	velocimetry	NOUN
ispiv-92	1	8	–	–	PUNCT
ispiv-92	1	9	ispiv	ispiv	NOUN
ispiv-92	1	10	2021	2021	NUM
ispiv-92	1	11	august	august	PROPN
ispiv-92	1	12	1–5	1–5	NUM
ispiv-92	1	13	,	,	PUNCT
ispiv-92	1	14	2021	2021	NUM
ispiv-92	1	15	trackfit	trackfit	NOUN
ispiv-92	1	16	:	:	PUNCT
ispiv-92	1	17	uncertainty	uncertainty	NOUN
ispiv-92	1	18	quantification	quantification	NOUN
ispiv-92	1	19	,	,	PUNCT
ispiv-92	1	20	optimal	optimal	ADJ
ispiv-92	1	21	filtering	filtering	NOUN
ispiv-92	1	22	and	and	CCONJ
ispiv-92	1	23	interpolation	interpolation	NOUN
ispiv-92	1	24	of	of	ADP
ispiv-92	1	25	tracks	track	NOUN
ispiv-92	1	26	for	for	ADP
ispiv-92	1	27	time	time	NOUN
ispiv-92	1	28	-	-	PUNCT
ispiv-92	1	29	resolved	resolve	VERB
ispiv-92	1	30	lagrangian	lagrangian	ADJ
ispiv-92	1	31	particle	particle	NOUN
ispiv-92	1	32	tracking	track	VERB
ispiv-92	1	33	s.	s.	PROPN
ispiv-92	1	34	gesemann1∗	gesemann1∗	PROPN
ispiv-92	1	35	1	1	NUM
ispiv-92	1	36	dlr	dlr	NOUN
ispiv-92	1	37	(	(	PUNCT
ispiv-92	1	38	german	german	ADJ
ispiv-92	1	39	aerospace	aerospace	NOUN
ispiv-92	1	40	center	center	NOUN
ispiv-92	1	41	)	)	PUNCT
ispiv-92	1	42	,	,	PUNCT
ispiv-92	1	43	institute	institute	NOUN
ispiv-92	1	44	of	of	ADP
ispiv-92	1	45	aerodynamics	aerodynamic	NOUN
ispiv-92	1	46	and	and	CCONJ
ispiv-92	1	47	flow	flow	NOUN
ispiv-92	1	48	technology	technology	NOUN
ispiv-92	1	49	,	,	PUNCT
ispiv-92	1	50	department	department	NOUN
ispiv-92	1	51	of	of	ADP
ispiv-92	1	52	experimental	experimental	ADJ
ispiv-92	1	53	methods	method	NOUN
ispiv-92	1	54	,	,	PUNCT
ispiv-92	1	55	göttingen	göttingen	PROPN
ispiv-92	1	56	,	,	PUNCT
ispiv-92	1	57	germany	germany	PROPN
ispiv-92	1	58	∗	∗	NOUN
ispiv-92	1	59	sebastian.gesemann@dlr.de	sebastian.gesemann@dlr.de	PROPN
ispiv-92	2	1	abstract	abstract	ADJ
ispiv-92	2	2	advanced	advance	VERB
ispiv-92	2	3	lagrangian	lagrangian	ADJ
ispiv-92	2	4	particle	particle	NOUN
ispiv-92	2	5	tracking	tracking	NOUN
ispiv-92	2	6	methods	method	NOUN
ispiv-92	2	7	(	(	PUNCT
ispiv-92	2	8	such	such	ADJ
ispiv-92	2	9	as	as	ADP
ispiv-92	2	10	the	the	DET
ispiv-92	2	11	stb	stb	PROPN
ispiv-92	2	12	algorithm	algorithm	NOUN
ispiv-92	2	13	(	(	PUNCT
ispiv-92	2	14	schanz	schanz	PROPN
ispiv-92	2	15	et	et	PROPN
ispiv-92	2	16	al	al	PROPN
ispiv-92	2	17	.	.	PROPN
ispiv-92	2	18	2016	2016	NUM
ispiv-92	2	19	)	)	PUNCT
ispiv-92	2	20	)	)	PUNCT
ispiv-92	2	21	are	be	AUX
ispiv-92	2	22	a	a	DET
ispiv-92	2	23	very	very	ADV
ispiv-92	2	24	useful	useful	ADJ
ispiv-92	2	25	tool	tool	NOUN
ispiv-92	2	26	for	for	ADP
ispiv-92	2	27	uncovering	uncover	VERB
ispiv-92	2	28	properties	property	NOUN
ispiv-92	2	29	of	of	ADP
ispiv-92	2	30	flow	flow	NOUN
ispiv-92	2	31	.	.	PUNCT
ispiv-92	3	1	as	as	ADP
ispiv-92	3	2	a	a	DET
ispiv-92	3	3	measurement	measurement	NOUN
ispiv-92	3	4	technique	technique	NOUN
ispiv-92	3	5	,	,	PUNCT
ispiv-92	3	6	the	the	DET
ispiv-92	3	7	results	result	NOUN
ispiv-92	3	8	of	of	ADP
ispiv-92	3	9	such	such	ADJ
ispiv-92	3	10	methods	method	NOUN
ispiv-92	3	11	are	be	AUX
ispiv-92	3	12	perturbed	perturb	VERB
ispiv-92	3	13	by	by	ADP
ispiv-92	3	14	different	different	ADJ
ispiv-92	3	15	sources	source	NOUN
ispiv-92	3	16	of	of	ADP
ispiv-92	3	17	errors	error	NOUN
ispiv-92	3	18	and	and	CCONJ
ispiv-92	3	19	noise	noise	NOUN
ispiv-92	3	20	.	.	PUNCT
ispiv-92	4	1	this	this	DET
ispiv-92	4	2	work	work	NOUN
ispiv-92	4	3	addresses	address	VERB
ispiv-92	4	4	the	the	DET
ispiv-92	4	5	problem	problem	NOUN
ispiv-92	4	6	of	of	ADP
ispiv-92	4	7	optimal	optimal	ADJ
ispiv-92	4	8	filtering	filtering	NOUN
ispiv-92	4	9	of	of	ADP
ispiv-92	4	10	particle	particle	NOUN
ispiv-92	4	11	tracks	track	NOUN
ispiv-92	4	12	as	as	ADV
ispiv-92	4	13	well	well	ADV
ispiv-92	4	14	as	as	ADP
ispiv-92	4	15	estimating	estimate	VERB
ispiv-92	4	16	uncertainties	uncertainty	NOUN
ispiv-92	4	17	of	of	ADP
ispiv-92	4	18	derived	derive	VERB
ispiv-92	4	19	quantities	quantity	NOUN
ispiv-92	4	20	such	such	ADJ
ispiv-92	4	21	as	as	ADP
ispiv-92	4	22	location	location	NOUN
ispiv-92	4	23	,	,	PUNCT
ispiv-92	4	24	velocity	velocity	NOUN
ispiv-92	4	25	and	and	CCONJ
ispiv-92	4	26	acceleration	acceleration	NOUN
ispiv-92	4	27	of	of	ADP
ispiv-92	4	28	observed	observed	ADJ
ispiv-92	4	29	particles	particle	NOUN
ispiv-92	4	30	.	.	PUNCT
ispiv-92	5	1	the	the	DET
ispiv-92	5	2	behavior	behavior	NOUN
ispiv-92	5	3	and	and	CCONJ
ispiv-92	5	4	performance	performance	NOUN
ispiv-92	5	5	of	of	ADP
ispiv-92	5	6	this	this	DET
ispiv-92	5	7	new	new	ADJ
ispiv-92	5	8	filtering	filtering	NOUN
ispiv-92	5	9	method	method	NOUN
ispiv-92	5	10	(	(	PUNCT
ispiv-92	5	11	“	"	PUNCT
ispiv-92	5	12	trackfit	trackfit	ADJ
ispiv-92	5	13	”	"	PUNCT
ispiv-92	5	14	)	)	PUNCT
ispiv-92	5	15	,	,	PUNCT
ispiv-92	5	16	first	first	ADV
ispiv-92	5	17	introduced	introduce	VERB
ispiv-92	5	18	at	at	ADP
ispiv-92	5	19	gesemann	gesemann	PROPN
ispiv-92	5	20	et	et	PROPN
ispiv-92	5	21	al	al	PROPN
ispiv-92	5	22	.	.	PUNCT
ispiv-92	6	1	(	(	PUNCT
ispiv-92	6	2	2016	2016	NUM
ispiv-92	6	3	)	)	PUNCT
ispiv-92	6	4	is	be	AUX
ispiv-92	6	5	analyzed	analyze	VERB
ispiv-92	6	6	and	and	CCONJ
ispiv-92	6	7	compared	compare	VERB
ispiv-92	6	8	to	to	ADP
ispiv-92	6	9	the	the	DET
ispiv-92	6	10	savitzky	savitzky	NOUN
ispiv-92	6	11	–	–	PUNCT
ispiv-92	6	12	golay	golay	NOUN
ispiv-92	6	13	filter	filter	NOUN
ispiv-92	6	14	(	(	PUNCT
ispiv-92	6	15	savitzky	savitzky	NOUN
ispiv-92	6	16	and	and	CCONJ
ispiv-92	6	17	golay	golay	NOUN
ispiv-92	6	18	(	(	PUNCT
ispiv-92	6	19	1964	1964	NUM
ispiv-92	6	20	)	)	PUNCT
ispiv-92	6	21	)	)	PUNCT
ispiv-92	6	22	which	which	PRON
ispiv-92	6	23	is	be	AUX
ispiv-92	6	24	commonly	commonly	ADV
ispiv-92	6	25	used	use	VERB
ispiv-92	6	26	for	for	ADP
ispiv-92	6	27	these	these	DET
ispiv-92	6	28	purposes	purpose	NOUN
ispiv-92	6	29	.	.	PUNCT
ispiv-92	7	1	the	the	DET
ispiv-92	7	2	optimal	optimal	ADJ
ispiv-92	7	3	choice	choice	NOUN
ispiv-92	7	4	of	of	ADP
ispiv-92	7	5	parameters	parameter	NOUN
ispiv-92	7	6	of	of	ADP
ispiv-92	7	7	this	this	DET
ispiv-92	7	8	filtering	filtering	NOUN
ispiv-92	7	9	method	method	NOUN
ispiv-92	7	10	as	as	ADV
ispiv-92	7	11	well	well	ADV
ispiv-92	7	12	as	as	ADP
ispiv-92	7	13	the	the	DET
ispiv-92	7	14	uncertainty	uncertainty	NOUN
ispiv-92	7	15	quantification	quantification	NOUN
ispiv-92	7	16	of	of	ADP
ispiv-92	7	17	the	the	DET
ispiv-92	7	18	reconstructed	reconstructed	ADJ
ispiv-92	7	19	tracks	track	NOUN
ispiv-92	7	20	can	can	AUX
ispiv-92	7	21	be	be	AUX
ispiv-92	7	22	extracted	extract	VERB
ispiv-92	7	23	from	from	ADP
ispiv-92	7	24	a	a	DET
ispiv-92	7	25	spectral	spectral	ADJ
ispiv-92	7	26	analysis	analysis	NOUN
ispiv-92	7	27	of	of	ADP
ispiv-92	7	28	the	the	DET
ispiv-92	7	29	recorded	record	VERB
ispiv-92	7	30	raw	raw	ADJ
ispiv-92	7	31	particle	particle	NOUN
ispiv-92	7	32	tracking	tracking	NOUN
ispiv-92	7	33	data	datum	NOUN
ispiv-92	7	34	.	.	PUNCT
ispiv-92	8	1	this	this	PRON
ispiv-92	8	2	is	be	AUX
ispiv-92	8	3	in	in	ADP
ispiv-92	8	4	contrast	contrast	NOUN
ispiv-92	8	5	to	to	ADP
ispiv-92	8	6	a	a	DET
ispiv-92	8	7	savitzky	savitzky	ADJ
ispiv-92	8	8	–	–	PUNCT
ispiv-92	8	9	golay	golay	NOUN
ispiv-92	8	10	filter	filter	NOUN
ispiv-92	8	11	where	where	SCONJ
ispiv-92	8	12	the	the	DET
ispiv-92	8	13	choice	choice	NOUN
ispiv-92	8	14	of	of	ADP
ispiv-92	8	15	parameters	parameter	NOUN
ispiv-92	8	16	might	might	AUX
ispiv-92	8	17	often	often	ADV
ispiv-92	8	18	be	be	AUX
ispiv-92	8	19	driven	drive	VERB
ispiv-92	8	20	by	by	ADP
ispiv-92	8	21	experience	experience	NOUN
ispiv-92	8	22	and	and	CCONJ
ispiv-92	8	23	gut	gut	NOUN
ispiv-92	8	24	feeling	feeling	NOUN
ispiv-92	8	25	.	.	PUNCT
ispiv-92	9	1	estimating	estimate	VERB
ispiv-92	9	2	the	the	DET
ispiv-92	9	3	power	power	NOUN
ispiv-92	9	4	spectral	spectral	ADJ
ispiv-92	9	5	density	density	NOUN
ispiv-92	9	6	(	(	PUNCT
ispiv-92	9	7	psd	psd	NOUN
ispiv-92	9	8	)	)	PUNCT
ispiv-92	9	9	of	of	ADP
ispiv-92	9	10	the	the	DET
ispiv-92	9	11	particle	particle	NOUN
ispiv-92	9	12	trajectory	trajectory	NOUN
ispiv-92	9	13	signals	signal	NOUN
ispiv-92	9	14	for	for	ADP
ispiv-92	9	15	the	the	DET
ispiv-92	9	16	purpose	purpose	NOUN
ispiv-92	9	17	of	of	ADP
ispiv-92	9	18	optimal	optimal	ADJ
ispiv-92	9	19	filtering	filtering	NOUN
ispiv-92	9	20	parameter	parameter	NOUN
ispiv-92	9	21	selection	selection	NOUN
ispiv-92	9	22	represents	represent	VERB
ispiv-92	9	23	a	a	DET
ispiv-92	9	24	challenge	challenge	NOUN
ispiv-92	9	25	due	due	ADP
ispiv-92	9	26	to	to	ADP
ispiv-92	9	27	possibly	possibly	ADV
ispiv-92	9	28	short	short	ADJ
ispiv-92	9	29	trajectory	trajectory	NOUN
ispiv-92	9	30	signals	signal	NOUN
ispiv-92	9	31	.	.	PUNCT
ispiv-92	10	1	in	in	ADP
ispiv-92	10	2	the	the	DET
ispiv-92	10	3	following	follow	VERB
ispiv-92	10	4	work	work	NOUN
ispiv-92	10	5	we	we	PRON
ispiv-92	10	6	will	will	AUX
ispiv-92	10	7	present	present	VERB
ispiv-92	10	8	a	a	DET
ispiv-92	10	9	method	method	NOUN
ispiv-92	10	10	for	for	ADP
ispiv-92	10	11	psd	psd	NOUN
ispiv-92	10	12	estimation	estimation	NOUN
ispiv-92	10	13	that	that	PRON
ispiv-92	10	14	is	be	AUX
ispiv-92	10	15	applicable	applicable	ADJ
ispiv-92	10	16	in	in	ADP
ispiv-92	10	17	this	this	DET
ispiv-92	10	18	scenario	scenario	NOUN
ispiv-92	10	19	.	.	PUNCT
ispiv-92	11	1	in	in	ADP
ispiv-92	11	2	addition	addition	NOUN
ispiv-92	11	3	,	,	PUNCT
ispiv-92	11	4	we	we	PRON
ispiv-92	11	5	show	show	VERB
ispiv-92	11	6	that	that	SCONJ
ispiv-92	11	7	regardless	regardless	ADV
ispiv-92	11	8	of	of	ADP
ispiv-92	11	9	the	the	DET
ispiv-92	11	10	choice	choice	NOUN
ispiv-92	11	11	of	of	ADP
ispiv-92	11	12	savitzky	savitzky	NOUN
ispiv-92	11	13	–	–	PUNCT
ispiv-92	11	14	golay	golay	NOUN
ispiv-92	11	15	filter	filter	NOUN
ispiv-92	11	16	parameters	parameter	NOUN
ispiv-92	11	17	,	,	PUNCT
ispiv-92	11	18	the	the	DET
ispiv-92	11	19	resulting	result	VERB
ispiv-92	11	20	filter	filter	NOUN
ispiv-92	11	21	will	will	AUX
ispiv-92	11	22	not	not	PART
ispiv-92	11	23	approximate	approximate	VERB
ispiv-92	11	24	the	the	DET
ispiv-92	11	25	ideal	ideal	ADJ
ispiv-92	11	26	noise	noise	NOUN
ispiv-92	11	27	reduction	reduction	NOUN
ispiv-92	11	28	filter	filter	NOUN
ispiv-92	11	29	well	well	INTJ
ispiv-92	11	30	unlike	unlike	ADP
ispiv-92	11	31	the	the	DET
ispiv-92	11	32	“	"	PUNCT
ispiv-92	11	33	trackfit	trackfit	NOUN
ispiv-92	11	34	”	"	PUNCT
ispiv-92	11	35	described	describe	VERB
ispiv-92	11	36	in	in	ADP
ispiv-92	11	37	this	this	DET
ispiv-92	11	38	work	work	NOUN
ispiv-92	11	39	.	.	PUNCT
ispiv-92	12	1	1	1	NUM
ispiv-92	12	2	introduction	introduction	NOUN
ispiv-92	12	3	in	in	ADP
ispiv-92	12	4	the	the	DET
ispiv-92	12	5	interest	interest	NOUN
ispiv-92	12	6	of	of	ADP
ispiv-92	12	7	optimal	optimal	ADJ
ispiv-92	12	8	noise	noise	NOUN
ispiv-92	12	9	reduction	reduction	NOUN
ispiv-92	12	10	filtering	filtering	NOUN
ispiv-92	12	11	and	and	CCONJ
ispiv-92	12	12	interpolation	interpolation	NOUN
ispiv-92	12	13	for	for	ADP
ispiv-92	12	14	derived	derive	VERB
ispiv-92	12	15	quantities	quantity	NOUN
ispiv-92	12	16	such	such	ADJ
ispiv-92	12	17	as	as	ADP
ispiv-92	12	18	velocity	velocity	NOUN
ispiv-92	12	19	and	and	CCONJ
ispiv-92	12	20	acceleration	acceleration	NOUN
ispiv-92	12	21	and	and	CCONJ
ispiv-92	12	22	their	their	PRON
ispiv-92	12	23	uncertainty	uncertainty	NOUN
ispiv-92	12	24	estimation	estimation	NOUN
ispiv-92	12	25	,	,	PUNCT
ispiv-92	12	26	knowledge	knowledge	NOUN
ispiv-92	12	27	about	about	ADP
ispiv-92	12	28	the	the	DET
ispiv-92	12	29	spectral	spectral	ADJ
ispiv-92	12	30	properties	property	NOUN
ispiv-92	12	31	of	of	ADP
ispiv-92	12	32	the	the	DET
ispiv-92	12	33	position	position	NOUN
ispiv-92	12	34	-	-	PUNCT
ispiv-92	12	35	overtime	overtime	NOUN
ispiv-92	12	36	signals	signal	NOUN
ispiv-92	12	37	is	be	AUX
ispiv-92	12	38	important	important	ADJ
ispiv-92	12	39	.	.	PUNCT
ispiv-92	13	1	we	we	PRON
ispiv-92	13	2	expect	expect	VERB
ispiv-92	13	3	the	the	DET
ispiv-92	13	4	low	low	ADJ
ispiv-92	13	5	frequencies	frequency	NOUN
ispiv-92	13	6	of	of	ADP
ispiv-92	13	7	such	such	ADJ
ispiv-92	13	8	signals	signal	NOUN
ispiv-92	13	9	to	to	PART
ispiv-92	13	10	have	have	VERB
ispiv-92	13	11	a	a	DET
ispiv-92	13	12	lot	lot	NOUN
ispiv-92	13	13	of	of	ADP
ispiv-92	13	14	energy	energy	NOUN
ispiv-92	13	15	and	and	CCONJ
ispiv-92	13	16	a	a	DET
ispiv-92	13	17	high	high	ADJ
ispiv-92	13	18	signal	signal	NOUN
ispiv-92	13	19	-	-	PUNCT
ispiv-92	13	20	to	to	ADP
ispiv-92	13	21	-	-	PUNCT
ispiv-92	13	22	noise	noise	NOUN
ispiv-92	13	23	ratio	ratio	NOUN
ispiv-92	13	24	while	while	SCONJ
ispiv-92	13	25	for	for	ADP
ispiv-92	13	26	higher	high	ADJ
ispiv-92	13	27	frequencies	frequency	NOUN
ispiv-92	13	28	we	we	PRON
ispiv-92	13	29	expect	expect	VERB
ispiv-92	13	30	a	a	DET
ispiv-92	13	31	low	low	ADJ
ispiv-92	13	32	signal	signal	NOUN
ispiv-92	13	33	-	-	PUNCT
ispiv-92	13	34	to	to	ADP
ispiv-92	13	35	-	-	PUNCT
ispiv-92	13	36	noise	noise	NOUN
ispiv-92	13	37	ratio	ratio	NOUN
ispiv-92	13	38	due	due	ADP
ispiv-92	13	39	to	to	ADP
ispiv-92	13	40	mostly	mostly	ADV
ispiv-92	13	41	white	white	ADJ
ispiv-92	13	42	measurement	measurement	NOUN
ispiv-92	13	43	noise	noise	NOUN
ispiv-92	13	44	.	.	PUNCT
ispiv-92	14	1	further	far	ADV
ispiv-92	14	2	,	,	PUNCT
ispiv-92	14	3	we	we	PRON
ispiv-92	14	4	expect	expect	VERB
ispiv-92	14	5	the	the	DET
ispiv-92	14	6	measurement	measurement	NOUN
ispiv-92	14	7	noise	noise	NOUN
ispiv-92	14	8	to	to	PART
ispiv-92	14	9	be	be	AUX
ispiv-92	14	10	additive	additive	ADJ
ispiv-92	14	11	and	and	CCONJ
ispiv-92	14	12	statistically	statistically	ADV
ispiv-92	14	13	uncorrelated	uncorrelated	ADJ
ispiv-92	14	14	to	to	ADP
ispiv-92	14	15	the	the	DET
ispiv-92	14	16	true	true	ADJ
ispiv-92	14	17	positional	positional	ADJ
ispiv-92	14	18	signals	signal	NOUN
ispiv-92	14	19	.	.	PUNCT
ispiv-92	15	1	in	in	ADP
ispiv-92	15	2	such	such	DET
ispiv-92	15	3	a	a	DET
ispiv-92	15	4	case	case	NOUN
ispiv-92	15	5	the	the	DET
ispiv-92	15	6	optimal	optimal	ADJ
ispiv-92	15	7	filter	filter	NOUN
ispiv-92	15	8	(	(	PUNCT
ispiv-92	15	9	optimal	optimal	ADJ
ispiv-92	15	10	with	with	ADP
ispiv-92	15	11	respect	respect	NOUN
ispiv-92	15	12	to	to	ADP
ispiv-92	15	13	minimizing	minimize	VERB
ispiv-92	15	14	the	the	DET
ispiv-92	15	15	sum	sum	NOUN
ispiv-92	15	16	of	of	ADP
ispiv-92	15	17	squared	square	VERB
ispiv-92	15	18	errors	error	NOUN
ispiv-92	15	19	)	)	PUNCT
ispiv-92	15	20	would	would	AUX
ispiv-92	15	21	reduce	reduce	VERB
ispiv-92	15	22	to	to	ADP
ispiv-92	15	23	a	a	DET
ispiv-92	15	24	simplified	simplified	ADJ
ispiv-92	15	25	wiener	wiener	NOUN
ispiv-92	15	26	filter	filter	NOUN
ispiv-92	15	27	that	that	PRON
ispiv-92	15	28	ignores	ignore	VERB
ispiv-92	15	29	cross	cross	NOUN
ispiv-92	15	30	correlations	correlation	NOUN
ispiv-92	15	31	between	between	ADP
ispiv-92	15	32	signal	signal	NOUN
ispiv-92	15	33	and	and	CCONJ
ispiv-92	15	34	noise	noise	NOUN
ispiv-92	15	35	.	.	PUNCT
ispiv-92	16	1	such	such	DET
ispiv-92	16	2	a	a	DET
ispiv-92	16	3	filter	filter	NOUN
ispiv-92	16	4	’s	’s	PART
ispiv-92	16	5	response	response	NOUN
ispiv-92	16	6	can	can	AUX
ispiv-92	16	7	be	be	AUX
ispiv-92	16	8	expressed	express	VERB
ispiv-92	16	9	as	as	SCONJ
ispiv-92	16	10	follows	follow	VERB
ispiv-92	16	11	:	:	PUNCT
ispiv-92	16	12	h	h	NUM
ispiv-92	16	13	(	(	PUNCT
ispiv-92	16	14	f	f	PROPN
ispiv-92	16	15	)	)	PUNCT
ispiv-92	17	1	=	=	SYM
ispiv-92	17	2	snr	snr	PROPN
ispiv-92	17	3	(	(	PUNCT
ispiv-92	17	4	f	f	PROPN
ispiv-92	17	5	)	)	PUNCT
ispiv-92	17	6	1+snr	1+snr	PROPN
ispiv-92	17	7	(	(	PUNCT
ispiv-92	17	8	f	f	PROPN
ispiv-92	17	9	)	)	PUNCT
ispiv-92	17	10	(	(	PUNCT
ispiv-92	17	11	1	1	X
ispiv-92	17	12	)	)	PUNCT
ispiv-92	17	13	in	in	ADP
ispiv-92	17	14	equation	equation	NOUN
ispiv-92	17	15	1	1	NUM
ispiv-92	17	16	snr	snr	PROPN
ispiv-92	17	17	(	(	PUNCT
ispiv-92	17	18	f	f	PROPN
ispiv-92	17	19	)	)	PUNCT
ispiv-92	17	20	refers	refer	VERB
ispiv-92	17	21	to	to	ADP
ispiv-92	17	22	the	the	DET
ispiv-92	17	23	local	local	ADJ
ispiv-92	17	24	signal	signal	NOUN
ispiv-92	17	25	power	power	NOUN
ispiv-92	17	26	to	to	PART
ispiv-92	17	27	noise	noise	VERB
ispiv-92	17	28	power	power	NOUN
ispiv-92	17	29	ratio	ratio	NOUN
ispiv-92	17	30	close	close	ADJ
ispiv-92	17	31	to	to	ADP
ispiv-92	17	32	the	the	DET
ispiv-92	17	33	frequency	frequency	NOUN
ispiv-92	17	34	f	f	X
ispiv-92	17	35	.	.	PUNCT
ispiv-92	18	1	for	for	ADP
ispiv-92	18	2	a	a	DET
ispiv-92	18	3	high	high	ADJ
ispiv-92	18	4	signal	signal	NOUN
ispiv-92	18	5	-	-	PUNCT
ispiv-92	18	6	to	to	ADP
ispiv-92	18	7	-	-	PUNCT
ispiv-92	18	8	noise	noise	NOUN
ispiv-92	18	9	ratio	ratio	NOUN
ispiv-92	18	10	the	the	DET
ispiv-92	18	11	filter	filter	NOUN
ispiv-92	18	12	gain	gain	NOUN
ispiv-92	18	13	will	will	AUX
ispiv-92	18	14	approach	approach	VERB
ispiv-92	18	15	1	1	NUM
ispiv-92	18	16	while	while	SCONJ
ispiv-92	18	17	for	for	ADP
ispiv-92	18	18	a	a	DET
ispiv-92	18	19	low	low	ADJ
ispiv-92	18	20	signal	signal	NOUN
ispiv-92	18	21	-	-	PUNCT
ispiv-92	18	22	to	to	ADP
ispiv-92	18	23	-	-	PUNCT
ispiv-92	18	24	noise	noise	NOUN
ispiv-92	18	25	ratio	ratio	NOUN
ispiv-92	18	26	the	the	DET
ispiv-92	18	27	gain	gain	NOUN
ispiv-92	18	28	will	will	AUX
ispiv-92	18	29	approach	approach	VERB
ispiv-92	18	30	zero	zero	NUM
ispiv-92	18	31	to	to	PART
ispiv-92	18	32	suppress	suppress	VERB
ispiv-92	18	33	the	the	DET
ispiv-92	18	34	noise	noise	NOUN
ispiv-92	18	35	.	.	PUNCT
ispiv-92	19	1	two	two	NUM
ispiv-92	19	2	challenges	challenge	NOUN
ispiv-92	19	3	arise	arise	VERB
ispiv-92	19	4	in	in	ADP
ispiv-92	19	5	the	the	DET
ispiv-92	19	6	context	context	NOUN
ispiv-92	19	7	of	of	ADP
ispiv-92	19	8	lagrangian	lagrangian	ADJ
ispiv-92	19	9	particle	particle	NOUN
ispiv-92	19	10	tracking	tracking	NOUN
ispiv-92	19	11	(	(	PUNCT
ispiv-92	19	12	ltp	ltp	PROPN
ispiv-92	19	13	)	)	PUNCT
ispiv-92	19	14	.	.	PUNCT
ispiv-92	20	1	the	the	DET
ispiv-92	20	2	particle	particle	NOUN
ispiv-92	20	3	trajectories	trajectory	NOUN
ispiv-92	20	4	may	may	AUX
ispiv-92	20	5	span	span	VERB
ispiv-92	20	6	only	only	ADV
ispiv-92	20	7	a	a	DET
ispiv-92	20	8	small	small	ADJ
ispiv-92	20	9	number	number	NOUN
ispiv-92	20	10	of	of	ADP
ispiv-92	20	11	time	time	NOUN
ispiv-92	20	12	steps	step	NOUN
ispiv-92	20	13	(	(	PUNCT
ispiv-92	20	14	order	order	NOUN
ispiv-92	20	15	of	of	ADP
ispiv-92	20	16	30	30	NUM
ispiv-92	20	17	)	)	PUNCT
ispiv-92	20	18	.	.	PUNCT
ispiv-92	21	1	in	in	ADP
ispiv-92	21	2	order	order	NOUN
ispiv-92	21	3	to	to	PART
ispiv-92	21	4	estimate	estimate	VERB
ispiv-92	21	5	the	the	DET
ispiv-92	21	6	ideal	ideal	ADJ
ispiv-92	21	7	filter	filter	NOUN
ispiv-92	21	8	transfer	transfer	NOUN
ispiv-92	21	9	function	function	NOUN
ispiv-92	21	10	,	,	PUNCT
ispiv-92	21	11	an	an	DET
ispiv-92	21	12	accurate	accurate	ADJ
ispiv-92	21	13	estimate	estimate	NOUN
ispiv-92	21	14	of	of	ADP
ispiv-92	21	15	the	the	DET
ispiv-92	21	16	power	power	NOUN
ispiv-92	21	17	spectral	spectral	ADJ
ispiv-92	21	18	densities	density	NOUN
ispiv-92	21	19	of	of	ADP
ispiv-92	21	20	the	the	DET
ispiv-92	21	21	true	true	ADJ
ispiv-92	21	22	signal	signal	NOUN
ispiv-92	21	23	and	and	CCONJ
ispiv-92	21	24	the	the	DET
ispiv-92	21	25	additive	additive	ADJ
ispiv-92	21	26	noise	noise	NOUN
ispiv-92	21	27	is	be	AUX
ispiv-92	21	28	necessary	necessary	ADJ
ispiv-92	21	29	.	.	PUNCT
ispiv-92	22	1	but	but	CCONJ
ispiv-92	22	2	for	for	ADP
ispiv-92	22	3	such	such	ADJ
ispiv-92	22	4	short	short	ADJ
ispiv-92	22	5	signals	signal	NOUN
ispiv-92	22	6	,	,	PUNCT
ispiv-92	22	7	spectral	spectral	ADJ
ispiv-92	22	8	estimation	estimation	NOUN
ispiv-92	22	9	requires	require	VERB
ispiv-92	22	10	special	special	ADJ
ispiv-92	22	11	attention	attention	NOUN
ispiv-92	22	12	.	.	PUNCT
ispiv-92	23	1	the	the	DET
ispiv-92	23	2	possibly	possibly	ADV
ispiv-92	23	3	short	short	ADJ
ispiv-92	23	4	nature	nature	NOUN
ispiv-92	23	5	of	of	ADP
ispiv-92	23	6	particle	particle	NOUN
ispiv-92	23	7	trajectories	trajectory	NOUN
ispiv-92	23	8	also	also	ADV
ispiv-92	23	9	poses	pose	VERB
ispiv-92	23	10	a	a	DET
ispiv-92	23	11	problem	problem	NOUN
ispiv-92	23	12	during	during	ADP
ispiv-92	23	13	the	the	DET
ispiv-92	23	14	application	application	NOUN
ispiv-92	23	15	of	of	ADP
ispiv-92	23	16	a	a	DET
ispiv-92	23	17	filter	filter	NOUN
ispiv-92	23	18	especially	especially	ADV
ispiv-92	23	19	at	at	ADP
ispiv-92	23	20	the	the	DET
ispiv-92	23	21	borders	border	NOUN
ispiv-92	23	22	of	of	ADP
ispiv-92	23	23	the	the	DET
ispiv-92	23	24	signal	signal	NOUN
ispiv-92	23	25	(	(	PUNCT
ispiv-92	23	26	the	the	DET
ispiv-92	23	27	beginning	beginning	NOUN
ispiv-92	23	28	and	and	CCONJ
ispiv-92	23	29	ending	ending	NOUN
ispiv-92	23	30	of	of	ADP
ispiv-92	23	31	a	a	DET
ispiv-92	23	32	trajectory	trajectory	NOUN
ispiv-92	23	33	)	)	PUNCT
ispiv-92	23	34	because	because	SCONJ
ispiv-92	23	35	the	the	DET
ispiv-92	23	36	filter	filter	NOUN
ispiv-92	23	37	would	would	AUX
ispiv-92	23	38	require	require	VERB
ispiv-92	23	39	samples	sample	NOUN
ispiv-92	23	40	outside	outside	ADP
ispiv-92	23	41	of	of	ADP
ispiv-92	23	42	the	the	DET
ispiv-92	23	43	recorded	record	VERB
ispiv-92	23	44	domain	domain	NOUN
ispiv-92	23	45	.	.	PUNCT
ispiv-92	24	1	the	the	DET
ispiv-92	24	2	remainder	remainder	NOUN
ispiv-92	24	3	of	of	ADP
ispiv-92	24	4	this	this	DET
ispiv-92	24	5	paper	paper	NOUN
ispiv-92	24	6	is	be	AUX
ispiv-92	24	7	structured	structure	VERB
ispiv-92	24	8	as	as	SCONJ
ispiv-92	24	9	follows	follow	VERB
ispiv-92	24	10	:	:	PUNCT
ispiv-92	24	11	section	section	NOUN
ispiv-92	24	12	2	2	NUM
ispiv-92	24	13	will	will	AUX
ispiv-92	24	14	cover	cover	VERB
ispiv-92	24	15	the	the	DET
ispiv-92	24	16	problem	problem	NOUN
ispiv-92	24	17	of	of	ADP
ispiv-92	24	18	spectral	spectral	ADJ
ispiv-92	24	19	analysis	analysis	NOUN
ispiv-92	24	20	for	for	ADP
ispiv-92	24	21	this	this	DET
ispiv-92	24	22	kind	kind	NOUN
ispiv-92	24	23	of	of	ADP
ispiv-92	24	24	filtering	filtering	NOUN
ispiv-92	24	25	problem	problem	NOUN
ispiv-92	24	26	.	.	PUNCT
ispiv-92	25	1	section	section	NOUN
ispiv-92	25	2	3	3	NUM
ispiv-92	25	3	will	will	AUX
ispiv-92	25	4	show	show	VERB
ispiv-92	25	5	the	the	DET
ispiv-92	25	6	results	result	NOUN
ispiv-92	25	7	of	of	ADP
ispiv-92	25	8	our	our	PRON
ispiv-92	25	9	spectral	spectral	ADJ
ispiv-92	25	10	estimation	estimation	NOUN
ispiv-92	25	11	method	method	NOUN
ispiv-92	25	12	when	when	SCONJ
ispiv-92	25	13	applied	apply	VERB
ispiv-92	25	14	to	to	ADP
ispiv-92	25	15	a	a	DET
ispiv-92	25	16	known	know	VERB
ispiv-92	25	17	data	datum	NOUN
ispiv-92	25	18	set	set	VERB
ispiv-92	25	19	from	from	ADP
ispiv-92	25	20	the	the	DET
ispiv-92	25	21	1st	1st	ADJ
ispiv-92	25	22	lpt	lpt	PROPN
ispiv-92	25	23	and	and	CCONJ
ispiv-92	25	24	da	da	PROPN
ispiv-92	25	25	challenge	challenge	NOUN
ispiv-92	25	26	for	for	ADP
ispiv-92	25	27	testing	test	VERB
ispiv-92	25	28	whether	whether	SCONJ
ispiv-92	25	29	the	the	DET
ispiv-92	25	30	method	method	NOUN
ispiv-92	25	31	results	result	VERB
ispiv-92	25	32	in	in	ADP
ispiv-92	25	33	a	a	DET
ispiv-92	25	34	reasonable	reasonable	ADJ
ispiv-92	25	35	power	power	NOUN
ispiv-92	25	36	spectrum	spectrum	NOUN
ispiv-92	25	37	estimate	estimate	NOUN
ispiv-92	25	38	but	but	CCONJ
ispiv-92	25	39	also	also	ADV
ispiv-92	25	40	to	to	PART
ispiv-92	25	41	verify	verify	VERB
ispiv-92	25	42	that	that	SCONJ
ispiv-92	25	43	our	our	PRON
ispiv-92	25	44	assumptions	assumption	NOUN
ispiv-92	25	45	about	about	ADP
ispiv-92	25	46	what	what	PRON
ispiv-92	25	47	such	such	DET
ispiv-92	25	48	a	a	DET
ispiv-92	25	49	spectrum	spectrum	NOUN
ispiv-92	25	50	may	may	AUX
ispiv-92	25	51	look	look	VERB
ispiv-92	25	52	like	like	ADP
ispiv-92	25	53	are	be	AUX
ispiv-92	25	54	true	true	ADJ
ispiv-92	25	55	.	.	PUNCT
ispiv-92	26	1	section	section	NOUN
ispiv-92	26	2	4	4	NUM
ispiv-92	26	3	will	will	AUX
ispiv-92	26	4	describe	describe	VERB
ispiv-92	26	5	the	the	DET
ispiv-92	26	6	trackfit	trackfit	ADJ
ispiv-92	26	7	filtering	filtering	NOUN
ispiv-92	26	8	method	method	NOUN
ispiv-92	26	9	(	(	PUNCT
ispiv-92	26	10	see	see	VERB
ispiv-92	26	11	also	also	ADV
ispiv-92	26	12	(	(	PUNCT
ispiv-92	26	13	gesemann	gesemann	PROPN
ispiv-92	26	14	et	et	PROPN
ispiv-92	26	15	al	al	PROPN
ispiv-92	26	16	.	.	PUNCT
ispiv-92	27	1	(	(	PUNCT
ispiv-92	27	2	2016	2016	NUM
ispiv-92	27	3	)	)	PUNCT
ispiv-92	27	4	)	)	PUNCT
ispiv-92	27	5	with	with	ADP
ispiv-92	27	6	its	its	PRON
ispiv-92	27	7	properties	property	NOUN
ispiv-92	27	8	.	.	PUNCT
ispiv-92	28	1	in	in	ADP
ispiv-92	28	2	section	section	NOUN
ispiv-92	28	3	5	5	NUM
ispiv-92	28	4	the	the	DET
ispiv-92	28	5	trackfit	trackfit	ADJ
ispiv-92	28	6	and	and	CCONJ
ispiv-92	28	7	savitzky	savitzky	ADJ
ispiv-92	28	8	–	–	PUNCT
ispiv-92	28	9	golay	golay	NOUN
ispiv-92	28	10	(	(	PUNCT
ispiv-92	28	11	savitzky	savitzky	NOUN
ispiv-92	28	12	and	and	CCONJ
ispiv-92	28	13	golay	golay	NOUN
ispiv-92	28	14	(	(	PUNCT
ispiv-92	28	15	1964	1964	NUM
ispiv-92	28	16	)	)	PUNCT
ispiv-92	28	17	)	)	PUNCT
ispiv-92	28	18	filter	filter	NOUN
ispiv-92	28	19	methods	method	NOUN
ispiv-92	28	20	are	be	AUX
ispiv-92	28	21	analyzed	analyze	VERB
ispiv-92	28	22	and	and	CCONJ
ispiv-92	28	23	compared	compare	VERB
ispiv-92	28	24	.	.	PUNCT
ispiv-92	29	1	section	section	NOUN
ispiv-92	29	2	7	7	NUM
ispiv-92	29	3	closes	close	VERB
ispiv-92	29	4	with	with	ADP
ispiv-92	29	5	a	a	DET
ispiv-92	29	6	summary	summary	NOUN
ispiv-92	29	7	and	and	CCONJ
ispiv-92	29	8	conclusion	conclusion	NOUN
ispiv-92	29	9	.	.	PUNCT
ispiv-92	30	1	2	2	NUM
ispiv-92	30	2	spectral	spectral	ADJ
ispiv-92	30	3	estimation	estimation	NOUN
ispiv-92	30	4	for	for	ADP
ispiv-92	30	5	our	our	PRON
ispiv-92	30	6	case	case	NOUN
ispiv-92	30	7	with	with	ADP
ispiv-92	30	8	potentially	potentially	ADV
ispiv-92	30	9	short	short	ADJ
ispiv-92	30	10	tracks	track	NOUN
ispiv-92	30	11	which	which	PRON
ispiv-92	30	12	have	have	VERB
ispiv-92	30	13	strong	strong	ADJ
ispiv-92	30	14	low	low	ADJ
ispiv-92	30	15	-	-	PUNCT
ispiv-92	30	16	frequency	frequency	NOUN
ispiv-92	30	17	components	component	NOUN
ispiv-92	30	18	we	we	PRON
ispiv-92	30	19	have	have	AUX
ispiv-92	30	20	developed	develop	VERB
ispiv-92	30	21	an	an	DET
ispiv-92	30	22	appropriate	appropriate	ADJ
ispiv-92	30	23	spectral	spectral	ADJ
ispiv-92	30	24	estimation	estimation	NOUN
ispiv-92	30	25	method	method	NOUN
ispiv-92	30	26	.	.	PUNCT
ispiv-92	31	1	the	the	DET
ispiv-92	31	2	method	method	NOUN
ispiv-92	31	3	can	can	AUX
ispiv-92	31	4	be	be	AUX
ispiv-92	31	5	summarized	summarize	VERB
ispiv-92	31	6	with	with	ADP
ispiv-92	31	7	the	the	DET
ispiv-92	31	8	following	follow	VERB
ispiv-92	31	9	steps	step	NOUN
ispiv-92	31	10	:	:	PUNCT
ispiv-92	31	11	1	1	X
ispiv-92	31	12	.	.	X
ispiv-92	31	13	prefilter	prefilter	NOUN
ispiv-92	31	14	(	(	PUNCT
ispiv-92	31	15	fir	fir	PROPN
ispiv-92	31	16	)	)	PUNCT
ispiv-92	31	17	the	the	DET
ispiv-92	31	18	position	position	NOUN
ispiv-92	31	19	-	-	PUNCT
ispiv-92	31	20	over	over	ADP
ispiv-92	31	21	-	-	PUNCT
ispiv-92	31	22	time	time	NOUN
ispiv-92	31	23	data	datum	NOUN
ispiv-92	31	24	2	2	NUM
ispiv-92	31	25	.	.	PUNCT
ispiv-92	31	26	compute	compute	NOUN
ispiv-92	31	27	autocorrelation	autocorrelation	NOUN
ispiv-92	31	28	of	of	ADP
ispiv-92	31	29	the	the	DET
ispiv-92	31	30	result	result	NOUN
ispiv-92	31	31	3	3	X
ispiv-92	31	32	.	.	PUNCT
ispiv-92	31	33	apply	apply	VERB
ispiv-92	31	34	levinson	levinson	PROPN
ispiv-92	31	35	-	-	PUNCT
ispiv-92	31	36	durbin	durbin	ADJ
ispiv-92	31	37	recursion	recursion	NOUN
ispiv-92	31	38	for	for	ADP
ispiv-92	31	39	auto	auto	NOUN
ispiv-92	31	40	-	-	PUNCT
ispiv-92	31	41	regressive	regressive	ADJ
ispiv-92	31	42	model	model	NOUN
ispiv-92	31	43	on	on	ADP
ispiv-92	31	44	autocorrelation	autocorrelation	NOUN
ispiv-92	31	45	data	datum	NOUN
ispiv-92	31	46	4	4	NUM
ispiv-92	31	47	.	.	PUNCT
ispiv-92	32	1	compensate	compensate	NOUN
ispiv-92	32	2	for	for	ADP
ispiv-92	32	3	prefiltering	prefiltere	VERB
ispiv-92	32	4	in	in	ADP
ispiv-92	32	5	auto	auto	NOUN
ispiv-92	32	6	-	-	PUNCT
ispiv-92	32	7	regressive	regressive	ADJ
ispiv-92	32	8	model	model	NOUN
ispiv-92	32	9	2.1	2.1	NUM
ispiv-92	32	10	prefilter	prefilter	NOUN
ispiv-92	32	11	a	a	DET
ispiv-92	32	12	prefilter	prefilter	NOUN
ispiv-92	32	13	can	can	AUX
ispiv-92	32	14	be	be	AUX
ispiv-92	32	15	used	use	VERB
ispiv-92	32	16	for	for	ADP
ispiv-92	32	17	spectral	spectral	ADJ
ispiv-92	32	18	analysis	analysis	NOUN
ispiv-92	32	19	as	as	ADP
ispiv-92	32	20	a	a	DET
ispiv-92	32	21	first	first	ADJ
ispiv-92	32	22	stage	stage	NOUN
ispiv-92	32	23	to	to	PART
ispiv-92	32	24	flatten	flatten	VERB
ispiv-92	32	25	the	the	DET
ispiv-92	32	26	signal	signal	NOUN
ispiv-92	32	27	spectrum	spectrum	NOUN
ispiv-92	32	28	.	.	PUNCT
ispiv-92	33	1	the	the	DET
ispiv-92	33	2	spectrum	spectrum	NOUN
ispiv-92	33	3	of	of	ADP
ispiv-92	33	4	the	the	DET
ispiv-92	33	5	resulting	result	VERB
ispiv-92	33	6	intermediate	intermediate	ADJ
ispiv-92	33	7	signal	signal	NOUN
ispiv-92	33	8	would	would	AUX
ispiv-92	33	9	be	be	AUX
ispiv-92	33	10	estimated	estimate	VERB
ispiv-92	33	11	instead	instead	ADV
ispiv-92	33	12	to	to	PART
ispiv-92	33	13	derive	derive	VERB
ispiv-92	33	14	the	the	DET
ispiv-92	33	15	original	original	ADJ
ispiv-92	33	16	spectrum	spectrum	NOUN
ispiv-92	33	17	by	by	ADP
ispiv-92	33	18	compensating	compensate	VERB
ispiv-92	33	19	for	for	ADP
ispiv-92	33	20	the	the	DET
ispiv-92	33	21	prefilter	prefilter	NOUN
ispiv-92	33	22	’s	’s	PART
ispiv-92	33	23	response	response	NOUN
ispiv-92	33	24	.	.	PUNCT
ispiv-92	34	1	this	this	DET
ispiv-92	34	2	approach	approach	NOUN
ispiv-92	34	3	can	can	AUX
ispiv-92	34	4	be	be	AUX
ispiv-92	34	5	preferable	preferable	ADJ
ispiv-92	34	6	to	to	PART
ispiv-92	34	7	directly	directly	ADV
ispiv-92	34	8	estimating	estimate	VERB
ispiv-92	34	9	the	the	DET
ispiv-92	34	10	original	original	ADJ
ispiv-92	34	11	signal	signal	NOUN
ispiv-92	34	12	’s	’s	PART
ispiv-92	34	13	spectrum	spectrum	NOUN
ispiv-92	34	14	.	.	PUNCT
ispiv-92	35	1	in	in	ADP
ispiv-92	35	2	particular	particular	ADJ
ispiv-92	35	3	,	,	PUNCT
ispiv-92	35	4	an	an	DET
ispiv-92	35	5	fft	fft	NOUN
ispiv-92	35	6	-	-	PUNCT
ispiv-92	35	7	based	base	VERB
ispiv-92	35	8	estimation	estimation	NOUN
ispiv-92	35	9	tends	tend	VERB
ispiv-92	35	10	to	to	PART
ispiv-92	35	11	suffer	suffer	VERB
ispiv-92	35	12	from	from	ADP
ispiv-92	35	13	spectral	spectral	ADJ
ispiv-92	35	14	leakage	leakage	NOUN
ispiv-92	35	15	due	due	ADP
ispiv-92	35	16	to	to	ADP
ispiv-92	35	17	the	the	DET
ispiv-92	35	18	use	use	NOUN
ispiv-92	35	19	of	of	ADP
ispiv-92	35	20	finite	finite	ADJ
ispiv-92	35	21	windows	window	NOUN
ispiv-92	35	22	.	.	PUNCT
ispiv-92	36	1	spectral	spectral	ADJ
ispiv-92	36	2	leakage	leakage	NOUN
ispiv-92	36	3	manifests	manifest	NOUN
ispiv-92	36	4	in	in	ADP
ispiv-92	36	5	the	the	DET
ispiv-92	36	6	form	form	NOUN
ispiv-92	36	7	of	of	ADP
ispiv-92	36	8	a	a	DET
ispiv-92	36	9	broader	broad	ADJ
ispiv-92	36	10	main	main	ADJ
ispiv-92	36	11	lobe	lobe	NOUN
ispiv-92	36	12	and	and	CCONJ
ispiv-92	36	13	the	the	DET
ispiv-92	36	14	presence	presence	NOUN
ispiv-92	36	15	of	of	ADP
ispiv-92	36	16	side	side	NOUN
ispiv-92	36	17	lobes	lobe	NOUN
ispiv-92	36	18	for	for	ADP
ispiv-92	36	19	a	a	DET
ispiv-92	36	20	single	single	ADJ
ispiv-92	36	21	frequency	frequency	NOUN
ispiv-92	36	22	that	that	PRON
ispiv-92	36	23	is	be	AUX
ispiv-92	36	24	present	present	ADJ
ispiv-92	36	25	in	in	ADP
ispiv-92	36	26	the	the	DET
ispiv-92	36	27	signal	signal	NOUN
ispiv-92	36	28	.	.	PUNCT
ispiv-92	37	1	these	these	DET
ispiv-92	37	2	artefacts	artefact	NOUN
ispiv-92	37	3	will	will	AUX
ispiv-92	37	4	be	be	AUX
ispiv-92	37	5	less	less	ADV
ispiv-92	37	6	noticeable	noticeable	ADJ
ispiv-92	37	7	if	if	SCONJ
ispiv-92	37	8	the	the	DET
ispiv-92	37	9	signal	signal	NOUN
ispiv-92	37	10	already	already	ADV
ispiv-92	37	11	has	have	VERB
ispiv-92	37	12	a	a	DET
ispiv-92	37	13	flat	flat	ADJ
ispiv-92	37	14	shape	shape	NOUN
ispiv-92	37	15	.	.	PUNCT
ispiv-92	38	1	for	for	ADP
ispiv-92	38	2	spectral	spectral	ADJ
ispiv-92	38	3	estimation	estimation	NOUN
ispiv-92	38	4	based	base	VERB
ispiv-92	38	5	on	on	ADP
ispiv-92	38	6	the	the	DET
ispiv-92	38	7	auto	auto	NOUN
ispiv-92	38	8	-	-	PUNCT
ispiv-92	38	9	regressive	regressive	ADJ
ispiv-92	38	10	model	model	NOUN
ispiv-92	38	11	,	,	PUNCT
ispiv-92	38	12	prefiltering	prefiltering	NOUN
ispiv-92	38	13	also	also	ADV
ispiv-92	38	14	has	have	VERB
ispiv-92	38	15	benefits	benefit	NOUN
ispiv-92	38	16	.	.	PUNCT
ispiv-92	39	1	the	the	DET
ispiv-92	39	2	effect	effect	NOUN
ispiv-92	39	3	of	of	ADP
ispiv-92	39	4	different	different	ADJ
ispiv-92	39	5	prefilters	prefilter	NOUN
ispiv-92	39	6	is	be	AUX
ispiv-92	39	7	shown	show	VERB
ispiv-92	39	8	in	in	ADP
ispiv-92	39	9	section	section	NOUN
ispiv-92	39	10	2.2	2.2	NUM
ispiv-92	39	11	.	.	PUNCT
ispiv-92	40	1	apart	apart	ADV
ispiv-92	40	2	from	from	ADP
ispiv-92	40	3	flattening	flatten	VERB
ispiv-92	40	4	the	the	DET
ispiv-92	40	5	spectrum	spectrum	NOUN
ispiv-92	40	6	,	,	PUNCT
ispiv-92	40	7	such	such	DET
ispiv-92	40	8	a	a	DET
ispiv-92	40	9	prefilter	prefilter	NOUN
ispiv-92	40	10	should	should	AUX
ispiv-92	40	11	also	also	ADV
ispiv-92	40	12	have	have	VERB
ispiv-92	40	13	a	a	DET
ispiv-92	40	14	short	short	ADJ
ispiv-92	40	15	impulse	impulse	ADJ
ispiv-92	40	16	response	response	NOUN
ispiv-92	40	17	,	,	PUNCT
ispiv-92	40	18	e.g.	e.g.	ADV
ispiv-92	40	19	two	two	NUM
ispiv-92	40	20	or	or	CCONJ
ispiv-92	40	21	three	three	NUM
ispiv-92	40	22	samples	sample	NOUN
ispiv-92	40	23	.	.	PUNCT
ispiv-92	41	1	this	this	PRON
ispiv-92	41	2	becomes	become	VERB
ispiv-92	41	3	obvious	obvious	ADJ
ispiv-92	41	4	when	when	SCONJ
ispiv-92	41	5	the	the	DET
ispiv-92	41	6	filter	filter	NOUN
ispiv-92	41	7	has	have	VERB
ispiv-92	41	8	to	to	PART
ispiv-92	41	9	be	be	AUX
ispiv-92	41	10	applied	apply	VERB
ispiv-92	41	11	to	to	ADP
ispiv-92	41	12	potentially	potentially	ADV
ispiv-92	41	13	short	short	ADJ
ispiv-92	41	14	signals	signal	NOUN
ispiv-92	41	15	.	.	PUNCT
ispiv-92	42	1	suppose	suppose	VERB
ispiv-92	42	2	a	a	DET
ispiv-92	42	3	short	short	ADJ
ispiv-92	42	4	signal	signal	NOUN
ispiv-92	42	5	with	with	ADP
ispiv-92	42	6	25	25	NUM
ispiv-92	42	7	particle	particle	NOUN
ispiv-92	42	8	locations	location	NOUN
ispiv-92	42	9	is	be	AUX
ispiv-92	42	10	available	available	ADJ
ispiv-92	42	11	.	.	PUNCT
ispiv-92	43	1	after	after	ADP
ispiv-92	43	2	applying	apply	VERB
ispiv-92	43	3	a	a	DET
ispiv-92	43	4	prefilter	prefilter	NOUN
ispiv-92	43	5	with	with	ADP
ispiv-92	43	6	an	an	DET
ispiv-92	43	7	impulse	impulse	ADJ
ispiv-92	43	8	response	response	NOUN
ispiv-92	43	9	of	of	ADP
ispiv-92	43	10	three	three	NUM
ispiv-92	43	11	samples	sample	NOUN
ispiv-92	43	12	only	only	ADV
ispiv-92	43	13	23	23	NUM
ispiv-92	43	14	samples	sample	NOUN
ispiv-92	43	15	of	of	ADP
ispiv-92	43	16	the	the	DET
ispiv-92	43	17	result	result	NOUN
ispiv-92	43	18	can	can	AUX
ispiv-92	43	19	be	be	AUX
ispiv-92	43	20	used	use	VERB
ispiv-92	43	21	for	for	ADP
ispiv-92	43	22	estimating	estimate	VERB
ispiv-92	43	23	autocorrelation	autocorrelation	NOUN
ispiv-92	43	24	coefficients	coefficient	NOUN
ispiv-92	43	25	.	.	PUNCT
ispiv-92	44	1	the	the	PRON
ispiv-92	44	2	longer	long	ADV
ispiv-92	44	3	the	the	DET
ispiv-92	44	4	filter	filter	NOUN
ispiv-92	44	5	’s	’s	PART
ispiv-92	44	6	impulse	impulse	ADJ
ispiv-92	44	7	response	response	NOUN
ispiv-92	44	8	,	,	PUNCT
ispiv-92	44	9	the	the	DET
ispiv-92	44	10	shorter	short	ADJ
ispiv-92	44	11	the	the	DET
ispiv-92	44	12	intermediate	intermediate	ADJ
ispiv-92	44	13	signals	signal	NOUN
ispiv-92	44	14	will	will	AUX
ispiv-92	44	15	get	get	VERB
ispiv-92	44	16	.	.	PUNCT
ispiv-92	45	1	the	the	DET
ispiv-92	45	2	prefilters	prefilter	NOUN
ispiv-92	45	3	we	we	PRON
ispiv-92	45	4	chose	choose	VERB
ispiv-92	45	5	are	be	AUX
ispiv-92	45	6	first	first	ADJ
ispiv-92	45	7	and	and	CCONJ
ispiv-92	45	8	second	second	ADJ
ispiv-92	45	9	order	order	NOUN
ispiv-92	45	10	digital	digital	ADJ
ispiv-92	45	11	fir	fir	NOUN
ispiv-92	45	12	filters	filter	NOUN
ispiv-92	45	13	with	with	ADP
ispiv-92	45	14	the	the	DET
ispiv-92	45	15	following	follow	VERB
ispiv-92	45	16	transfer	transfer	NOUN
ispiv-92	45	17	functions	function	NOUN
ispiv-92	45	18	hp1	hp1	PROPN
ispiv-92	45	19	and	and	CCONJ
ispiv-92	45	20	hp2	hp2	PROPN
ispiv-92	45	21	:	:	PUNCT
ispiv-92	45	22	hp1(z	hp1(z	PROPN
ispiv-92	45	23	)	)	PUNCT
ispiv-92	45	24	=	=	SYM
ispiv-92	45	25	1−	1−	NUM
ispiv-92	45	26	z−1	z−1	NUM
ispiv-92	45	27	hp2(z	hp2(z	PROPN
ispiv-92	45	28	)	)	PUNCT
ispiv-92	45	29	=	=	SYM
ispiv-92	45	30	1−1.9z−1	1−1.9z−1	NUM
ispiv-92	45	31	+0.9z−2	+0.9z−2	SYM
ispiv-92	45	32	(	(	PUNCT
ispiv-92	45	33	2	2	X
ispiv-92	45	34	)	)	PUNCT
ispiv-92	45	35	these	these	DET
ispiv-92	45	36	filters	filter	NOUN
ispiv-92	45	37	attenuate	attenuate	VERB
ispiv-92	45	38	the	the	DET
ispiv-92	45	39	low	low	ADJ
ispiv-92	45	40	frequencies	frequency	NOUN
ispiv-92	45	41	and	and	CCONJ
ispiv-92	45	42	amplify	amplify	VERB
ispiv-92	45	43	the	the	DET
ispiv-92	45	44	higher	high	ADJ
ispiv-92	45	45	frequencies	frequency	NOUN
ispiv-92	45	46	.	.	PUNCT
ispiv-92	46	1	2.2	2.2	NUM
ispiv-92	46	2	spectral	spectral	ADJ
ispiv-92	46	3	estimation	estimation	NOUN
ispiv-92	46	4	via	via	ADP
ispiv-92	46	5	auto	auto	NOUN
ispiv-92	46	6	-	-	PUNCT
ispiv-92	46	7	regressive	regressive	ADJ
ispiv-92	46	8	model	model	NOUN
ispiv-92	46	9	the	the	DET
ispiv-92	46	10	auto	auto	NOUN
ispiv-92	46	11	-	-	PUNCT
ispiv-92	46	12	regressive	regressive	ADJ
ispiv-92	46	13	model	model	NOUN
ispiv-92	46	14	(	(	PUNCT
ispiv-92	46	15	ar	ar	NOUN
ispiv-92	46	16	)	)	PUNCT
ispiv-92	46	17	basically	basically	ADV
ispiv-92	46	18	describes	describe	VERB
ispiv-92	46	19	a	a	DET
ispiv-92	46	20	random	random	ADJ
ispiv-92	46	21	process	process	NOUN
ispiv-92	46	22	as	as	SCONJ
ispiv-92	46	23	filtered	filter	VERB
ispiv-92	46	24	white	white	ADJ
ispiv-92	46	25	noise	noise	NOUN
ispiv-92	46	26	using	use	VERB
ispiv-92	46	27	an	an	DET
ispiv-92	46	28	allpole	allpole	NOUN
ispiv-92	46	29	iir	iir	NOUN
ispiv-92	46	30	filter	filter	NOUN
ispiv-92	46	31	for	for	ADP
ispiv-92	46	32	coloring	color	VERB
ispiv-92	46	33	the	the	DET
ispiv-92	46	34	noise	noise	NOUN
ispiv-92	46	35	.	.	PUNCT
ispiv-92	47	1	with	with	ADP
ispiv-92	47	2	the	the	DET
ispiv-92	47	3	help	help	NOUN
ispiv-92	47	4	of	of	ADP
ispiv-92	47	5	the	the	DET
ispiv-92	47	6	levinson	levinson	PROPN
ispiv-92	47	7	-	-	PUNCT
ispiv-92	47	8	durbin	durbin	ADJ
ispiv-92	47	9	recursion	recursion	NOUN
ispiv-92	47	10	the	the	DET
ispiv-92	47	11	filter	filter	NOUN
ispiv-92	47	12	coefficients	coefficient	NOUN
ispiv-92	47	13	can	can	AUX
ispiv-92	47	14	be	be	AUX
ispiv-92	47	15	extracted	extract	VERB
ispiv-92	47	16	from	from	ADP
ispiv-92	47	17	autocorrelation	autocorrelation	NOUN
ispiv-92	47	18	coefficients	coefficient	NOUN
ispiv-92	47	19	.	.	PUNCT
ispiv-92	48	1	this	this	PRON
ispiv-92	48	2	allows	allow	VERB
ispiv-92	48	3	another	another	DET
ispiv-92	48	4	form	form	NOUN
ispiv-92	48	5	of	of	ADP
ispiv-92	48	6	spectral	spectral	ADJ
ispiv-92	48	7	estimation	estimation	NOUN
ispiv-92	48	8	in	in	ADP
ispiv-92	48	9	that	that	SCONJ
ispiv-92	48	10	the	the	DET
ispiv-92	48	11	filter	filter	NOUN
ispiv-92	48	12	represents	represent	VERB
ispiv-92	48	13	the	the	DET
ispiv-92	48	14	spectral	spectral	ADJ
ispiv-92	48	15	shape	shape	NOUN
ispiv-92	48	16	(	(	PUNCT
ispiv-92	48	17	with	with	ADP
ispiv-92	48	18	an	an	DET
ispiv-92	48	19	average	average	ADJ
ispiv-92	48	20	response	response	NOUN
ispiv-92	48	21	of	of	ADP
ispiv-92	48	22	0	0	NUM
ispiv-92	48	23	db	db	NOUN
ispiv-92	48	24	over	over	ADP
ispiv-92	48	25	a	a	DET
ispiv-92	48	26	linear	linear	ADJ
ispiv-92	48	27	frequency	frequency	NOUN
ispiv-92	48	28	axis	axis	NOUN
ispiv-92	48	29	)	)	PUNCT
ispiv-92	48	30	and	and	CCONJ
ispiv-92	48	31	the	the	DET
ispiv-92	48	32	noise	noise	NOUN
ispiv-92	48	33	power	power	NOUN
ispiv-92	48	34	represents	represent	VERB
ispiv-92	48	35	an	an	DET
ispiv-92	48	36	overall	overall	ADJ
ispiv-92	48	37	offset	offset	NOUN
ispiv-92	48	38	for	for	ADP
ispiv-92	48	39	the	the	DET
ispiv-92	48	40	power	power	NOUN
ispiv-92	48	41	spectral	spectral	ADJ
ispiv-92	48	42	density	density	PROPN
ispiv-92	48	43	.	.	PUNCT
ispiv-92	49	1	see	see	VERB
ispiv-92	49	2	listing	list	VERB
ispiv-92	49	3	1	1	NUM
ispiv-92	49	4	for	for	ADP
ispiv-92	49	5	a	a	DET
ispiv-92	49	6	gnu	gnu	NOUN
ispiv-92	49	7	octave	octave	NOUN
ispiv-92	49	8	script	script	NOUN
ispiv-92	49	9	that	that	PRON
ispiv-92	49	10	shows	show	VERB
ispiv-92	49	11	this	this	DET
ispiv-92	49	12	process	process	NOUN
ispiv-92	49	13	.	.	PUNCT
ispiv-92	50	1	%	%	INTJ
ispiv-92	50	2	let	let	VERB
ispiv-92	50	3	acf	acf	PROPN
ispiv-92	50	4	be	be	AUX
ispiv-92	50	5	a	a	DET
ispiv-92	50	6	vector	vector	NOUN
ispiv-92	50	7	with	with	ADP
ispiv-92	50	8	the	the	DET
ispiv-92	50	9	autocorrelations	autocorrelation	NOUN
ispiv-92	50	10	%	%	NOUN
ispiv-92	50	11	for	for	ADP
ispiv-92	50	12	lags	lag	NOUN
ispiv-92	50	13	zero	zero	NUM
ispiv-92	50	14	to	to	ADP
ispiv-92	50	15	p	p	NOUN
ispiv-92	50	16	(	(	PUNCT
ispiv-92	50	17	inclusive	inclusive	ADJ
ispiv-92	50	18	)	)	PUNCT
ispiv-92	50	19	%	%	NOUN
ispiv-92	50	20	auto	auto	NOUN
ispiv-92	50	21	-	-	PUNCT
ispiv-92	50	22	regressive	regressive	ADJ
ispiv-92	50	23	model	model	NOUN
ispiv-92	50	24	ar(p	ar(p	NUM
ispiv-92	50	25	)	)	PUNCT
ispiv-92	50	26	computed	compute	VERB
ispiv-92	50	27	from	from	ADP
ispiv-92	50	28	acf	acf	NOUN
ispiv-92	50	29	using	use	VERB
ispiv-92	50	30	%	%	NOUN
ispiv-92	50	31	levinson	levinson	PROPN
ispiv-92	50	32	-	-	PUNCT
ispiv-92	50	33	durbin	durbin	ADJ
ispiv-92	50	34	recursion	recursion	NOUN
ispiv-92	50	35	[	[	X
ispiv-92	50	36	a	a	X
ispiv-92	50	37	,	,	PUNCT
ispiv-92	50	38	v	v	NOUN
ispiv-92	50	39	]	]	X
ispiv-92	50	40	=	=	SYM
ispiv-92	50	41	levinson(acf	levinson(acf	PROPN
ispiv-92	50	42	)	)	PUNCT
ispiv-92	50	43	;	;	PUNCT
ispiv-92	51	1	%	%	NOUN
ispiv-92	51	2	a	a	DET
ispiv-92	51	3	=	=	NOUN
ispiv-92	51	4	order	order	NOUN
ispiv-92	51	5	p	p	NOUN
ispiv-92	51	6	all	all	DET
ispiv-92	51	7	-	-	PUNCT
ispiv-92	51	8	pole	pole	NOUN
ispiv-92	51	9	filter	filter	NOUN
ispiv-92	51	10	coefficients	coefficient	NOUN
ispiv-92	51	11	%	%	NOUN
ispiv-92	51	12	v	v	NOUN
ispiv-92	51	13	=	=	NOUN
ispiv-92	51	14	variance	variance	NOUN
ispiv-92	51	15	of	of	ADP
ispiv-92	51	16	white	white	ADJ
ispiv-92	51	17	noise	noise	NOUN
ispiv-92	51	18	%	%	NOUN
ispiv-92	51	19	power	power	NOUN
ispiv-92	51	20	spectral	spectral	ADJ
ispiv-92	51	21	density	density	NOUN
ispiv-92	51	22	estimate	estimate	NOUN
ispiv-92	51	23	by	by	ADP
ispiv-92	51	24	evaluating	evaluate	VERB
ispiv-92	51	25	the	the	DET
ispiv-92	51	26	%	%	NOUN
ispiv-92	51	27	filter	filter	NOUN
ispiv-92	51	28	's	's	PART
ispiv-92	51	29	transfer	transfer	NOUN
ispiv-92	51	30	function	function	NOUN
ispiv-92	51	31	and	and	CCONJ
ispiv-92	51	32	scaling	scale	VERB
ispiv-92	51	33	with	with	ADP
ispiv-92	51	34	variance	variance	NOUN
ispiv-92	52	1	[	[	X
ispiv-92	52	2	h	h	NOUN
ispiv-92	52	3	,	,	PUNCT
ispiv-92	52	4	f	f	X
ispiv-92	52	5	]	]	X
ispiv-92	52	6	=	=	SYM
ispiv-92	52	7	freqz(1,a	freqz(1,a	PROPN
ispiv-92	52	8	)	)	PUNCT
ispiv-92	52	9	;	;	PUNCT
ispiv-92	52	10	%	%	NOUN
ispiv-92	52	11	transfer	transfer	NOUN
ispiv-92	52	12	function	function	NOUN
ispiv-92	52	13	p	p	NOUN
ispiv-92	52	14	=	=	PUNCT
ispiv-92	52	15	abs(h).ˆ2	abs(h).ˆ2	PROPN
ispiv-92	52	16	*	*	PUNCT
ispiv-92	52	17	v	v	NOUN
ispiv-92	52	18	;	;	PUNCT
ispiv-92	52	19	%	%	NOUN
ispiv-92	52	20	power	power	NOUN
ispiv-92	52	21	spectral	spectral	ADJ
ispiv-92	52	22	density	density	NOUN
ispiv-92	52	23	estimate	estimate	NOUN
ispiv-92	52	24	loglog(f(2	loglog(f(2	NOUN
ispiv-92	52	25	:	:	PUNCT
ispiv-92	52	26	end	end	NOUN
ispiv-92	52	27	)	)	PUNCT
ispiv-92	52	28	,	,	PUNCT
ispiv-92	52	29	p(2	p(2	NOUN
ispiv-92	52	30	:	:	PUNCT
ispiv-92	52	31	end	end	NOUN
ispiv-92	52	32	)	)	PUNCT
ispiv-92	52	33	)	)	PUNCT
ispiv-92	52	34	;	;	PUNCT
ispiv-92	52	35	listing	list	VERB
ispiv-92	52	36	1	1	NUM
ispiv-92	52	37	:	:	PUNCT
ispiv-92	52	38	gnu	gnu	PROPN
ispiv-92	52	39	octave	octave	PROPN
ispiv-92	52	40	example	example	NOUN
ispiv-92	52	41	script	script	NOUN
ispiv-92	52	42	for	for	ADP
ispiv-92	52	43	estimating	estimate	VERB
ispiv-92	52	44	the	the	DET
ispiv-92	52	45	power	power	NOUN
ispiv-92	52	46	spectral	spectral	ADJ
ispiv-92	52	47	density	density	NOUN
ispiv-92	52	48	based	base	VERB
ispiv-92	52	49	on	on	ADP
ispiv-92	52	50	autocorrelation	autocorrelation	NOUN
ispiv-92	52	51	coefficients	coefficient	NOUN
ispiv-92	52	52	via	via	ADP
ispiv-92	52	53	an	an	DET
ispiv-92	52	54	auto	auto	NOUN
ispiv-92	52	55	-	-	PUNCT
ispiv-92	52	56	regressive	regressive	ADJ
ispiv-92	52	57	model	model	NOUN
ispiv-92	52	58	of	of	ADP
ispiv-92	52	59	order	order	NOUN
ispiv-92	52	60	p.	p.	NOUN
ispiv-92	52	61	2.3	2.3	NUM
ispiv-92	52	62	test	test	NOUN
ispiv-92	52	63	and	and	CCONJ
ispiv-92	52	64	comparison	comparison	NOUN
ispiv-92	52	65	of	of	ADP
ispiv-92	52	66	spectral	spectral	ADJ
ispiv-92	52	67	estimation	estimation	NOUN
ispiv-92	52	68	methods	method	NOUN
ispiv-92	52	69	to	to	PART
ispiv-92	52	70	test	test	VERB
ispiv-92	52	71	the	the	DET
ispiv-92	52	72	various	various	ADJ
ispiv-92	52	73	spectral	spectral	ADJ
ispiv-92	52	74	estimation	estimation	NOUN
ispiv-92	52	75	methods	method	NOUN
ispiv-92	52	76	a	a	DET
ispiv-92	52	77	ground	ground	NOUN
ispiv-92	52	78	truth	truth	NOUN
ispiv-92	52	79	spectrum	spectrum	NOUN
ispiv-92	52	80	has	have	AUX
ispiv-92	52	81	been	be	AUX
ispiv-92	52	82	chosen	choose	VERB
ispiv-92	52	83	that	that	PRON
ispiv-92	52	84	is	be	AUX
ispiv-92	52	85	believed	believe	VERB
ispiv-92	52	86	to	to	PART
ispiv-92	52	87	be	be	AUX
ispiv-92	52	88	representative	representative	ADJ
ispiv-92	52	89	of	of	ADP
ispiv-92	52	90	typical	typical	ADJ
ispiv-92	52	91	particle	particle	NOUN
ispiv-92	52	92	tracks	track	NOUN
ispiv-92	52	93	including	include	VERB
ispiv-92	52	94	measurement	measurement	NOUN
ispiv-92	52	95	noise	noise	NOUN
ispiv-92	52	96	,	,	PUNCT
ispiv-92	52	97	see	see	VERB
ispiv-92	52	98	figure	figure	NOUN
ispiv-92	52	99	1	1	NUM
ispiv-92	52	100	.	.	PUNCT
ispiv-92	53	1	the	the	DET
ispiv-92	53	2	lower	low	ADJ
ispiv-92	53	3	frequency	frequency	NOUN
ispiv-92	53	4	part	part	NOUN
ispiv-92	53	5	is	be	AUX
ispiv-92	53	6	dominated	dominate	VERB
ispiv-92	53	7	by	by	ADP
ispiv-92	53	8	true	true	ADJ
ispiv-92	53	9	particle	particle	NOUN
ispiv-92	53	10	locations	location	NOUN
ispiv-92	53	11	while	while	SCONJ
ispiv-92	53	12	the	the	DET
ispiv-92	53	13	higher	high	ADJ
ispiv-92	53	14	frequency	frequency	NOUN
ispiv-92	53	15	part	part	NOUN
ispiv-92	53	16	is	be	AUX
ispiv-92	53	17	dominated	dominate	VERB
ispiv-92	53	18	by	by	ADP
ispiv-92	53	19	flat	flat	ADJ
ispiv-92	53	20	white	white	ADJ
ispiv-92	53	21	measurement	measurement	NOUN
ispiv-92	53	22	noise	noise	NOUN
ispiv-92	53	23	.	.	PUNCT
ispiv-92	54	1	the	the	DET
ispiv-92	54	2	ground	ground	NOUN
ispiv-92	54	3	truth	truth	NOUN
ispiv-92	54	4	is	be	AUX
ispiv-92	54	5	the	the	DET
ispiv-92	54	6	sum	sum	NOUN
ispiv-92	54	7	of	of	ADP
ispiv-92	54	8	two	two	NUM
ispiv-92	54	9	power	power	NOUN
ispiv-92	54	10	spectra	spectra	NOUN
ispiv-92	54	11	:	:	PUNCT
ispiv-92	54	12	signal	signal	NOUN
ispiv-92	54	13	(	(	PUNCT
ispiv-92	54	14	psds	psds	NOUN
ispiv-92	54	15	)	)	PUNCT
ispiv-92	54	16	and	and	CCONJ
ispiv-92	54	17	noise	noise	NOUN
ispiv-92	54	18	(	(	PUNCT
ispiv-92	54	19	psdn	psdn	PROPN
ispiv-92	54	20	)	)	PUNCT
ispiv-92	54	21	.	.	PUNCT
ispiv-92	55	1	on	on	ADP
ispiv-92	55	2	a	a	DET
ispiv-92	55	3	normalized	normalize	VERB
ispiv-92	55	4	frequency	frequency	NOUN
ispiv-92	55	5	axis	axis	NOUN
ispiv-92	55	6	(	(	PUNCT
ispiv-92	55	7	ranging	range	VERB
ispiv-92	55	8	from	from	ADP
ispiv-92	55	9	zero	zero	NUM
ispiv-92	55	10	to	to	ADP
ispiv-92	55	11	one	one	NUM
ispiv-92	55	12	for	for	ADP
ispiv-92	55	13	the	the	DET
ispiv-92	55	14	nyquist	nyquist	NOUN
ispiv-92	55	15	frequency	frequency	NOUN
ispiv-92	55	16	)	)	PUNCT
ispiv-92	55	17	they	they	PRON
ispiv-92	55	18	are	be	AUX
ispiv-92	55	19	defined	define	VERB
ispiv-92	55	20	as	as	SCONJ
ispiv-92	55	21	follows	follow	VERB
ispiv-92	55	22	:	:	PUNCT
ispiv-92	56	1	psds	psds	NOUN
ispiv-92	56	2	(	(	PUNCT
ispiv-92	56	3	f	f	PROPN
ispiv-92	56	4	)	)	PUNCT
ispiv-92	56	5	=	=	SYM
ispiv-92	56	6	1	1	NUM
ispiv-92	56	7	(	(	PUNCT
ispiv-92	56	8	3.77	3.77	NUM
ispiv-92	56	9	f	f	NOUN
ispiv-92	56	10	)	)	PUNCT
ispiv-92	56	11	2	2	NUM
ispiv-92	56	12	+	+	NOUN
ispiv-92	56	13	(	(	PUNCT
ispiv-92	56	14	641.52	641.52	NUM
ispiv-92	56	15	f	f	PROPN
ispiv-92	56	16	2)2	2)2	NUM
ispiv-92	56	17	+	+	NOUN
ispiv-92	56	18	(	(	PUNCT
ispiv-92	56	19	17363.515	17363.515	PROPN
ispiv-92	56	20	f	f	X
ispiv-92	56	21	3)2	3)2	NUM
ispiv-92	56	22	(	(	PUNCT
ispiv-92	56	23	3	3	NUM
ispiv-92	56	24	)	)	PUNCT
ispiv-92	56	25	psdn	psdn	NOUN
ispiv-92	56	26	(	(	PUNCT
ispiv-92	56	27	f	f	NOUN
ispiv-92	56	28	)	)	PUNCT
ispiv-92	56	29	=	=	PUNCT
ispiv-92	56	30	0.00592	0.00592	NUM
ispiv-92	56	31	(	(	PUNCT
ispiv-92	56	32	4	4	NUM
ispiv-92	56	33	)	)	PUNCT
ispiv-92	56	34	based	base	VERB
ispiv-92	56	35	on	on	ADP
ispiv-92	56	36	the	the	DET
ispiv-92	56	37	chosen	choose	VERB
ispiv-92	56	38	ground	ground	NOUN
ispiv-92	56	39	truth	truth	NOUN
ispiv-92	56	40	spectrum	spectrum	NOUN
ispiv-92	56	41	and	and	CCONJ
ispiv-92	56	42	the	the	DET
ispiv-92	56	43	transfer	transfer	NOUN
ispiv-92	56	44	function	function	NOUN
ispiv-92	56	45	of	of	ADP
ispiv-92	56	46	the	the	DET
ispiv-92	56	47	prefilter	prefilter	NOUN
ispiv-92	56	48	autocorrelation	autocorrelation	NOUN
ispiv-92	56	49	coefficients	coefficient	NOUN
ispiv-92	56	50	can	can	AUX
ispiv-92	56	51	be	be	AUX
ispiv-92	56	52	computed	compute	VERB
ispiv-92	56	53	directly	directly	ADV
ispiv-92	56	54	using	use	VERB
ispiv-92	56	55	a	a	DET
ispiv-92	56	56	fourier	fourier	NOUN
ispiv-92	56	57	transform	transform	NOUN
ispiv-92	56	58	.	.	PUNCT
ispiv-92	57	1	only	only	ADV
ispiv-92	57	2	21	21	NUM
ispiv-92	57	3	autocorrelation	autocorrelation	NOUN
ispiv-92	57	4	coefficients	coefficient	NOUN
ispiv-92	57	5	have	have	AUX
ispiv-92	57	6	been	be	AUX
ispiv-92	57	7	selected	select	VERB
ispiv-92	57	8	(	(	PUNCT
ispiv-92	57	9	for	for	ADP
ispiv-92	57	10	lags	lag	NOUN
ispiv-92	57	11	0	0	NUM
ispiv-92	57	12	to	to	PART
ispiv-92	57	13	20	20	NUM
ispiv-92	57	14	inclusive	inclusive	NOUN
ispiv-92	57	15	)	)	PUNCT
ispiv-92	57	16	to	to	PART
ispiv-92	57	17	test	test	VERB
ispiv-92	57	18	how	how	SCONJ
ispiv-92	57	19	the	the	DET
ispiv-92	57	20	spectral	spectral	ADJ
ispiv-92	57	21	estimation	estimation	NOUN
ispiv-92	57	22	methods	method	NOUN
ispiv-92	57	23	perform	perform	VERB
ispiv-92	57	24	.	.	PUNCT
ispiv-92	58	1	the	the	DET
ispiv-92	58	2	fft	fft	PROPN
ispiv-92	58	3	-	-	PUNCT
ispiv-92	58	4	based	base	VERB
ispiv-92	58	5	method	method	NOUN
ispiv-92	58	6	extends	extend	VERB
ispiv-92	58	7	the	the	DET
ispiv-92	58	8	21	21	NUM
ispiv-92	58	9	coefficients	coefficient	NOUN
ispiv-92	58	10	for	for	ADP
ispiv-92	58	11	lags	lag	NOUN
ispiv-92	58	12	0	0	NUM
ispiv-92	58	13	to	to	ADP
ispiv-92	58	14	20	20	NUM
ispiv-92	58	15	to	to	PART
ispiv-92	58	16	41	41	NUM
ispiv-92	58	17	coefficients	coefficient	NOUN
ispiv-92	58	18	for	for	ADP
ispiv-92	58	19	lags	lag	NOUN
ispiv-92	58	20	-21	-21	NOUN
ispiv-92	58	21	to	to	ADP
ispiv-92	58	22	21	21	NUM
ispiv-92	58	23	by	by	ADP
ispiv-92	58	24	mirroring	mirror	VERB
ispiv-92	58	25	and	and	CCONJ
ispiv-92	58	26	zero	zero	NUM
ispiv-92	58	27	-	-	PUNCT
ispiv-92	58	28	padding	padding	NOUN
ispiv-92	58	29	and	and	CCONJ
ispiv-92	58	30	applies	apply	VERB
ispiv-92	58	31	a	a	DET
ispiv-92	58	32	hann	hann	PROPN
ispiv-92	58	33	window	window	NOUN
ispiv-92	58	34	to	to	ADP
ispiv-92	58	35	the	the	DET
ispiv-92	58	36	result	result	NOUN
ispiv-92	58	37	.	.	PUNCT
ispiv-92	59	1	the	the	DET
ispiv-92	59	2	windowed	windowed	ADJ
ispiv-92	59	3	autocorrelation	autocorrelation	NOUN
ispiv-92	59	4	function	function	NOUN
ispiv-92	59	5	is	be	AUX
ispiv-92	59	6	then	then	ADV
ispiv-92	59	7	used	use	VERB
ispiv-92	59	8	as	as	ADP
ispiv-92	59	9	input	input	NOUN
ispiv-92	59	10	to	to	ADP
ispiv-92	59	11	a	a	DET
ispiv-92	59	12	zero	zero	NUM
ispiv-92	59	13	-	-	PUNCT
ispiv-92	59	14	padded	pad	VERB
ispiv-92	59	15	fft	fft	NOUN
ispiv-92	59	16	.	.	PUNCT
ispiv-92	60	1	the	the	DET
ispiv-92	60	2	resulting	result	VERB
ispiv-92	60	3	magnitudes	magnitude	NOUN
ispiv-92	60	4	are	be	AUX
ispiv-92	60	5	squared	square	VERB
ispiv-92	60	6	and	and	CCONJ
ispiv-92	60	7	plotted	plot	VERB
ispiv-92	60	8	against	against	ADP
ispiv-92	60	9	their	their	PRON
ispiv-92	60	10	frequency	frequency	NOUN
ispiv-92	60	11	.	.	PUNCT
ispiv-92	61	1	the	the	DET
ispiv-92	61	2	ar	ar	NOUN
ispiv-92	61	3	-	-	PUNCT
ispiv-92	61	4	based	base	VERB
ispiv-92	61	5	method	method	NOUN
ispiv-92	61	6	applies	apply	VERB
ispiv-92	61	7	the	the	DET
ispiv-92	61	8	computations	computation	NOUN
ispiv-92	61	9	shown	show	VERB
ispiv-92	61	10	in	in	ADP
ispiv-92	61	11	listing	list	VERB
ispiv-92	61	12	1	1	NUM
ispiv-92	61	13	of	of	ADP
ispiv-92	61	14	section	section	NOUN
ispiv-92	61	15	2.2	2.2	NUM
ispiv-92	61	16	with	with	ADP
ispiv-92	61	17	p	p	NOUN
ispiv-92	61	18	=	=	NOUN
ispiv-92	61	19	20	20	NUM
ispiv-92	61	20	.	.	PUNCT
ispiv-92	62	1	as	as	SCONJ
ispiv-92	62	2	can	can	AUX
ispiv-92	62	3	be	be	AUX
ispiv-92	62	4	seen	see	VERB
ispiv-92	62	5	in	in	ADP
ispiv-92	62	6	figure	figure	NOUN
ispiv-92	62	7	1	1	NUM
ispiv-92	62	8	,	,	PUNCT
ispiv-92	62	9	fft	fft	NOUN
ispiv-92	62	10	-	-	PUNCT
ispiv-92	62	11	based	base	VERB
ispiv-92	62	12	methods	method	NOUN
ispiv-92	62	13	struggle	struggle	VERB
ispiv-92	62	14	to	to	PART
ispiv-92	62	15	deal	deal	VERB
ispiv-92	62	16	with	with	ADP
ispiv-92	62	17	such	such	DET
ispiv-92	62	18	a	a	DET
ispiv-92	62	19	spectrum	spectrum	NOUN
ispiv-92	62	20	given	give	VERB
ispiv-92	62	21	only	only	ADV
ispiv-92	62	22	a	a	DET
ispiv-92	62	23	small	small	ADJ
ispiv-92	62	24	symmetric	symmetric	ADJ
ispiv-92	62	25	window	window	NOUN
ispiv-92	62	26	of	of	ADP
ispiv-92	62	27	41	41	NUM
ispiv-92	62	28	autocorrelation	autocorrelation	NOUN
ispiv-92	62	29	coefficients	coefficient	NOUN
ispiv-92	62	30	.	.	PUNCT
ispiv-92	63	1	we	we	PRON
ispiv-92	63	2	can	can	AUX
ispiv-92	63	3	clearly	clearly	ADV
ispiv-92	63	4	see	see	VERB
ispiv-92	63	5	the	the	DET
ispiv-92	63	6	side	side	NOUN
ispiv-92	63	7	lobes	lobe	NOUN
ispiv-92	63	8	of	of	ADP
ispiv-92	63	9	lower	low	ADJ
ispiv-92	63	10	frequencies	frequency	NOUN
ispiv-92	63	11	that	that	PRON
ispiv-92	63	12	dominate	dominate	VERB
ispiv-92	63	13	the	the	DET
ispiv-92	63	14	estimation	estimation	NOUN
ispiv-92	63	15	of	of	ADP
ispiv-92	63	16	the	the	DET
ispiv-92	63	17	power	power	NOUN
ispiv-92	63	18	spectrum	spectrum	NOUN
ispiv-92	63	19	estimates	estimate	NOUN
ispiv-92	63	20	for	for	ADP
ispiv-92	63	21	higher	high	ADJ
ispiv-92	63	22	frequencies	frequency	NOUN
ispiv-92	63	23	.	.	PUNCT
ispiv-92	64	1	the	the	DET
ispiv-92	64	2	prefilters	prefilter	NOUN
ispiv-92	64	3	help	help	VERB
ispiv-92	64	4	reduce	reduce	VERB
ispiv-92	64	5	the	the	DET
ispiv-92	64	6	damage	damage	NOUN
ispiv-92	64	7	by	by	ADP
ispiv-92	64	8	amplifying	amplify	VERB
ispiv-92	64	9	the	the	DET
ispiv-92	64	10	higher	high	ADJ
ispiv-92	64	11	frequencies	frequency	NOUN
ispiv-92	64	12	and	and	CCONJ
ispiv-92	64	13	attenuating	attenuate	VERB
ispiv-92	64	14	them	they	PRON
ispiv-92	64	15	again	again	ADV
ispiv-92	64	16	after	after	ADP
ispiv-92	64	17	the	the	DET
ispiv-92	64	18	estimation	estimation	NOUN
ispiv-92	64	19	.	.	PUNCT
ispiv-92	65	1	but	but	CCONJ
ispiv-92	65	2	the	the	DET
ispiv-92	65	3	most	most	ADV
ispiv-92	65	4	important	important	ADJ
ispiv-92	65	5	feature	feature	NOUN
ispiv-92	65	6	of	of	ADP
ispiv-92	65	7	the	the	DET
ispiv-92	65	8	spectrum	spectrum	NOUN
ispiv-92	65	9	for	for	ADP
ispiv-92	65	10	the	the	DET
ispiv-92	65	11	purpose	purpose	NOUN
ispiv-92	65	12	of	of	ADP
ispiv-92	65	13	noise	noise	NOUN
ispiv-92	65	14	reduction	reduction	NOUN
ispiv-92	65	15	is	be	AUX
ispiv-92	65	16	the	the	DET
ispiv-92	65	17	frequency	frequency	NOUN
ispiv-92	65	18	region	region	NOUN
ispiv-92	65	19	in	in	ADP
ispiv-92	65	20	which	which	PRON
ispiv-92	65	21	the	the	DET
ispiv-92	65	22	power	power	NOUN
ispiv-92	65	23	spectrum	spectrum	NOUN
ispiv-92	65	24	flattens	flatten	VERB
ispiv-92	65	25	again	again	ADV
ispiv-92	65	26	because	because	SCONJ
ispiv-92	65	27	this	this	PRON
ispiv-92	65	28	is	be	AUX
ispiv-92	65	29	where	where	SCONJ
ispiv-92	65	30	the	the	DET
ispiv-92	65	31	signal	signal	NOUN
ispiv-92	65	32	-	-	PUNCT
ispiv-92	65	33	to	to	ADP
ispiv-92	65	34	-	-	PUNCT
ispiv-92	65	35	noise	noise	NOUN
ispiv-92	65	36	ratio	ratio	NOUN
ispiv-92	65	37	crosses	cross	VERB
ispiv-92	65	38	the	the	DET
ispiv-92	65	39	0	0	NUM
ispiv-92	65	40	db	db	NOUN
ispiv-92	65	41	level	level	NOUN
ispiv-92	65	42	and	and	CCONJ
ispiv-92	65	43	the	the	DET
ispiv-92	65	44	point	point	NOUN
ispiv-92	65	45	at	at	ADP
ispiv-92	65	46	which	which	PRON
ispiv-92	65	47	a	a	DET
ispiv-92	65	48	noise	noise	NOUN
ispiv-92	65	49	reduction	reduction	NOUN
ispiv-92	65	50	filter	filter	NOUN
ispiv-92	65	51	should	should	AUX
ispiv-92	65	52	start	start	VERB
ispiv-92	65	53	to	to	PART
ispiv-92	65	54	attenuate	attenuate	VERB
ispiv-92	65	55	the	the	DET
ispiv-92	65	56	high	high	ADJ
ispiv-92	65	57	frequencies	frequency	NOUN
ispiv-92	65	58	.	.	PUNCT
ispiv-92	66	1	unfortunately	unfortunately	ADV
ispiv-92	66	2	,	,	PUNCT
ispiv-92	66	3	the	the	DET
ispiv-92	66	4	fft	fft	NOUN
ispiv-92	66	5	-	-	PUNCT
ispiv-92	66	6	based	base	VERB
ispiv-92	66	7	methods	method	NOUN
ispiv-92	66	8	fail	fail	VERB
ispiv-92	66	9	to	to	PART
ispiv-92	66	10	resolve	resolve	VERB
ispiv-92	66	11	this	this	PRON
ispiv-92	66	12	reliably	reliably	ADV
ispiv-92	66	13	in	in	ADP
ispiv-92	66	14	this	this	DET
ispiv-92	66	15	case	case	NOUN
ispiv-92	66	16	even	even	ADV
ispiv-92	66	17	with	with	SCONJ
ispiv-92	66	18	the	the	DET
ispiv-92	66	19	prefilters	prefilter	NOUN
ispiv-92	66	20	enabled	enable	VERB
ispiv-92	66	21	(	(	PUNCT
ispiv-92	66	22	k	k	X
ispiv-92	66	23	>	>	X
ispiv-92	66	24	0	0	NUM
ispiv-92	66	25	)	)	PUNCT
ispiv-92	66	26	.	.	PUNCT
ispiv-92	67	1	the	the	DET
ispiv-92	67	2	auto	auto	NOUN
ispiv-92	67	3	-	-	PUNCT
ispiv-92	67	4	regressive	regressive	ADJ
ispiv-92	67	5	approach	approach	NOUN
ispiv-92	67	6	tracks	track	VERB
ispiv-92	67	7	the	the	DET
ispiv-92	67	8	true	true	ADJ
ispiv-92	67	9	spectrum	spectrum	NOUN
ispiv-92	67	10	more	more	ADV
ispiv-92	67	11	closely	closely	ADV
ispiv-92	67	12	in	in	ADP
ispiv-92	67	13	comparison	comparison	NOUN
ispiv-92	67	14	.	.	PUNCT
ispiv-92	68	1	most	most	ADJ
ispiv-92	68	2	errors	error	NOUN
ispiv-92	68	3	of	of	ADP
ispiv-92	68	4	the	the	DET
ispiv-92	68	5	estimates	estimate	NOUN
ispiv-92	68	6	are	be	AUX
ispiv-92	68	7	below	below	ADP
ispiv-92	68	8	1	1	NUM
ispiv-92	68	9	%	%	NOUN
ispiv-92	68	10	and	and	CCONJ
ispiv-92	68	11	only	only	ADV
ispiv-92	68	12	rise	rise	VERB
ispiv-92	68	13	with	with	ADP
ispiv-92	68	14	the	the	DET
ispiv-92	68	15	lower	low	ADJ
ispiv-92	68	16	frequencies	frequency	NOUN
ispiv-92	68	17	to	to	ADP
ispiv-92	68	18	about	about	ADP
ispiv-92	68	19	6	6	NUM
ispiv-92	68	20	%	%	NOUN
ispiv-92	68	21	.	.	PUNCT
ispiv-92	69	1	the	the	DET
ispiv-92	69	2	estimated	estimate	VERB
ispiv-92	69	3	curves	curve	NOUN
ispiv-92	69	4	oscillate	oscillate	VERB
ispiv-92	69	5	around	around	ADP
ispiv-92	69	6	the	the	DET
ispiv-92	69	7	ground	ground	NOUN
ispiv-92	69	8	truth	truth	NOUN
ispiv-92	69	9	which	which	PRON
ispiv-92	69	10	is	be	AUX
ispiv-92	69	11	not	not	PART
ispiv-92	69	12	surprising	surprising	ADJ
ispiv-92	69	13	given	give	VERB
ispiv-92	69	14	that	that	SCONJ
ispiv-92	69	15	they	they	PRON
ispiv-92	69	16	are	be	AUX
ispiv-92	69	17	expressed	express	VERB
ispiv-92	69	18	using	use	VERB
ispiv-92	69	19	an	an	DET
ispiv-92	69	20	order	order	NOUN
ispiv-92	69	21	20	20	NUM
ispiv-92	69	22	polynomial	polynomial	ADJ
ispiv-92	69	23	.	.	PUNCT
ispiv-92	70	1	between	between	ADP
ispiv-92	70	2	different	different	ADJ
ispiv-92	70	3	prefilters	prefilter	NOUN
ispiv-92	70	4	the	the	DET
ispiv-92	70	5	curves	curve	NOUN
ispiv-92	70	6	look	look	VERB
ispiv-92	70	7	similar	similar	ADJ
ispiv-92	70	8	.	.	PUNCT
ispiv-92	71	1	but	but	CCONJ
ispiv-92	71	2	the	the	DET
ispiv-92	71	3	equation	equation	NOUN
ispiv-92	71	4	systems	system	NOUN
ispiv-92	71	5	to	to	PART
ispiv-92	71	6	compute	compute	VERB
ispiv-92	71	7	the	the	DET
ispiv-92	71	8	filter	filter	NOUN
ispiv-92	71	9	coefficients	coefficient	NOUN
ispiv-92	71	10	are	be	AUX
ispiv-92	71	11	very	very	ADV
ispiv-92	71	12	different	different	ADJ
ispiv-92	71	13	in	in	ADP
ispiv-92	71	14	their	their	PRON
ispiv-92	71	15	”	"	PUNCT
ispiv-92	71	16	numerical	numerical	ADJ
ispiv-92	71	17	difficulty	difficulty	NOUN
ispiv-92	71	18	”	"	PUNCT
ispiv-92	71	19	,	,	PUNCT
ispiv-92	71	20	see	see	VERB
ispiv-92	71	21	table	table	NOUN
ispiv-92	71	22	1	1	NUM
ispiv-92	71	23	.	.	PUNCT
ispiv-92	72	1	high	high	ADJ
ispiv-92	72	2	condition	condition	NOUN
ispiv-92	72	3	numbers	number	NOUN
ispiv-92	72	4	can	can	AUX
ispiv-92	72	5	make	make	VERB
ispiv-92	72	6	the	the	DET
ispiv-92	72	7	method	method	NOUN
ispiv-92	72	8	unreliable	unreliable	ADJ
ispiv-92	72	9	in	in	ADP
ispiv-92	72	10	the	the	DET
ispiv-92	72	11	light	light	NOUN
ispiv-92	72	12	of	of	ADP
ispiv-92	72	13	finite	finite	ADJ
ispiv-92	72	14	precision	precision	NOUN
ispiv-92	72	15	arithmetic	arithmetic	ADJ
ispiv-92	72	16	and	and	CCONJ
ispiv-92	72	17	rounding	round	VERB
ispiv-92	72	18	errors	error	NOUN
ispiv-92	72	19	.	.	PUNCT
ispiv-92	73	1	the	the	DET
ispiv-92	73	2	use	use	NOUN
ispiv-92	73	3	of	of	ADP
ispiv-92	73	4	appropriate	appropriate	ADJ
ispiv-92	73	5	prefilters	prefilter	NOUN
ispiv-92	73	6	can	can	AUX
ispiv-92	73	7	lower	lower	VERB
ispiv-92	73	8	the	the	DET
ispiv-92	73	9	condition	condition	NOUN
ispiv-92	73	10	number	number	NOUN
ispiv-92	73	11	and	and	CCONJ
ispiv-92	73	12	thus	thus	ADV
ispiv-92	73	13	improve	improve	VERB
ispiv-92	73	14	numerical	numerical	ADJ
ispiv-92	73	15	stability	stability	NOUN
ispiv-92	73	16	of	of	ADP
ispiv-92	73	17	the	the	DET
ispiv-92	73	18	method	method	NOUN
ispiv-92	73	19	.	.	PUNCT
ispiv-92	74	1	in	in	ADP
ispiv-92	74	2	fact	fact	NOUN
ispiv-92	74	3	,	,	PUNCT
ispiv-92	74	4	the	the	DET
ispiv-92	74	5	condition	condition	NOUN
ispiv-92	74	6	number	number	NOUN
ispiv-92	74	7	can	can	AUX
ispiv-92	74	8	be	be	AUX
ispiv-92	74	9	seen	see	VERB
ispiv-92	74	10	as	as	ADP
ispiv-92	74	11	a	a	DET
ispiv-92	74	12	measure	measure	NOUN
ispiv-92	74	13	of	of	ADP
ispiv-92	74	14	how	how	SCONJ
ispiv-92	74	15	well	well	ADV
ispiv-92	74	16	the	the	DET
ispiv-92	74	17	prefilter	prefilter	NOUN
ispiv-92	74	18	is	be	AUX
ispiv-92	74	19	able	able	ADJ
ispiv-92	74	20	to	to	PART
ispiv-92	74	21	”	"	PUNCT
ispiv-92	74	22	whiten	whiten	VERB
ispiv-92	74	23	”	"	PUNCT
ispiv-92	74	24	the	the	DET
ispiv-92	74	25	signal	signal	NOUN
ispiv-92	74	26	.	.	PUNCT
ispiv-92	75	1	10	10	NUM
ispiv-92	75	2	-3	-3	SYM
ispiv-92	75	3	10	10	NUM
ispiv-92	75	4	-2	-2	NOUN
ispiv-92	75	5	10	10	NUM
ispiv-92	75	6	-1	-1	SYM
ispiv-92	75	7	10	10	NUM
ispiv-92	75	8	0	0	NUM
ispiv-92	75	9	10	10	NUM
ispiv-92	75	10	-10	-10	SYM
ispiv-92	75	11	10	10	NUM
ispiv-92	75	12	-09	-09	NUM
ispiv-92	75	13	10	10	NUM
ispiv-92	75	14	-08	-08	SYM
ispiv-92	75	15	10	10	NUM
ispiv-92	75	16	-07	-07	SYM
ispiv-92	75	17	10	10	NUM
ispiv-92	75	18	-06	-06	NUM
ispiv-92	75	19	10	10	NUM
ispiv-92	75	20	-05	-05	NUM
ispiv-92	75	21	10	10	NUM
ispiv-92	75	22	-04	-04	NUM
ispiv-92	75	23	10	10	NUM
ispiv-92	75	24	-03	-03	NUM
ispiv-92	75	25	10	10	NUM
ispiv-92	75	26	-02	-02	NUM
ispiv-92	75	27	10	10	NUM
ispiv-92	75	28	-01	-01	NUM
ispiv-92	75	29	10	10	NUM
ispiv-92	75	30	00	00	NUM
ispiv-92	75	31	10	10	NUM
ispiv-92	75	32	01	01	NUM
ispiv-92	75	33	10	10	NUM
ispiv-92	75	34	02	02	NUM
ispiv-92	75	35	10	10	NUM
ispiv-92	75	36	03	03	NUM
ispiv-92	75	37	10	10	NUM
ispiv-92	75	38	04	04	NUM
ispiv-92	75	39	10	10	NUM
ispiv-92	75	40	05	05	NUM
ispiv-92	75	41	10	10	NUM
ispiv-92	75	42	06	06	NUM
ispiv-92	75	43	10	10	NUM
ispiv-92	75	44	07	07	NUM
ispiv-92	75	45	frequency	frequency	NOUN
ispiv-92	76	1	p	p	X
ispiv-92	76	2	o	o	X
ispiv-92	76	3	w	w	NOUN
ispiv-92	76	4	e	e	NOUN
ispiv-92	76	5	r	r	NOUN
ispiv-92	76	6	sp	sp	ADP
ispiv-92	76	7	e	e	NOUN
ispiv-92	76	8	c	c	NOUN
ispiv-92	76	9	tr	tr	NOUN
ispiv-92	76	10	a	a	DET
ispiv-92	76	11	l	l	NOUN
ispiv-92	76	12	d	d	X
ispiv-92	76	13	e	e	NOUN
ispiv-92	76	14	n	n	CCONJ
ispiv-92	76	15	si	si	X
ispiv-92	76	16	ty	ty	PRON
ispiv-92	76	17	fft	fft	PROPN
ispiv-92	76	18	-	-	PUNCT
ispiv-92	76	19	based	base	VERB
ispiv-92	76	20	spectral	spectral	ADJ
ispiv-92	76	21	estimation	estimation	NOUN
ispiv-92	76	22	10	10	NUM
ispiv-92	76	23	-3	-3	SYM
ispiv-92	76	24	10	10	NUM
ispiv-92	76	25	-2	-2	NOUN
ispiv-92	76	26	10	10	NUM
ispiv-92	76	27	-1	-1	SYM
ispiv-92	76	28	10	10	NUM
ispiv-92	76	29	0	0	NUM
ispiv-92	76	30	10	10	NUM
ispiv-92	76	31	-10	-10	SYM
ispiv-92	76	32	10	10	NUM
ispiv-92	76	33	-09	-09	NUM
ispiv-92	76	34	10	10	NUM
ispiv-92	76	35	-08	-08	SYM
ispiv-92	76	36	10	10	NUM
ispiv-92	76	37	-07	-07	SYM
ispiv-92	76	38	10	10	NUM
ispiv-92	76	39	-06	-06	NUM
ispiv-92	76	40	10	10	NUM
ispiv-92	76	41	-05	-05	NUM
ispiv-92	76	42	10	10	NUM
ispiv-92	76	43	-04	-04	NUM
ispiv-92	76	44	10	10	NUM
ispiv-92	76	45	-03	-03	NUM
ispiv-92	76	46	10	10	NUM
ispiv-92	76	47	-02	-02	NUM
ispiv-92	76	48	10	10	NUM
ispiv-92	76	49	-01	-01	NUM
ispiv-92	76	50	10	10	NUM
ispiv-92	76	51	00	00	NUM
ispiv-92	76	52	10	10	NUM
ispiv-92	76	53	01	01	NUM
ispiv-92	76	54	10	10	NUM
ispiv-92	76	55	02	02	NUM
ispiv-92	76	56	10	10	NUM
ispiv-92	76	57	03	03	NUM
ispiv-92	76	58	10	10	NUM
ispiv-92	76	59	04	04	NUM
ispiv-92	76	60	10	10	NUM
ispiv-92	76	61	05	05	NUM
ispiv-92	76	62	10	10	NUM
ispiv-92	76	63	06	06	NUM
ispiv-92	76	64	10	10	NUM
ispiv-92	76	65	07	07	NUM
ispiv-92	76	66	frequency	frequency	NOUN
ispiv-92	77	1	p	p	X
ispiv-92	77	2	o	o	X
ispiv-92	77	3	w	w	NOUN
ispiv-92	77	4	e	e	NOUN
ispiv-92	77	5	r	r	NOUN
ispiv-92	77	6	sp	sp	ADP
ispiv-92	77	7	e	e	NOUN
ispiv-92	77	8	c	c	NOUN
ispiv-92	77	9	tr	tr	NOUN
ispiv-92	77	10	a	a	DET
ispiv-92	77	11	l	l	NOUN
ispiv-92	77	12	d	d	X
ispiv-92	77	13	e	e	NOUN
ispiv-92	77	14	n	n	CCONJ
ispiv-92	77	15	si	si	PROPN
ispiv-92	77	16	ty	ty	PRON
ispiv-92	77	17	ar	ar	PROPN
ispiv-92	77	18	-	-	PUNCT
ispiv-92	77	19	based	base	VERB
ispiv-92	77	20	spectral	spectral	ADJ
ispiv-92	77	21	estimation	estimation	NOUN
ispiv-92	77	22	true	true	ADJ
ispiv-92	77	23	error	error	NOUN
ispiv-92	77	24	(	(	PUNCT
ispiv-92	77	25	fft	fft	PROPN
ispiv-92	77	26	,	,	PUNCT
ispiv-92	77	27	k=0	k=0	PROPN
ispiv-92	77	28	)	)	PUNCT
ispiv-92	77	29	error	error	NOUN
ispiv-92	77	30	(	(	PUNCT
ispiv-92	77	31	fft	fft	PROPN
ispiv-92	77	32	,	,	PUNCT
ispiv-92	77	33	k=1	k=1	NOUN
ispiv-92	77	34	)	)	PUNCT
ispiv-92	77	35	error	error	NOUN
ispiv-92	77	36	(	(	PUNCT
ispiv-92	77	37	fft	fft	PROPN
ispiv-92	77	38	,	,	PUNCT
ispiv-92	77	39	k=2	k=2	NOUN
ispiv-92	77	40	)	)	PUNCT
ispiv-92	77	41	true	true	ADJ
ispiv-92	77	42	error	error	NOUN
ispiv-92	77	43	(	(	PUNCT
ispiv-92	77	44	ar	ar	NOUN
ispiv-92	77	45	,	,	PUNCT
ispiv-92	77	46	k=0	k=0	PROPN
ispiv-92	77	47	)	)	PUNCT
ispiv-92	77	48	error	error	NOUN
ispiv-92	77	49	(	(	PUNCT
ispiv-92	77	50	ar	ar	NOUN
ispiv-92	77	51	,	,	PUNCT
ispiv-92	77	52	k=1	k=1	NOUN
ispiv-92	77	53	)	)	PUNCT
ispiv-92	77	54	error	error	NOUN
ispiv-92	77	55	(	(	PUNCT
ispiv-92	77	56	ar	ar	PROPN
ispiv-92	77	57	,	,	PUNCT
ispiv-92	77	58	k=2	k=2	PROPN
ispiv-92	77	59	)	)	PUNCT
ispiv-92	77	60	figure	figure	NOUN
ispiv-92	77	61	1	1	NUM
ispiv-92	77	62	:	:	PUNCT
ispiv-92	77	63	power	power	NOUN
ispiv-92	77	64	spectral	spectral	ADJ
ispiv-92	77	65	density	density	PROPN
ispiv-92	77	66	estimation	estimation	PROPN
ispiv-92	77	67	method	method	NOUN
ispiv-92	77	68	comparison	comparison	NOUN
ispiv-92	77	69	for	for	ADP
ispiv-92	77	70	a	a	DET
ispiv-92	77	71	synthetically	synthetically	ADV
ispiv-92	77	72	generated	generate	VERB
ispiv-92	77	73	case	case	NOUN
ispiv-92	77	74	.	.	PUNCT
ispiv-92	78	1	the	the	DET
ispiv-92	78	2	black	black	ADJ
ispiv-92	78	3	curve	curve	NOUN
ispiv-92	78	4	represents	represent	VERB
ispiv-92	78	5	the	the	DET
ispiv-92	78	6	true	true	ADJ
ispiv-92	78	7	signal	signal	NOUN
ispiv-92	78	8	spectrum	spectrum	NOUN
ispiv-92	78	9	.	.	PUNCT
ispiv-92	79	1	for	for	ADP
ispiv-92	79	2	the	the	DET
ispiv-92	79	3	spectrum	spectrum	NOUN
ispiv-92	79	4	estimates	estimate	VERB
ispiv-92	79	5	only	only	ADV
ispiv-92	79	6	the	the	DET
ispiv-92	79	7	errors	error	NOUN
ispiv-92	79	8	to	to	ADP
ispiv-92	79	9	the	the	DET
ispiv-92	79	10	ground	ground	NOUN
ispiv-92	79	11	truth	truth	NOUN
ispiv-92	79	12	are	be	AUX
ispiv-92	79	13	shown	show	VERB
ispiv-92	79	14	.	.	PUNCT
ispiv-92	80	1	k	k	PROPN
ispiv-92	80	2	refers	refer	VERB
ispiv-92	80	3	to	to	ADP
ispiv-92	80	4	the	the	DET
ispiv-92	80	5	prefilter	prefilter	NOUN
ispiv-92	80	6	order	order	NOUN
ispiv-92	80	7	with	with	ADP
ispiv-92	80	8	k	k	PROPN
ispiv-92	80	9	=	=	SYM
ispiv-92	80	10	0	0	NUM
ispiv-92	80	11	meaning	mean	VERB
ispiv-92	80	12	no	no	DET
ispiv-92	80	13	prefilter	prefilter	NOUN
ispiv-92	80	14	.	.	PUNCT
ispiv-92	81	1	k	k	X
ispiv-92	82	1	=	=	PUNCT
ispiv-92	82	2	0	0	PUNCT
ispiv-92	83	1	k	k	X
ispiv-92	83	2	=	=	SYM
ispiv-92	83	3	1	1	NUM
ispiv-92	83	4	k	k	NOUN
ispiv-92	83	5	=	=	SYM
ispiv-92	83	6	2	2	NUM
ispiv-92	83	7	condition	condition	NOUN
ispiv-92	83	8	number	number	NOUN
ispiv-92	83	9	2.6	2.6	NUM
ispiv-92	83	10	·	·	SYM
ispiv-92	83	11	108	108	NUM
ispiv-92	83	12	3.3	3.3	NUM
ispiv-92	83	13	·	·	SYM
ispiv-92	83	14	103	103	NUM
ispiv-92	83	15	8.1	8.1	NUM
ispiv-92	83	16	·	·	SYM
ispiv-92	83	17	101	101	NUM
ispiv-92	83	18	table	table	NOUN
ispiv-92	83	19	1	1	NUM
ispiv-92	83	20	:	:	PUNCT
ispiv-92	83	21	condition	condition	NOUN
ispiv-92	83	22	numbers	number	NOUN
ispiv-92	83	23	for	for	ADP
ispiv-92	83	24	different	different	ADJ
ispiv-92	83	25	prefilter	prefilter	NOUN
ispiv-92	83	26	orders	order	NOUN
ispiv-92	83	27	3	3	NUM
ispiv-92	83	28	spectral	spectral	ADJ
ispiv-92	83	29	estimation	estimation	NOUN
ispiv-92	83	30	test	test	NOUN
ispiv-92	83	31	on	on	ADP
ispiv-92	83	32	fluid	fluid	ADJ
ispiv-92	83	33	simulation	simulation	NOUN
ispiv-92	83	34	data	data	VERB
ispiv-92	83	35	the	the	DET
ispiv-92	83	36	question	question	NOUN
ispiv-92	83	37	arises	arise	VERB
ispiv-92	83	38	whether	whether	SCONJ
ispiv-92	83	39	the	the	DET
ispiv-92	83	40	black	black	ADJ
ispiv-92	83	41	curve	curve	NOUN
ispiv-92	83	42	in	in	ADP
ispiv-92	83	43	figure	figure	NOUN
ispiv-92	83	44	1	1	NUM
ispiv-92	83	45	for	for	ADP
ispiv-92	83	46	a	a	DET
ispiv-92	83	47	hypothetical	hypothetical	ADJ
ispiv-92	83	48	power	power	NOUN
ispiv-92	83	49	spectrum	spectrum	NOUN
ispiv-92	83	50	is	be	AUX
ispiv-92	83	51	representative	representative	ADJ
ispiv-92	83	52	of	of	ADP
ispiv-92	83	53	measured	measure	VERB
ispiv-92	83	54	particle	particle	NOUN
ispiv-92	83	55	motion	motion	NOUN
ispiv-92	83	56	in	in	ADP
ispiv-92	83	57	a	a	DET
ispiv-92	83	58	fluid	fluid	NOUN
ispiv-92	83	59	.	.	PUNCT
ispiv-92	84	1	therefore	therefore	ADV
ispiv-92	84	2	,	,	PUNCT
ispiv-92	84	3	we	we	PRON
ispiv-92	84	4	applied	apply	VERB
ispiv-92	84	5	our	our	PRON
ispiv-92	84	6	spectral	spectral	ADJ
ispiv-92	84	7	estimation	estimation	NOUN
ispiv-92	84	8	method	method	NOUN
ispiv-92	84	9	on	on	ADP
ispiv-92	84	10	a	a	DET
ispiv-92	84	11	known	know	VERB
ispiv-92	84	12	data	datum	NOUN
ispiv-92	84	13	set	set	VERB
ispiv-92	84	14	of	of	ADP
ispiv-92	84	15	the	the	DET
ispiv-92	84	16	first	first	ADJ
ispiv-92	84	17	data	data	NOUN
ispiv-92	84	18	assimilation	assimilation	NOUN
ispiv-92	84	19	challenge	challenge	NOUN
ispiv-92	84	20	(	(	PUNCT
ispiv-92	84	21	sciacchitano	sciacchitano	NOUN
ispiv-92	84	22	et	et	PROPN
ispiv-92	84	23	al	al	PROPN
ispiv-92	84	24	.	.	PROPN
ispiv-92	84	25	(	(	PUNCT
ispiv-92	84	26	2021a	2021a	NUM
ispiv-92	84	27	)	)	PUNCT
ispiv-92	84	28	)	)	PUNCT
ispiv-92	84	29	.	.	PUNCT
ispiv-92	85	1	this	this	DET
ispiv-92	85	2	data	datum	NOUN
ispiv-92	85	3	set	set	VERB
ispiv-92	85	4	covers	cover	VERB
ispiv-92	85	5	particle	particle	NOUN
ispiv-92	85	6	locations	location	NOUN
ispiv-92	85	7	for	for	ADP
ispiv-92	85	8	25	25	NUM
ispiv-92	85	9	time	time	NOUN
ispiv-92	85	10	steps	step	NOUN
ispiv-92	85	11	based	base	VERB
ispiv-92	85	12	on	on	ADP
ispiv-92	85	13	a	a	DET
ispiv-92	85	14	fluid	fluid	ADJ
ispiv-92	85	15	simulation	simulation	NOUN
ispiv-92	85	16	and	and	CCONJ
ispiv-92	85	17	simulated	simulate	VERB
ispiv-92	85	18	white	white	ADJ
ispiv-92	85	19	measurement	measurement	PROPN
ispiv-92	85	20	noise	noise	NOUN
ispiv-92	85	21	.	.	PUNCT
ispiv-92	86	1	figure	figure	NOUN
ispiv-92	86	2	2	2	NUM
ispiv-92	86	3	shows	show	VERB
ispiv-92	86	4	the	the	DET
ispiv-92	86	5	power	power	NOUN
ispiv-92	86	6	spectral	spectral	ADJ
ispiv-92	86	7	density	density	NOUN
ispiv-92	86	8	estimate	estimate	NOUN
ispiv-92	86	9	of	of	ADP
ispiv-92	86	10	the	the	DET
ispiv-92	86	11	simulated	simulate	VERB
ispiv-92	86	12	particle	particle	NOUN
ispiv-92	86	13	data	datum	NOUN
ispiv-92	86	14	for	for	ADP
ispiv-92	86	15	the	the	DET
ispiv-92	86	16	particles	particle	NOUN
ispiv-92	86	17	’	'	PUNCT
ispiv-92	86	18	z	z	NOUN
ispiv-92	86	19	coordinates	coordinate	NOUN
ispiv-92	86	20	which	which	PRON
ispiv-92	86	21	closely	closely	ADV
ispiv-92	86	22	matches	match	VERB
ispiv-92	86	23	the	the	DET
ispiv-92	86	24	spectrum	spectrum	NOUN
ispiv-92	86	25	assumption	assumption	NOUN
ispiv-92	86	26	from	from	ADP
ispiv-92	86	27	the	the	DET
ispiv-92	86	28	previous	previous	ADJ
ispiv-92	86	29	section	section	NOUN
ispiv-92	86	30	.	.	PUNCT
ispiv-92	87	1	in	in	ADP
ispiv-92	87	2	particular	particular	ADJ
ispiv-92	87	3	,	,	PUNCT
ispiv-92	87	4	we	we	PRON
ispiv-92	87	5	have	have	VERB
ispiv-92	87	6	the	the	DET
ispiv-92	87	7	same	same	ADJ
ispiv-92	87	8	slope	slope	NOUN
ispiv-92	87	9	of	of	ADP
ispiv-92	87	10	about	about	ADP
ispiv-92	87	11	-6	-6	PROPN
ispiv-92	87	12	in	in	ADP
ispiv-92	87	13	the	the	DET
ispiv-92	87	14	log	log	NOUN
ispiv-92	87	15	-	-	PUNCT
ispiv-92	87	16	log	log	NOUN
ispiv-92	87	17	plot	plot	NOUN
ispiv-92	87	18	right	right	ADV
ispiv-92	87	19	before	before	SCONJ
ispiv-92	87	20	the	the	DET
ispiv-92	87	21	measurement	measurement	NOUN
ispiv-92	87	22	noise	noise	NOUN
ispiv-92	87	23	becomes	become	VERB
ispiv-92	87	24	dominant	dominant	ADJ
ispiv-92	87	25	and	and	CCONJ
ispiv-92	87	26	the	the	DET
ispiv-92	87	27	curve	curve	NOUN
ispiv-92	87	28	flattens	flatten	VERB
ispiv-92	87	29	.	.	PUNCT
ispiv-92	88	1	we	we	PRON
ispiv-92	88	2	have	have	AUX
ispiv-92	88	3	observed	observe	VERB
ispiv-92	88	4	this	this	DET
ispiv-92	88	5	slope	slope	NOUN
ispiv-92	88	6	to	to	PART
ispiv-92	88	7	be	be	AUX
ispiv-92	88	8	typical	typical	ADJ
ispiv-92	88	9	in	in	ADP
ispiv-92	88	10	these	these	DET
ispiv-92	88	11	sorts	sort	NOUN
ispiv-92	88	12	of	of	ADP
ispiv-92	88	13	fluid	fluid	ADJ
ispiv-92	88	14	experiments	experiment	NOUN
ispiv-92	88	15	.	.	PUNCT
ispiv-92	89	1	4	4	NUM
ispiv-92	89	2	filtering	filter	VERB
ispiv-92	89	3	with	with	ADP
ispiv-92	89	4	trackfit	trackfit	NOUN
ispiv-92	89	5	instead	instead	ADV
ispiv-92	89	6	of	of	ADP
ispiv-92	89	7	low	low	ADJ
ispiv-92	89	8	-	-	PUNCT
ispiv-92	89	9	pass	pass	NOUN
ispiv-92	89	10	filtering	filtering	NOUN
ispiv-92	89	11	by	by	ADP
ispiv-92	89	12	direct	direct	ADJ
ispiv-92	89	13	convolution	convolution	NOUN
ispiv-92	89	14	,	,	PUNCT
ispiv-92	89	15	a	a	DET
ispiv-92	89	16	filtering	filter	VERB
ispiv-92	89	17	effect	effect	NOUN
ispiv-92	89	18	can	can	AUX
ispiv-92	89	19	also	also	ADV
ispiv-92	89	20	be	be	AUX
ispiv-92	89	21	achieved	achieve	VERB
ispiv-92	89	22	by	by	ADP
ispiv-92	89	23	posing	pose	VERB
ispiv-92	89	24	and	and	CCONJ
ispiv-92	89	25	solving	solve	VERB
ispiv-92	89	26	an	an	DET
ispiv-92	89	27	overdetermined	overdetermine	VERB
ispiv-92	89	28	linear	linear	ADJ
ispiv-92	89	29	equation	equation	NOUN
ispiv-92	89	30	system	system	NOUN
ispiv-92	89	31	in	in	ADP
ispiv-92	89	32	the	the	DET
ispiv-92	89	33	least	least	ADJ
ispiv-92	89	34	squares	square	NOUN
ispiv-92	89	35	sense	sense	NOUN
ispiv-92	89	36	such	such	ADJ
ispiv-92	89	37	as	as	ADP
ispiv-92	89	38	the	the	DET
ispiv-92	89	39	one	one	NOUN
ispiv-92	89	40	in	in	ADP
ispiv-92	89	41	equation	equation	NOUN
ispiv-92	89	42	5	5	NUM
ispiv-92	89	43	:	:	SYM
ispiv-92	89	44	10	10	NUM
ispiv-92	89	45	-3	-3	SYM
ispiv-92	89	46	10	10	NUM
ispiv-92	90	1	-2	-2	NOUN
ispiv-92	90	2	10	10	NUM
ispiv-92	90	3	-1	-1	SYM
ispiv-92	91	1	10	10	NUM
ispiv-92	91	2	0	0	NUM
ispiv-92	91	3	10	10	NUM
ispiv-92	91	4	-5	-5	NUM
ispiv-92	91	5	10	10	NUM
ispiv-92	91	6	-4	-4	SYM
ispiv-92	91	7	10	10	NUM
ispiv-92	91	8	-3	-3	SYM
ispiv-92	91	9	10	10	NUM
ispiv-92	91	10	-2	-2	NOUN
ispiv-92	91	11	10	10	NUM
ispiv-92	91	12	-1	-1	SYM
ispiv-92	91	13	10	10	NUM
ispiv-92	91	14	0	0	NUM
ispiv-92	91	15	10	10	NUM
ispiv-92	91	16	1	1	NUM
ispiv-92	91	17	10	10	NUM
ispiv-92	91	18	2	2	NUM
ispiv-92	91	19	10	10	NUM
ispiv-92	91	20	3	3	NUM
ispiv-92	91	21	10	10	NUM
ispiv-92	91	22	4	4	NUM
ispiv-92	91	23	10	10	NUM
ispiv-92	91	24	5	5	NUM
ispiv-92	91	25	normalized	normalize	VERB
ispiv-92	91	26	frequency	frequency	NOUN
ispiv-92	92	1	p	p	X
ispiv-92	92	2	o	o	X
ispiv-92	92	3	w	w	NOUN
ispiv-92	92	4	e	e	NOUN
ispiv-92	92	5	r	r	NOUN
ispiv-92	92	6	sp	sp	ADP
ispiv-92	92	7	e	e	NOUN
ispiv-92	92	8	c	c	NOUN
ispiv-92	92	9	tr	tr	NOUN
ispiv-92	92	10	a	a	DET
ispiv-92	92	11	l	l	NOUN
ispiv-92	92	12	d	d	X
ispiv-92	92	13	e	e	NOUN
ispiv-92	92	14	n	n	NOUN
ispiv-92	92	15	si	si	INTJ
ispiv-92	92	16	ty	ty	INTJ
ispiv-92	92	17	figure	figure	NOUN
ispiv-92	92	18	2	2	NUM
ispiv-92	92	19	:	:	PUNCT
ispiv-92	92	20	power	power	NOUN
ispiv-92	92	21	spectral	spectral	ADJ
ispiv-92	92	22	density	density	NOUN
ispiv-92	92	23	estimation	estimation	NOUN
ispiv-92	92	24	of	of	ADP
ispiv-92	92	25	particle	particle	NOUN
ispiv-92	92	26	data	datum	NOUN
ispiv-92	92	27	of	of	ADP
ispiv-92	92	28	1st	1st	ADJ
ispiv-92	92	29	da	da	PROPN
ispiv-92	92	30	challenge	challenge	NOUN
ispiv-92	92	31	(	(	PUNCT
ispiv-92	92	32	0.160	0.160	NUM
ispiv-92	92	33	ppp	ppp	NOUN
ispiv-92	92	34	case	case	NOUN
ispiv-92	92	35	)	)	PUNCT
ispiv-92	92	36	.	.	PUNCT
ispiv-92	93	1			PROPN
ispiv-92	93	2	w	w	PROPN
ispiv-92	93	3	w	w	PROPN
ispiv-92	93	4	w	w	PROPN
ispiv-92	93	5	.	.	PUNCT
ispiv-92	93	6	.	.	PUNCT
ispiv-92	93	7	.	.	PUNCT
ispiv-92	94	1	w	w	PROPN
ispiv-92	94	2	w	w	PROPN
ispiv-92	94	3	−1	−1	NOUN
ispiv-92	94	4	1	1	NUM
ispiv-92	94	5	−1	−1	NOUN
ispiv-92	94	6	1	1	NUM
ispiv-92	94	7	−1	−1	NOUN
ispiv-92	94	8	1	1	NUM
ispiv-92	94	9	.	.	PUNCT
ispiv-92	94	10	.	.	PUNCT
ispiv-92	94	11	.	.	PUNCT
ispiv-92	94	12	.	.	PUNCT
ispiv-92	94	13	.	.	PUNCT
ispiv-92	94	14	.	.	PUNCT
ispiv-92	95	1	−1	−1	NOUN
ispiv-92	95	2	1	1	NUM
ispiv-92	95	3			PROPN
ispiv-92	95	4	s′	s′	PUNCT
ispiv-92	95	5	=	=	PUNCT
ispiv-92	95	6	(	(	PUNCT
ispiv-92	95	7	w	w	PROPN
ispiv-92	95	8	·	·	PUNCT
ispiv-92	95	9	s	s	PART
ispiv-92	95	10	0	0	NUM
ispiv-92	95	11	)	)	PUNCT
ispiv-92	95	12	(	(	PUNCT
ispiv-92	95	13	5	5	X
ispiv-92	95	14	)	)	PUNCT
ispiv-92	95	15	here	here	ADV
ispiv-92	95	16	,	,	PUNCT
ispiv-92	95	17	s	s	VERB
ispiv-92	95	18	refers	refer	VERB
ispiv-92	95	19	to	to	ADP
ispiv-92	95	20	the	the	DET
ispiv-92	95	21	raw	raw	ADJ
ispiv-92	95	22	unfiltered	unfiltered	ADJ
ispiv-92	95	23	signal	signal	NOUN
ispiv-92	95	24	,	,	PUNCT
ispiv-92	95	25	s′	s′	PROPN
ispiv-92	95	26	refers	refer	VERB
ispiv-92	95	27	to	to	ADP
ispiv-92	95	28	the	the	DET
ispiv-92	95	29	filtered	filter	VERB
ispiv-92	95	30	signal	signal	NOUN
ispiv-92	95	31	that	that	PRON
ispiv-92	95	32	needs	need	VERB
ispiv-92	95	33	to	to	PART
ispiv-92	95	34	be	be	AUX
ispiv-92	95	35	solved	solve	VERB
ispiv-92	95	36	for	for	ADP
ispiv-92	95	37	and	and	CCONJ
ispiv-92	95	38	w	w	NOUN
ispiv-92	95	39	is	be	AUX
ispiv-92	95	40	a	a	DET
ispiv-92	95	41	scalar	scalar	ADJ
ispiv-92	95	42	weighting	weighting	NOUN
ispiv-92	95	43	factor	factor	NOUN
ispiv-92	95	44	for	for	ADP
ispiv-92	95	45	the	the	DET
ispiv-92	95	46	identity	identity	NOUN
ispiv-92	95	47	portion	portion	NOUN
ispiv-92	95	48	of	of	ADP
ispiv-92	95	49	the	the	DET
ispiv-92	95	50	equation	equation	NOUN
ispiv-92	95	51	system	system	NOUN
ispiv-92	95	52	.	.	PUNCT
ispiv-92	96	1	the	the	DET
ispiv-92	96	2	lower	low	ADJ
ispiv-92	96	3	part	part	NOUN
ispiv-92	96	4	of	of	ADP
ispiv-92	96	5	the	the	DET
ispiv-92	96	6	equation	equation	NOUN
ispiv-92	96	7	system	system	NOUN
ispiv-92	96	8	sets	set	VERB
ispiv-92	96	9	finite	finite	VERB
ispiv-92	96	10	differences	difference	NOUN
ispiv-92	96	11	of	of	ADP
ispiv-92	96	12	the	the	DET
ispiv-92	96	13	first	first	ADJ
ispiv-92	96	14	order	order	NOUN
ispiv-92	96	15	to	to	ADP
ispiv-92	96	16	zero	zero	NUM
ispiv-92	96	17	.	.	PUNCT
ispiv-92	97	1	higher	high	ADJ
ispiv-92	97	2	order	order	NOUN
ispiv-92	97	3	differences	difference	NOUN
ispiv-92	97	4	can	can	AUX
ispiv-92	97	5	also	also	ADV
ispiv-92	97	6	be	be	AUX
ispiv-92	97	7	used	use	VERB
ispiv-92	97	8	.	.	PUNCT
ispiv-92	98	1	this	this	DET
ispiv-92	98	2	approach	approach	NOUN
ispiv-92	98	3	sidesteps	sidestep	VERB
ispiv-92	98	4	the	the	DET
ispiv-92	98	5	problem	problem	NOUN
ispiv-92	98	6	of	of	ADP
ispiv-92	98	7	missing	miss	VERB
ispiv-92	98	8	samples	sample	NOUN
ispiv-92	98	9	at	at	ADP
ispiv-92	98	10	the	the	DET
ispiv-92	98	11	signal	signal	NOUN
ispiv-92	98	12	’s	’s	PART
ispiv-92	98	13	beginning	beginning	NOUN
ispiv-92	98	14	and	and	CCONJ
ispiv-92	98	15	end	end	VERB
ispiv-92	98	16	and	and	CCONJ
ispiv-92	98	17	is	be	AUX
ispiv-92	98	18	thus	thus	ADV
ispiv-92	98	19	easily	easily	ADV
ispiv-92	98	20	applicable	applicable	ADJ
ispiv-92	98	21	without	without	ADP
ispiv-92	98	22	special	special	ADJ
ispiv-92	98	23	treatment	treatment	NOUN
ispiv-92	98	24	at	at	ADP
ispiv-92	98	25	the	the	DET
ispiv-92	98	26	borders	border	NOUN
ispiv-92	98	27	.	.	PUNCT
ispiv-92	99	1	solving	solve	VERB
ispiv-92	99	2	this	this	DET
ispiv-92	99	3	kind	kind	NOUN
ispiv-92	99	4	of	of	ADP
ispiv-92	99	5	equation	equation	NOUN
ispiv-92	99	6	system	system	NOUN
ispiv-92	99	7	has	have	VERB
ispiv-92	99	8	the	the	DET
ispiv-92	99	9	effect	effect	NOUN
ispiv-92	99	10	of	of	ADP
ispiv-92	99	11	a	a	DET
ispiv-92	99	12	low	low	ADJ
ispiv-92	99	13	-	-	PUNCT
ispiv-92	99	14	pass	pass	NOUN
ispiv-92	99	15	filter	filter	NOUN
ispiv-92	99	16	where	where	SCONJ
ispiv-92	99	17	the	the	DET
ispiv-92	99	18	weight	weight	NOUN
ispiv-92	99	19	w	w	NOUN
ispiv-92	99	20	controls	control	VERB
ispiv-92	99	21	the	the	DET
ispiv-92	99	22	cutoff	cutoff	NOUN
ispiv-92	99	23	frequency	frequency	NOUN
ispiv-92	99	24	and	and	CCONJ
ispiv-92	99	25	the	the	DET
ispiv-92	99	26	finite	finite	ADJ
ispiv-92	99	27	difference	difference	NOUN
ispiv-92	99	28	order	order	NOUN
ispiv-92	99	29	controls	control	VERB
ispiv-92	99	30	the	the	DET
ispiv-92	99	31	steepness	steepness	NOUN
ispiv-92	99	32	of	of	ADP
ispiv-92	99	33	the	the	DET
ispiv-92	99	34	low	low	ADJ
ispiv-92	99	35	-	-	PUNCT
ispiv-92	99	36	pass	pass	NOUN
ispiv-92	99	37	filter	filter	NOUN
ispiv-92	99	38	’s	’s	PART
ispiv-92	99	39	transition	transition	NOUN
ispiv-92	99	40	band	band	NOUN
ispiv-92	99	41	.	.	PUNCT
ispiv-92	100	1	the	the	DET
ispiv-92	100	2	choice	choice	NOUN
ispiv-92	100	3	for	for	ADP
ispiv-92	100	4	w	w	PROPN
ispiv-92	100	5	given	give	VERB
ispiv-92	100	6	a	a	DET
ispiv-92	100	7	finite	finite	ADJ
ispiv-92	100	8	difference	difference	NOUN
ispiv-92	100	9	order	order	NOUN
ispiv-92	100	10	k	k	NOUN
ispiv-92	100	11	and	and	CCONJ
ispiv-92	100	12	a	a	DET
ispiv-92	100	13	normalized	normalize	VERB
ispiv-92	100	14	cutoff	cutoff	NOUN
ispiv-92	100	15	frequency	frequency	NOUN
ispiv-92	100	16	fcuto	fcuto	NOUN
ispiv-92	100	17	f	f	PROPN
ispiv-92	100	18	f	f	PROPN
ispiv-92	100	19	between	between	ADP
ispiv-92	100	20	0	0	NUM
ispiv-92	100	21	and	and	CCONJ
ispiv-92	100	22	1	1	NUM
ispiv-92	100	23	roughly	roughly	ADV
ispiv-92	100	24	follows	follow	VERB
ispiv-92	100	25	the	the	DET
ispiv-92	100	26	following	follow	VERB
ispiv-92	100	27	relation	relation	NOUN
ispiv-92	100	28	:	:	PUNCT
ispiv-92	100	29	w≈	w≈	PROPN
ispiv-92	101	1	(	(	PUNCT
ispiv-92	101	2	π	π	PROPN
ispiv-92	101	3	·	·	PUNCT
ispiv-92	101	4	fcuto	fcuto	NOUN
ispiv-92	101	5	f	f	PROPN
ispiv-92	101	6	f	f	PROPN
ispiv-92	101	7	)	)	PUNCT
ispiv-92	101	8	k	k	NOUN
ispiv-92	101	9	(	(	PUNCT
ispiv-92	101	10	6	6	NUM
ispiv-92	101	11	)	)	PUNCT
ispiv-92	101	12	this	this	DET
ispiv-92	101	13	filtering	filter	VERB
ispiv-92	101	14	approach	approach	NOUN
ispiv-92	101	15	can	can	AUX
ispiv-92	101	16	be	be	AUX
ispiv-92	101	17	modified	modify	VERB
ispiv-92	101	18	so	so	SCONJ
ispiv-92	101	19	that	that	SCONJ
ispiv-92	101	20	instead	instead	ADV
ispiv-92	101	21	of	of	ADP
ispiv-92	101	22	solving	solve	VERB
ispiv-92	101	23	for	for	ADP
ispiv-92	101	24	a	a	DET
ispiv-92	101	25	filtered	filter	VERB
ispiv-92	101	26	signal	signal	NOUN
ispiv-92	101	27	we	we	PRON
ispiv-92	101	28	solve	solve	VERB
ispiv-92	101	29	for	for	ADP
ispiv-92	101	30	scale	scale	NOUN
ispiv-92	101	31	factors	factor	NOUN
ispiv-92	101	32	for	for	ADP
ispiv-92	101	33	a	a	DET
ispiv-92	101	34	set	set	NOUN
ispiv-92	101	35	of	of	ADP
ispiv-92	101	36	smooth	smooth	ADJ
ispiv-92	101	37	and	and	CCONJ
ispiv-92	101	38	compact	compact	ADJ
ispiv-92	101	39	basis	basis	NOUN
ispiv-92	101	40	functions	function	NOUN
ispiv-92	101	41	for	for	ADP
ispiv-92	101	42	the	the	DET
ispiv-92	101	43	purpose	purpose	NOUN
ispiv-92	101	44	of	of	ADP
ispiv-92	101	45	interpolation	interpolation	NOUN
ispiv-92	101	46	.	.	PUNCT
ispiv-92	102	1	with	with	ADP
ispiv-92	102	2	the	the	DET
ispiv-92	102	3	cubic	cubic	ADJ
ispiv-92	102	4	b	b	PROPN
ispiv-92	102	5	-	-	PUNCT
ispiv-92	102	6	spline	spline	NOUN
ispiv-92	102	7	base	base	NOUN
ispiv-92	102	8	function	function	NOUN
ispiv-92	102	9	as	as	ADP
ispiv-92	102	10	basis	basis	NOUN
ispiv-92	102	11	β3(x	β3(x	NUM
ispiv-92	102	12	)	)	PUNCT
ispiv-92	102	13	=	=	PUNCT
ispiv-92	102	14			PUNCT
ispiv-92	102	15	2	2	NUM
ispiv-92	102	16	3	3	NUM
ispiv-92	102	17	−	−	NOUN
ispiv-92	102	18	x2	x2	NOUN
ispiv-92	102	19	(	(	PUNCT
ispiv-92	102	20	1−	1−	NUM
ispiv-92	102	21	1	1	NUM
ispiv-92	102	22	2	2	NUM
ispiv-92	102	23	|x|	|x|	PROPN
ispiv-92	102	24	)	)	PUNCT
ispiv-92	102	25	for	for	ADP
ispiv-92	102	26	0	0	NUM
ispiv-92	102	27	<	<	X
ispiv-92	102	28	=	=	X
ispiv-92	102	29	|x|	|x|	PROPN
ispiv-92	102	30	<	<	X
ispiv-92	102	31	1	1	NUM
ispiv-92	102	32	1	1	NUM
ispiv-92	102	33	6	6	NUM
ispiv-92	102	34	(	(	PUNCT
ispiv-92	102	35	2−|x|	2−|x|	NUM
ispiv-92	102	36	)	)	PUNCT
ispiv-92	102	37	3	3	NUM
ispiv-92	102	38	for	for	ADP
ispiv-92	102	39	1	1	NUM
ispiv-92	102	40	<	<	NOUN
ispiv-92	102	41	=	=	X
ispiv-92	102	42	|x|	|x|	PROPN
ispiv-92	102	43	<	<	X
ispiv-92	102	44	2	2	NUM
ispiv-92	102	45	0	0	NUM
ispiv-92	102	46	for	for	ADP
ispiv-92	102	47	2	2	NUM
ispiv-92	102	48	<	<	NOUN
ispiv-92	102	49	=	=	X
ispiv-92	102	50	|x|	|x|	PROPN
ispiv-92	102	51	(	(	PUNCT
ispiv-92	102	52	7	7	NUM
ispiv-92	102	53	)	)	PUNCT
ispiv-92	102	54	which	which	PRON
ispiv-92	102	55	evaluates	evaluate	VERB
ispiv-92	102	56	to	to	ADP
ispiv-92	102	57	1	1	NUM
ispiv-92	102	58	6	6	NUM
ispiv-92	102	59	,	,	PUNCT
ispiv-92	102	60	4	4	NUM
ispiv-92	102	61	6	6	NUM
ispiv-92	102	62	and	and	CCONJ
ispiv-92	102	63	1	1	NUM
ispiv-92	102	64	6	6	NUM
ispiv-92	102	65	at	at	ADP
ispiv-92	102	66	points	point	NOUN
ispiv-92	102	67	−1	−1	NOUN
ispiv-92	102	68	,	,	PUNCT
ispiv-92	102	69	0	0	NUM
ispiv-92	102	70	and	and	CCONJ
ispiv-92	102	71	1	1	NUM
ispiv-92	102	72	and	and	CCONJ
ispiv-92	102	73	the	the	DET
ispiv-92	102	74	use	use	NOUN
ispiv-92	102	75	of	of	ADP
ispiv-92	102	76	third	third	ADJ
ispiv-92	102	77	order	order	NOUN
ispiv-92	102	78	finite	finite	VERB
ispiv-92	102	79	differences	difference	NOUN
ispiv-92	102	80	of	of	ADP
ispiv-92	102	81	the	the	DET
ispiv-92	102	82	b	b	NOUN
ispiv-92	102	83	-	-	PUNCT
ispiv-92	102	84	spline	spline	NOUN
ispiv-92	102	85	coefficients	coefficient	NOUN
ispiv-92	102	86	which	which	PRON
ispiv-92	102	87	correspond	correspond	VERB
ispiv-92	102	88	to	to	ADP
ispiv-92	102	89	the	the	DET
ispiv-92	102	90	actual	actual	ADJ
ispiv-92	102	91	third	third	ADJ
ispiv-92	102	92	order	order	NOUN
ispiv-92	102	93	derivative	derivative	NOUN
ispiv-92	102	94	at	at	ADP
ispiv-92	102	95	the	the	DET
ispiv-92	102	96	midpoints	midpoint	NOUN
ispiv-92	102	97	of	of	ADP
ispiv-92	102	98	the	the	DET
ispiv-92	102	99	b	b	PROPN
ispiv-92	102	100	-	-	PUNCT
ispiv-92	102	101	spline	spline	NOUN
ispiv-92	102	102	curve	curve	NOUN
ispiv-92	102	103	between	between	ADP
ispiv-92	102	104	two	two	NUM
ispiv-92	102	105	neighboring	neighboring	NOUN
ispiv-92	102	106	knots	knot	NOUN
ispiv-92	102	107	,	,	PUNCT
ispiv-92	102	108	the	the	DET
ispiv-92	102	109	modified	modify	VERB
ispiv-92	102	110	equation	equation	NOUN
ispiv-92	102	111	system	system	NOUN
ispiv-92	102	112	looks	look	VERB
ispiv-92	102	113	as	as	SCONJ
ispiv-92	102	114	follows	follow	VERB
ispiv-92	102	115	:	:	PUNCT
ispiv-92	102	116			NOUN
ispiv-92	102	117	1w	1w	NUM
ispiv-92	102	118	4w	4w	NUM
ispiv-92	102	119	1w	1w	NUM
ispiv-92	102	120	1w	1w	NUM
ispiv-92	102	121	4w	4w	NOUN
ispiv-92	102	122	1w	1w	NUM
ispiv-92	102	123	1w	1w	NUM
ispiv-92	102	124	4w	4w	NOUN
ispiv-92	102	125	1w	1w	NUM
ispiv-92	102	126	.	.	PUNCT
ispiv-92	102	127	.	.	PUNCT
ispiv-92	102	128	.	.	PUNCT
ispiv-92	102	129	.	.	PUNCT
ispiv-92	102	130	.	.	PUNCT
ispiv-92	102	131	.	.	PUNCT
ispiv-92	102	132	.	.	PUNCT
ispiv-92	102	133	.	.	PUNCT
ispiv-92	102	134	.	.	PUNCT
ispiv-92	103	1	1w	1w	NUM
ispiv-92	103	2	4w	4w	NUM
ispiv-92	103	3	1w	1w	NUM
ispiv-92	103	4	1w	1w	NUM
ispiv-92	103	5	4w	4w	NOUN
ispiv-92	103	6	1w	1w	NUM
ispiv-92	103	7	−1	−1	NOUN
ispiv-92	103	8	3	3	NUM
ispiv-92	103	9	−3	−3	PROPN
ispiv-92	103	10	1	1	NUM
ispiv-92	103	11	−1	−1	NOUN
ispiv-92	103	12	3	3	NUM
ispiv-92	103	13	−3	−3	NOUN
ispiv-92	103	14	1	1	NUM
ispiv-92	103	15	−1	−1	NOUN
ispiv-92	103	16	3	3	NUM
ispiv-92	103	17	−3	−3	NOUN
ispiv-92	103	18	1	1	NUM
ispiv-92	103	19	.	.	PUNCT
ispiv-92	103	20	.	.	PUNCT
ispiv-92	103	21	.	.	PUNCT
ispiv-92	103	22	.	.	PUNCT
ispiv-92	103	23	.	.	PUNCT
ispiv-92	103	24	.	.	PUNCT
ispiv-92	103	25	.	.	PUNCT
ispiv-92	103	26	.	.	PUNCT
ispiv-92	103	27	.	.	PUNCT
ispiv-92	103	28	.	.	PUNCT
ispiv-92	103	29	.	.	PUNCT
ispiv-92	103	30	.	.	PUNCT
ispiv-92	104	1	−1	−1	NOUN
ispiv-92	104	2	3	3	NUM
ispiv-92	104	3	−3	−3	NOUN
ispiv-92	104	4	1	1	NUM
ispiv-92	104	5			NOUN
ispiv-92	104	6	c	c	NOUN
ispiv-92	104	7	=	=	SYM
ispiv-92	104	8	(	(	PUNCT
ispiv-92	104	9	6w	6w	NOUN
ispiv-92	104	10	·	·	PUNCT
ispiv-92	104	11	s	s	X
ispiv-92	104	12	0	0	NUM
ispiv-92	104	13	)	)	PUNCT
ispiv-92	104	14	(	(	PUNCT
ispiv-92	104	15	8)	8)	NUM
ispiv-92	104	16	here	here	ADV
ispiv-92	104	17	,	,	PUNCT
ispiv-92	104	18	the	the	DET
ispiv-92	104	19	solution	solution	NOUN
ispiv-92	104	20	c	c	NOUN
ispiv-92	104	21	is	be	AUX
ispiv-92	104	22	a	a	DET
ispiv-92	104	23	set	set	NOUN
ispiv-92	104	24	of	of	ADP
ispiv-92	104	25	scale	scale	NOUN
ispiv-92	104	26	factors	factor	NOUN
ispiv-92	104	27	which	which	PRON
ispiv-92	104	28	control	control	VERB
ispiv-92	104	29	the	the	DET
ispiv-92	104	30	contribution	contribution	NOUN
ispiv-92	104	31	of	of	ADP
ispiv-92	104	32	the	the	DET
ispiv-92	104	33	various	various	ADJ
ispiv-92	104	34	shifted	shift	VERB
ispiv-92	104	35	b	b	NUM
ispiv-92	104	36	-	-	PUNCT
ispiv-92	104	37	spline	spline	NOUN
ispiv-92	104	38	base	base	NOUN
ispiv-92	104	39	functions	function	NOUN
ispiv-92	104	40	to	to	ADP
ispiv-92	104	41	the	the	DET
ispiv-92	104	42	trajectory	trajectory	NOUN
ispiv-92	104	43	.	.	PUNCT
ispiv-92	105	1	given	give	VERB
ispiv-92	105	2	a	a	DET
ispiv-92	105	3	signal	signal	NOUN
ispiv-92	105	4	s	s	NOUN
ispiv-92	105	5	with	with	ADP
ispiv-92	105	6	n	n	ADP
ispiv-92	105	7	samples	sample	NOUN
ispiv-92	105	8	,	,	PUNCT
ispiv-92	105	9	n+2	n+2	PRON
ispiv-92	105	10	scaling	scale	VERB
ispiv-92	105	11	coefficients	coefficient	NOUN
ispiv-92	105	12	will	will	AUX
ispiv-92	105	13	be	be	AUX
ispiv-92	105	14	computed	compute	VERB
ispiv-92	105	15	to	to	PART
ispiv-92	105	16	cover	cover	VERB
ispiv-92	105	17	every	every	DET
ispiv-92	105	18	interval	interval	NOUN
ispiv-92	105	19	with	with	ADP
ispiv-92	105	20	four	four	NUM
ispiv-92	105	21	cubic	cubic	ADJ
ispiv-92	105	22	base	base	NOUN
ispiv-92	105	23	splines	spline	NOUN
ispiv-92	105	24	.	.	PUNCT
ispiv-92	106	1	the	the	DET
ispiv-92	106	2	choice	choice	NOUN
ispiv-92	106	3	of	of	ADP
ispiv-92	106	4	regularizing	regularize	VERB
ispiv-92	106	5	with	with	ADP
ispiv-92	106	6	the	the	DET
ispiv-92	106	7	third	third	ADJ
ispiv-92	106	8	order	order	NOUN
ispiv-92	106	9	derivative	derivative	NOUN
ispiv-92	106	10	is	be	AUX
ispiv-92	106	11	motivated	motivate	VERB
ispiv-92	106	12	by	by	ADP
ispiv-92	106	13	the	the	DET
ispiv-92	106	14	slope	slope	NOUN
ispiv-92	106	15	of	of	ADP
ispiv-92	106	16	estimated	estimate	VERB
ispiv-92	106	17	frequency	frequency	NOUN
ispiv-92	106	18	spectra	spectra	NOUN
ispiv-92	106	19	of	of	ADP
ispiv-92	106	20	position	position	NOUN
ispiv-92	106	21	-	-	PUNCT
ispiv-92	106	22	over	over	ADP
ispiv-92	106	23	-	-	PUNCT
ispiv-92	106	24	time	time	NOUN
ispiv-92	106	25	signals	signal	NOUN
ispiv-92	106	26	in	in	ADP
ispiv-92	106	27	simulations	simulation	NOUN
ispiv-92	106	28	as	as	ADV
ispiv-92	106	29	well	well	ADV
ispiv-92	106	30	as	as	ADP
ispiv-92	106	31	real	real	ADJ
ispiv-92	106	32	stb	stb	NOUN
ispiv-92	106	33	experiments	experiment	NOUN
ispiv-92	106	34	.	.	PUNCT
ispiv-92	107	1	a	a	DET
ispiv-92	107	2	derivative	derivative	ADJ
ispiv-92	107	3	order	order	NOUN
ispiv-92	107	4	of	of	ADP
ispiv-92	107	5	k	k	PROPN
ispiv-92	107	6	will	will	AUX
ispiv-92	107	7	approximate	approximate	VERB
ispiv-92	107	8	the	the	DET
ispiv-92	107	9	response	response	NOUN
ispiv-92	107	10	of	of	ADP
ispiv-92	107	11	the	the	DET
ispiv-92	107	12	ideal	ideal	ADJ
ispiv-92	107	13	wiener	wiener	NOUN
ispiv-92	107	14	filter	filter	NOUN
ispiv-92	107	15	for	for	ADP
ispiv-92	107	16	a	a	DET
ispiv-92	107	17	signal	signal	ADJ
ispiv-92	107	18	slope	slope	NOUN
ispiv-92	107	19	of	of	ADP
ispiv-92	107	20	−2k	−2k	PROPN
ispiv-92	107	21	in	in	ADP
ispiv-92	107	22	a	a	DET
ispiv-92	107	23	log	log	NOUN
ispiv-92	107	24	-	-	PUNCT
ispiv-92	107	25	log	log	NOUN
ispiv-92	107	26	plot	plot	NOUN
ispiv-92	107	27	right	right	ADV
ispiv-92	107	28	before	before	SCONJ
ispiv-92	107	29	the	the	DET
ispiv-92	107	30	power	power	NOUN
ispiv-92	107	31	spectral	spectral	ADJ
ispiv-92	107	32	density	density	PROPN
ispiv-92	107	33	curve	curve	NOUN
ispiv-92	107	34	starts	start	VERB
ispiv-92	107	35	to	to	PART
ispiv-92	107	36	flatten	flatten	VERB
ispiv-92	107	37	.	.	PUNCT
ispiv-92	108	1	using	use	VERB
ispiv-92	108	2	this	this	DET
ispiv-92	108	3	modification	modification	NOUN
ispiv-92	108	4	a	a	DET
ispiv-92	108	5	continuous	continuous	ADJ
ispiv-92	108	6	curve	curve	NOUN
ispiv-92	108	7	is	be	AUX
ispiv-92	108	8	reconstructed	reconstruct	VERB
ispiv-92	108	9	instead	instead	ADV
ispiv-92	108	10	of	of	ADP
ispiv-92	108	11	a	a	DET
ispiv-92	108	12	discrete	discrete	ADJ
ispiv-92	108	13	signal	signal	NOUN
ispiv-92	108	14	.	.	PUNCT
ispiv-92	109	1	thus	thus	ADV
ispiv-92	109	2	,	,	PUNCT
ispiv-92	109	3	the	the	DET
ispiv-92	109	4	curve	curve	NOUN
ispiv-92	109	5	can	can	AUX
ispiv-92	109	6	be	be	AUX
ispiv-92	109	7	evaluated	evaluate	VERB
ispiv-92	109	8	at	at	ADP
ispiv-92	109	9	any	any	DET
ispiv-92	109	10	point	point	NOUN
ispiv-92	109	11	in	in	ADP
ispiv-92	109	12	time	time	NOUN
ispiv-92	109	13	including	include	VERB
ispiv-92	109	14	its	its	PRON
ispiv-92	109	15	temporal	temporal	ADJ
ispiv-92	109	16	derivatives	derivative	NOUN
ispiv-92	109	17	for	for	ADP
ispiv-92	109	18	velocity	velocity	NOUN
ispiv-92	109	19	and	and	CCONJ
ispiv-92	109	20	acceleration	acceleration	NOUN
ispiv-92	109	21	.	.	PUNCT
ispiv-92	110	1	5	5	NUM
ispiv-92	110	2	analysis	analysis	NOUN
ispiv-92	110	3	and	and	CCONJ
ispiv-92	110	4	comparison	comparison	NOUN
ispiv-92	110	5	10	10	NUM
ispiv-92	110	6	-2	-2	NOUN
ispiv-92	110	7	10	10	NUM
ispiv-92	110	8	-1	-1	SYM
ispiv-92	110	9	10	10	NUM
ispiv-92	110	10	0	0	NUM
ispiv-92	110	11	10	10	NUM
ispiv-92	110	12	-4	-4	SYM
ispiv-92	110	13	10	10	NUM
ispiv-92	110	14	-3	-3	SYM
ispiv-92	110	15	10	10	NUM
ispiv-92	110	16	-2	-2	NOUN
ispiv-92	110	17	10	10	NUM
ispiv-92	110	18	-1	-1	SYM
ispiv-92	110	19	10	10	NUM
ispiv-92	110	20	0	0	NUM
ispiv-92	110	21	ideal	ideal	ADJ
ispiv-92	110	22	wiener	wiener	NOUN
ispiv-92	110	23	filter	filter	NOUN
ispiv-92	110	24	savitzky	savitzky	NOUN
ispiv-92	110	25	-	-	PUNCT
ispiv-92	110	26	golay	golay	NOUN
ispiv-92	110	27	,	,	PUNCT
ispiv-92	110	28	n=19	n=19	PROPN
ispiv-92	110	29	,	,	PUNCT
ispiv-92	110	30	k=4	k=4	PROPN
ispiv-92	110	31	savitzky	savitzky	PROPN
ispiv-92	110	32	-	-	PUNCT
ispiv-92	110	33	golay	golay	NOUN
ispiv-92	110	34	,	,	PUNCT
ispiv-92	110	35	n=13	n=13	PROPN
ispiv-92	110	36	,	,	PUNCT
ispiv-92	110	37	k=3	k=3	X
ispiv-92	110	38	trackfit	trackfit	ADJ
ispiv-92	110	39	w=0.213	w=0.213	NOUN
ispiv-92	110	40	figure	figure	NOUN
ispiv-92	110	41	3	3	NUM
ispiv-92	110	42	:	:	PUNCT
ispiv-92	110	43	comparison	comparison	NOUN
ispiv-92	110	44	of	of	ADP
ispiv-92	110	45	ideal	ideal	ADJ
ispiv-92	110	46	filter	filter	NOUN
ispiv-92	110	47	gain	gain	NOUN
ispiv-92	110	48	with	with	ADP
ispiv-92	110	49	savitzky	savitzky	NOUN
ispiv-92	110	50	-	-	PUNCT
ispiv-92	110	51	golay	golay	NOUN
ispiv-92	110	52	(	(	PUNCT
ispiv-92	110	53	window	window	NOUN
ispiv-92	110	54	size	size	NOUN
ispiv-92	110	55	n	n	NOUN
ispiv-92	110	56	and	and	CCONJ
ispiv-92	110	57	polynomial	polynomial	ADJ
ispiv-92	110	58	order	order	NOUN
ispiv-92	110	59	k	k	NOUN
ispiv-92	110	60	)	)	PUNCT
ispiv-92	110	61	filters	filter	NOUN
ispiv-92	110	62	and	and	CCONJ
ispiv-92	110	63	trackfit	trackfit	ADJ
ispiv-92	110	64	(	(	PUNCT
ispiv-92	110	65	cutoff	cutoff	NOUN
ispiv-92	110	66	frequency	frequency	NOUN
ispiv-92	110	67	parameter	parameter	NOUN
ispiv-92	110	68	w	w	PROPN
ispiv-92	110	69	)	)	PUNCT
ispiv-92	110	70	.	.	PUNCT
ispiv-92	111	1	based	base	VERB
ispiv-92	111	2	on	on	ADP
ispiv-92	111	3	the	the	DET
ispiv-92	111	4	assumed	assumed	ADJ
ispiv-92	111	5	ground	ground	NOUN
ispiv-92	111	6	truth	truth	NOUN
ispiv-92	111	7	spectrum	spectrum	NOUN
ispiv-92	111	8	that	that	PRON
ispiv-92	111	9	is	be	AUX
ispiv-92	111	10	the	the	DET
ispiv-92	111	11	sum	sum	NOUN
ispiv-92	111	12	of	of	ADP
ispiv-92	111	13	the	the	DET
ispiv-92	111	14	true	true	ADJ
ispiv-92	111	15	signal	signal	NOUN
ispiv-92	111	16	and	and	CCONJ
ispiv-92	111	17	white	white	ADJ
ispiv-92	111	18	noise	noise	NOUN
ispiv-92	111	19	the	the	DET
ispiv-92	111	20	ideal	ideal	ADJ
ispiv-92	111	21	filter	filter	NOUN
ispiv-92	111	22	transfer	transfer	NOUN
ispiv-92	111	23	can	can	AUX
ispiv-92	111	24	be	be	AUX
ispiv-92	111	25	determined	determine	VERB
ispiv-92	111	26	according	accord	VERB
ispiv-92	111	27	to	to	ADP
ispiv-92	111	28	equation	equation	NOUN
ispiv-92	111	29	1	1	NUM
ispiv-92	111	30	and	and	CCONJ
ispiv-92	111	31	compared	compare	VERB
ispiv-92	111	32	to	to	ADP
ispiv-92	111	33	the	the	DET
ispiv-92	111	34	response	response	NOUN
ispiv-92	111	35	of	of	ADP
ispiv-92	111	36	the	the	DET
ispiv-92	111	37	real	real	ADJ
ispiv-92	111	38	filter	filter	NOUN
ispiv-92	111	39	realizations	realization	NOUN
ispiv-92	111	40	of	of	ADP
ispiv-92	111	41	the	the	DET
ispiv-92	111	42	savitzky	savitzky	NOUN
ispiv-92	111	43	-	-	PUNCT
ispiv-92	111	44	golay	golay	NOUN
ispiv-92	111	45	filter	filter	NOUN
ispiv-92	111	46	and	and	CCONJ
ispiv-92	111	47	trackfit	trackfit	ADJ
ispiv-92	111	48	,	,	PUNCT
ispiv-92	111	49	see	see	VERB
ispiv-92	111	50	figure	figure	NOUN
ispiv-92	111	51	3	3	NUM
ispiv-92	111	52	.	.	PUNCT
ispiv-92	112	1	for	for	ADP
ispiv-92	112	2	the	the	DET
ispiv-92	112	3	savitzky	savitzky	NOUN
ispiv-92	112	4	-	-	PUNCT
ispiv-92	112	5	golay	golay	NOUN
ispiv-92	112	6	filter	filter	NOUN
ispiv-92	112	7	the	the	DET
ispiv-92	112	8	window	window	NOUN
ispiv-92	112	9	lengths	length	NOUN
ispiv-92	112	10	n	n	PRON
ispiv-92	112	11	were	be	AUX
ispiv-92	112	12	selected	select	VERB
ispiv-92	112	13	for	for	ADP
ispiv-92	112	14	polynomial	polynomial	ADJ
ispiv-92	112	15	order	order	NOUN
ispiv-92	112	16	k	k	NOUN
ispiv-92	112	17	=	=	SYM
ispiv-92	112	18	3	3	NUM
ispiv-92	112	19	and	and	CCONJ
ispiv-92	112	20	k	k	NOUN
ispiv-92	113	1	=	=	NOUN
ispiv-92	113	2	4	4	NUM
ispiv-92	113	3	so	so	SCONJ
ispiv-92	113	4	that	that	SCONJ
ispiv-92	113	5	the	the	DET
ispiv-92	113	6	filter	filter	NOUN
ispiv-92	113	7	’s	’s	PART
ispiv-92	113	8	response	response	NOUN
ispiv-92	113	9	would	would	AUX
ispiv-92	113	10	approximate	approximate	VERB
ispiv-92	113	11	the	the	DET
ispiv-92	113	12	ideal	ideal	ADJ
ispiv-92	113	13	filter	filter	NOUN
ispiv-92	113	14	response	response	NOUN
ispiv-92	113	15	.	.	PUNCT
ispiv-92	114	1	but	but	CCONJ
ispiv-92	114	2	these	these	DET
ispiv-92	114	3	filters	filter	NOUN
ispiv-92	114	4	tend	tend	VERB
ispiv-92	114	5	to	to	PART
ispiv-92	114	6	have	have	VERB
ispiv-92	114	7	a	a	DET
ispiv-92	114	8	poor	poor	ADJ
ispiv-92	114	9	suppression	suppression	NOUN
ispiv-92	114	10	of	of	ADP
ispiv-92	114	11	high	high	ADJ
ispiv-92	114	12	frequencies	frequency	NOUN
ispiv-92	114	13	which	which	PRON
ispiv-92	114	14	would	would	AUX
ispiv-92	114	15	retain	retain	VERB
ispiv-92	114	16	more	more	ADJ
ispiv-92	114	17	of	of	ADP
ispiv-92	114	18	the	the	DET
ispiv-92	114	19	measurement	measurement	NOUN
ispiv-92	114	20	noise	noise	NOUN
ispiv-92	114	21	than	than	ADP
ispiv-92	114	22	necessary	necessary	ADJ
ispiv-92	114	23	.	.	PUNCT
ispiv-92	115	1	the	the	DET
ispiv-92	115	2	trackfit	trackfit	ADJ
ispiv-92	115	3	approximates	approximate	VERB
ispiv-92	115	4	the	the	DET
ispiv-92	115	5	ideal	ideal	ADJ
ispiv-92	115	6	wiener	wiener	NOUN
ispiv-92	115	7	filter	filter	NOUN
ispiv-92	115	8	very	very	ADV
ispiv-92	115	9	well	well	ADV
ispiv-92	115	10	for	for	ADP
ispiv-92	115	11	this	this	DET
ispiv-92	115	12	type	type	NOUN
ispiv-92	115	13	of	of	ADP
ispiv-92	115	14	spectrum	spectrum	NOUN
ispiv-92	115	15	.	.	PUNCT
ispiv-92	116	1	it	it	PRON
ispiv-92	116	2	retains	retain	VERB
ispiv-92	116	3	the	the	DET
ispiv-92	116	4	necessary	necessary	ADJ
ispiv-92	116	5	low	low	ADJ
ispiv-92	116	6	frequency	frequency	NOUN
ispiv-92	116	7	information	information	NOUN
ispiv-92	116	8	and	and	CCONJ
ispiv-92	116	9	rejects	reject	VERB
ispiv-92	116	10	the	the	DET
ispiv-92	116	11	high	high	ADJ
ispiv-92	116	12	frequency	frequency	NOUN
ispiv-92	116	13	measurement	measurement	NOUN
ispiv-92	116	14	noise	noise	NOUN
ispiv-92	116	15	just	just	ADV
ispiv-92	116	16	as	as	SCONJ
ispiv-92	116	17	the	the	DET
ispiv-92	116	18	wiener	wiener	NOUN
ispiv-92	116	19	filter	filter	NOUN
ispiv-92	116	20	would	would	AUX
ispiv-92	116	21	.	.	PUNCT
ispiv-92	117	1	6	6	NUM
ispiv-92	117	2	uncertainty	uncertainty	NOUN
ispiv-92	117	3	estimation	estimation	NOUN
ispiv-92	117	4	each	each	DET
ispiv-92	117	5	b	b	NOUN
ispiv-92	117	6	-	-	PUNCT
ispiv-92	117	7	spline	spline	NOUN
ispiv-92	117	8	coefficient	coefficient	NOUN
ispiv-92	117	9	computed	compute	VERB
ispiv-92	117	10	with	with	ADP
ispiv-92	117	11	trackfit	trackfit	NOUN
ispiv-92	117	12	for	for	ADP
ispiv-92	117	13	a	a	DET
ispiv-92	117	14	particle	particle	NOUN
ispiv-92	117	15	trajectory	trajectory	NOUN
ispiv-92	117	16	can	can	AUX
ispiv-92	117	17	be	be	AUX
ispiv-92	117	18	represented	represent	VERB
ispiv-92	117	19	as	as	ADP
ispiv-92	117	20	a	a	DET
ispiv-92	117	21	weighted	weighted	ADJ
ispiv-92	117	22	sum	sum	NOUN
ispiv-92	117	23	of	of	ADP
ispiv-92	117	24	the	the	DET
ispiv-92	117	25	raw	raw	ADJ
ispiv-92	117	26	particle	particle	NOUN
ispiv-92	117	27	location	location	NOUN
ispiv-92	117	28	data	datum	NOUN
ispiv-92	117	29	with	with	ADP
ispiv-92	117	30	the	the	DET
ispiv-92	117	31	help	help	NOUN
ispiv-92	117	32	of	of	ADP
ispiv-92	117	33	the	the	DET
ispiv-92	117	34	equation	equation	NOUN
ispiv-92	117	35	system	system	NOUN
ispiv-92	117	36	’s	’s	PART
ispiv-92	117	37	pseudo	pseudo	NOUN
ispiv-92	117	38	-	-	NOUN
ispiv-92	117	39	inverse	inverse	NOUN
ispiv-92	117	40	.	.	PUNCT
ispiv-92	118	1	in	in	ADP
ispiv-92	118	2	addition	addition	NOUN
ispiv-92	118	3	,	,	PUNCT
ispiv-92	118	4	each	each	DET
ispiv-92	118	5	derived	derive	VERB
ispiv-92	118	6	quantity	quantity	NOUN
ispiv-92	118	7	from	from	ADP
ispiv-92	118	8	the	the	DET
ispiv-92	118	9	b	b	PROPN
ispiv-92	118	10	-	-	PUNCT
ispiv-92	118	11	spline	spline	NOUN
ispiv-92	118	12	curve	curve	NOUN
ispiv-92	118	13	(	(	PUNCT
ispiv-92	118	14	such	such	ADJ
ispiv-92	118	15	as	as	ADP
ispiv-92	118	16	location	location	NOUN
ispiv-92	118	17	,	,	PUNCT
ispiv-92	118	18	velocity	velocity	NOUN
ispiv-92	118	19	or	or	CCONJ
ispiv-92	118	20	acceleration	acceleration	NOUN
ispiv-92	118	21	)	)	PUNCT
ispiv-92	118	22	is	be	AUX
ispiv-92	118	23	also	also	ADV
ispiv-92	118	24	a	a	DET
ispiv-92	118	25	weighted	weight	VERB
ispiv-92	118	26	sum	sum	NOUN
ispiv-92	118	27	of	of	ADP
ispiv-92	118	28	the	the	DET
ispiv-92	118	29	b	b	NOUN
ispiv-92	118	30	-	-	PUNCT
ispiv-92	118	31	spline	spline	NOUN
ispiv-92	118	32	coefficients	coefficient	NOUN
ispiv-92	118	33	.	.	PUNCT
ispiv-92	119	1	the	the	DET
ispiv-92	119	2	concatenation	concatenation	NOUN
ispiv-92	119	3	of	of	ADP
ispiv-92	119	4	two	two	NUM
ispiv-92	119	5	linear	linear	ADJ
ispiv-92	119	6	mappings	mapping	NOUN
ispiv-92	119	7	is	be	AUX
ispiv-92	119	8	itself	itself	PRON
ispiv-92	119	9	linear	linear	ADJ
ispiv-92	119	10	.	.	PUNCT
ispiv-92	120	1	therefore	therefore	ADV
ispiv-92	120	2	,	,	PUNCT
ispiv-92	120	3	any	any	PRON
ispiv-92	120	4	of	of	ADP
ispiv-92	120	5	these	these	DET
ispiv-92	120	6	derived	derive	VERB
ispiv-92	120	7	quantities	quantity	NOUN
ispiv-92	120	8	can	can	AUX
ispiv-92	120	9	be	be	AUX
ispiv-92	120	10	written	write	VERB
ispiv-92	120	11	as	as	ADP
ispiv-92	120	12	a	a	DET
ispiv-92	120	13	weighted	weighted	ADJ
ispiv-92	120	14	sum	sum	NOUN
ispiv-92	120	15	of	of	ADP
ispiv-92	120	16	the	the	DET
ispiv-92	120	17	raw	raw	ADJ
ispiv-92	120	18	unfiltered	unfiltered	ADJ
ispiv-92	120	19	particle	particle	NOUN
ispiv-92	120	20	location	location	NOUN
ispiv-92	120	21	data	datum	NOUN
ispiv-92	120	22	,	,	PUNCT
ispiv-92	120	23	for	for	ADP
ispiv-92	120	24	example	example	NOUN
ispiv-92	120	25	,	,	PUNCT
ispiv-92	120	26	the	the	DET
ispiv-92	120	27	velocity	velocity	NOUN
ispiv-92	120	28	of	of	ADP
ispiv-92	120	29	a	a	DET
ispiv-92	120	30	particular	particular	ADJ
ispiv-92	120	31	particle	particle	NOUN
ispiv-92	120	32	at	at	ADP
ispiv-92	120	33	time	time	NOUN
ispiv-92	120	34	instant	instant	PROPN
ispiv-92	120	35	t	t	NOUN
ispiv-92	120	36	based	base	VERB
ispiv-92	120	37	on	on	ADP
ispiv-92	120	38	the	the	DET
ispiv-92	120	39	noisy	noisy	ADJ
ispiv-92	120	40	particle	particle	NOUN
ispiv-92	120	41	location	location	NOUN
ispiv-92	120	42	samples	sample	NOUN
ispiv-92	120	43	s	s	PART
ispiv-92	120	44	j	j	NOUN
ispiv-92	120	45	:	:	PUNCT
ispiv-92	120	46	v(t	v(t	NUM
ispiv-92	120	47	)	)	PUNCT
ispiv-92	120	48	=	=	PUNCT
ispiv-92	121	1	∑	∑	PUNCT
ispiv-92	121	2	j	j	PROPN
ispiv-92	121	3	α	α	PROPN
ispiv-92	121	4	j(t	j(t	PROPN
ispiv-92	121	5	)	)	PUNCT
ispiv-92	121	6	·	·	PUNCT
ispiv-92	121	7	s	s	PART
ispiv-92	121	8	j	j	X
ispiv-92	121	9	(	(	PUNCT
ispiv-92	121	10	9	9	NUM
ispiv-92	121	11	)	)	PUNCT
ispiv-92	121	12	under	under	ADP
ispiv-92	121	13	the	the	DET
ispiv-92	121	14	assumption	assumption	NOUN
ispiv-92	121	15	of	of	ADP
ispiv-92	121	16	uncorrelated	uncorrelated	ADJ
ispiv-92	121	17	white	white	ADJ
ispiv-92	121	18	measurement	measurement	PROPN
ispiv-92	121	19	noise	noise	NOUN
ispiv-92	121	20	with	with	ADP
ispiv-92	121	21	a	a	DET
ispiv-92	121	22	power	power	NOUN
ispiv-92	121	23	level	level	NOUN
ispiv-92	121	24	σ2	σ2	PROPN
ispiv-92	121	25	le	le	X
ispiv-92	121	26	that	that	PRON
ispiv-92	121	27	can	can	AUX
ispiv-92	121	28	be	be	AUX
ispiv-92	121	29	extracted	extract	VERB
ispiv-92	121	30	from	from	ADP
ispiv-92	121	31	the	the	DET
ispiv-92	121	32	flat	flat	ADJ
ispiv-92	121	33	high	high	ADJ
ispiv-92	121	34	frequency	frequency	NOUN
ispiv-92	121	35	portion	portion	NOUN
ispiv-92	121	36	of	of	ADP
ispiv-92	121	37	the	the	DET
ispiv-92	121	38	power	power	NOUN
ispiv-92	121	39	spectral	spectral	ADJ
ispiv-92	121	40	density	density	NOUN
ispiv-92	121	41	estimates	estimate	NOUN
ispiv-92	121	42	,	,	PUNCT
ispiv-92	121	43	it	it	PRON
ispiv-92	121	44	is	be	AUX
ispiv-92	121	45	possible	possible	ADJ
ispiv-92	121	46	to	to	PART
ispiv-92	121	47	perform	perform	VERB
ispiv-92	121	48	gaussian	gaussian	ADJ
ispiv-92	121	49	error	error	NOUN
ispiv-92	121	50	propagation	propagation	NOUN
ispiv-92	121	51	.	.	PUNCT
ispiv-92	122	1	assuming	assume	VERB
ispiv-92	122	2	the	the	DET
ispiv-92	122	3	variance	variance	NOUN
ispiv-92	122	4	of	of	ADP
ispiv-92	122	5	the	the	DET
ispiv-92	122	6	location	location	NOUN
ispiv-92	122	7	error	error	NOUN
ispiv-92	122	8	in	in	ADP
ispiv-92	122	9	s	s	PROPN
ispiv-92	122	10	j	j	PROPN
ispiv-92	122	11	is	be	AUX
ispiv-92	122	12	estimated	estimate	VERB
ispiv-92	122	13	to	to	PART
ispiv-92	122	14	be	be	AUX
ispiv-92	122	15	σ2	σ2	NOUN
ispiv-92	122	16	le	le	ADP
ispiv-92	122	17	then	then	ADV
ispiv-92	122	18	the	the	DET
ispiv-92	122	19	variance	variance	NOUN
ispiv-92	122	20	of	of	ADP
ispiv-92	122	21	the	the	DET
ispiv-92	122	22	error	error	NOUN
ispiv-92	122	23	of	of	ADP
ispiv-92	122	24	velocity	velocity	NOUN
ispiv-92	122	25	σ2	σ2	PROPN
ispiv-92	122	26	ve	ve	VERB
ispiv-92	122	27	can	can	AUX
ispiv-92	122	28	be	be	AUX
ispiv-92	122	29	written	write	VERB
ispiv-92	122	30	as	as	ADP
ispiv-92	122	31	σ	σ	PROPN
ispiv-92	122	32	2	2	NUM
ispiv-92	122	33	ve(t	ve(t	NOUN
ispiv-92	122	34	)	)	PUNCT
ispiv-92	123	1	=	=	SYM
ispiv-92	123	2	σ	σ	PROPN
ispiv-92	123	3	2	2	NUM
ispiv-92	123	4	le	le	X
ispiv-92	123	5	∑	∑	PROPN
ispiv-92	123	6	j	j	PROPN
ispiv-92	123	7	α	α	PRON
ispiv-92	123	8	2	2	NUM
ispiv-92	123	9	j(t	j(t	PROPN
ispiv-92	123	10	)	)	PUNCT
ispiv-92	123	11	(	(	PUNCT
ispiv-92	123	12	10	10	NUM
ispiv-92	123	13	)	)	PUNCT
ispiv-92	123	14	this	this	PRON
ispiv-92	123	15	gives	give	VERB
ispiv-92	123	16	us	we	PRON
ispiv-92	123	17	uncertainty	uncertainty	NOUN
ispiv-92	123	18	estimates	estimate	NOUN
ispiv-92	123	19	of	of	ADP
ispiv-92	123	20	any	any	DET
ispiv-92	123	21	quantity	quantity	NOUN
ispiv-92	123	22	based	base	VERB
ispiv-92	123	23	on	on	ADP
ispiv-92	123	24	the	the	DET
ispiv-92	123	25	spectral	spectral	ADJ
ispiv-92	123	26	power	power	NOUN
ispiv-92	123	27	density	density	NOUN
ispiv-92	123	28	estimates	estimate	NOUN
ispiv-92	123	29	of	of	ADP
ispiv-92	123	30	the	the	DET
ispiv-92	123	31	measurement	measurement	NOUN
ispiv-92	123	32	data	datum	NOUN
ispiv-92	123	33	and	and	CCONJ
ispiv-92	123	34	the	the	DET
ispiv-92	123	35	noise	noise	NOUN
ispiv-92	123	36	reduction	reduction	NOUN
ispiv-92	123	37	/	/	SYM
ispiv-92	123	38	interpolation	interpolation	NOUN
ispiv-92	123	39	approach	approach	NOUN
ispiv-92	123	40	which	which	PRON
ispiv-92	123	41	effectively	effectively	ADV
ispiv-92	123	42	controls	control	VERB
ispiv-92	123	43	the	the	DET
ispiv-92	123	44	α	α	NOUN
ispiv-92	123	45	scale	scale	NOUN
ispiv-92	123	46	factors	factor	NOUN
ispiv-92	123	47	that	that	PRON
ispiv-92	123	48	weight	weight	NOUN
ispiv-92	123	49	each	each	DET
ispiv-92	123	50	individual	individual	ADJ
ispiv-92	123	51	particle	particle	NOUN
ispiv-92	123	52	location	location	NOUN
ispiv-92	123	53	measurement	measurement	NOUN
ispiv-92	123	54	.	.	PUNCT
ispiv-92	124	1	7	7	NUM
ispiv-92	124	2	summary	summary	NOUN
ispiv-92	124	3	and	and	CCONJ
ispiv-92	124	4	conclusion	conclusion	NOUN
ispiv-92	124	5	in	in	ADP
ispiv-92	124	6	this	this	DET
ispiv-92	124	7	work	work	NOUN
ispiv-92	124	8	we	we	PRON
ispiv-92	124	9	have	have	AUX
ispiv-92	124	10	presented	present	VERB
ispiv-92	124	11	a	a	DET
ispiv-92	124	12	method	method	NOUN
ispiv-92	124	13	to	to	PART
ispiv-92	124	14	perform	perform	VERB
ispiv-92	124	15	spectral	spectral	ADJ
ispiv-92	124	16	analyses	analysis	NOUN
ispiv-92	124	17	on	on	ADP
ispiv-92	124	18	possibly	possibly	ADV
ispiv-92	124	19	short	short	ADJ
ispiv-92	124	20	particle	particle	NOUN
ispiv-92	124	21	trajectories	trajectory	NOUN
ispiv-92	124	22	which	which	PRON
ispiv-92	124	23	is	be	AUX
ispiv-92	124	24	tailored	tailor	VERB
ispiv-92	124	25	to	to	ADP
ispiv-92	124	26	strong	strong	ADJ
ispiv-92	124	27	low	low	ADJ
ispiv-92	124	28	frequency	frequency	NOUN
ispiv-92	124	29	content	content	NOUN
ispiv-92	124	30	and	and	CCONJ
ispiv-92	124	31	fast	fast	ADJ
ispiv-92	124	32	decay	decay	NOUN
ispiv-92	124	33	using	use	VERB
ispiv-92	124	34	a	a	DET
ispiv-92	124	35	compensating	compensating	NOUN
ispiv-92	124	36	prefilter	prefilter	NOUN
ispiv-92	124	37	.	.	PUNCT
ispiv-92	125	1	the	the	DET
ispiv-92	125	2	resulting	result	VERB
ispiv-92	125	3	spectral	spectral	ADJ
ispiv-92	125	4	information	information	NOUN
ispiv-92	125	5	allows	allow	VERB
ispiv-92	125	6	approaching	approach	VERB
ispiv-92	125	7	the	the	DET
ispiv-92	125	8	ideal	ideal	ADJ
ispiv-92	125	9	noise	noise	NOUN
ispiv-92	125	10	reduction	reduction	NOUN
ispiv-92	125	11	filter	filter	NOUN
ispiv-92	125	12	.	.	PUNCT
ispiv-92	126	1	further	far	ADV
ispiv-92	126	2	,	,	PUNCT
ispiv-92	126	3	the	the	DET
ispiv-92	126	4	benefits	benefit	NOUN
ispiv-92	126	5	of	of	ADP
ispiv-92	126	6	trackfit	trackfit	NOUN
ispiv-92	126	7	(	(	PUNCT
ispiv-92	126	8	gesemann	gesemann	NOUN
ispiv-92	126	9	et	et	PROPN
ispiv-92	126	10	al	al	PROPN
ispiv-92	126	11	.	.	PUNCT
ispiv-92	127	1	(	(	PUNCT
ispiv-92	127	2	2016	2016	NUM
ispiv-92	127	3	)	)	PUNCT
ispiv-92	127	4	)	)	PUNCT
ispiv-92	127	5	have	have	AUX
ispiv-92	127	6	been	be	AUX
ispiv-92	127	7	highlighted	highlight	VERB
ispiv-92	127	8	.	.	PUNCT
ispiv-92	128	1	specifically	specifically	ADV
ispiv-92	128	2	,	,	PUNCT
ispiv-92	128	3	it	it	PRON
ispiv-92	128	4	performs	perform	VERB
ispiv-92	128	5	a	a	DET
ispiv-92	128	6	joint	joint	ADJ
ispiv-92	128	7	noise	noise	NOUN
ispiv-92	128	8	reduction	reduction	NOUN
ispiv-92	128	9	approximating	approximate	VERB
ispiv-92	128	10	the	the	DET
ispiv-92	128	11	ideal	ideal	ADJ
ispiv-92	128	12	wiener	wiener	NOUN
ispiv-92	128	13	filter	filter	NOUN
ispiv-92	128	14	with	with	ADP
ispiv-92	128	15	an	an	DET
ispiv-92	128	16	interpolation	interpolation	NOUN
ispiv-92	128	17	that	that	PRON
ispiv-92	128	18	offers	offer	VERB
ispiv-92	128	19	consistent	consistent	ADJ
ispiv-92	128	20	temporal	temporal	ADJ
ispiv-92	128	21	derivatives	derivative	NOUN
ispiv-92	128	22	for	for	ADP
ispiv-92	128	23	velocity	velocity	NOUN
ispiv-92	128	24	and	and	CCONJ
ispiv-92	128	25	acceleration	acceleration	NOUN
ispiv-92	128	26	.	.	PUNCT
ispiv-92	129	1	in	in	ADP
ispiv-92	129	2	addition	addition	NOUN
ispiv-92	129	3	,	,	PUNCT
ispiv-92	129	4	it	it	PRON
ispiv-92	129	5	was	be	AUX
ispiv-92	129	6	shown	show	VERB
ispiv-92	129	7	how	how	SCONJ
ispiv-92	129	8	gaussian	gaussian	ADJ
ispiv-92	129	9	error	error	NOUN
ispiv-92	129	10	propagation	propagation	NOUN
ispiv-92	129	11	can	can	AUX
ispiv-92	129	12	be	be	AUX
ispiv-92	129	13	applied	apply	VERB
ispiv-92	129	14	based	base	VERB
ispiv-92	129	15	on	on	ADP
ispiv-92	129	16	the	the	DET
ispiv-92	129	17	estimated	estimate	VERB
ispiv-92	129	18	level	level	NOUN
ispiv-92	129	19	of	of	ADP
ispiv-92	129	20	the	the	DET
ispiv-92	129	21	measurement	measurement	NOUN
ispiv-92	129	22	noise	noise	NOUN
ispiv-92	129	23	floor	floor	NOUN
ispiv-92	129	24	from	from	ADP
ispiv-92	129	25	the	the	DET
ispiv-92	129	26	spectra	spectra	NOUN
ispiv-92	129	27	and	and	CCONJ
ispiv-92	129	28	the	the	DET
ispiv-92	129	29	filtering	filter	VERB
ispiv-92	129	30	coefficients	coefficient	NOUN
ispiv-92	129	31	α	α	PRON
ispiv-92	129	32	.	.	PUNCT
ispiv-92	130	1	we	we	PRON
ispiv-92	130	2	have	have	AUX
ispiv-92	130	3	applied	apply	VERB
ispiv-92	130	4	these	these	DET
ispiv-92	130	5	methods	method	NOUN
ispiv-92	130	6	in	in	ADP
ispiv-92	130	7	various	various	ADJ
ispiv-92	130	8	experiments	experiment	NOUN
ispiv-92	130	9	as	as	ADV
ispiv-92	130	10	well	well	ADV
ispiv-92	130	11	as	as	ADP
ispiv-92	130	12	both	both	CCONJ
ispiv-92	130	13	the	the	DET
ispiv-92	130	14	first	first	ADJ
ispiv-92	130	15	lpt	lpt	PROPN
ispiv-92	130	16	challenge	challenge	NOUN
ispiv-92	130	17	(	(	PUNCT
ispiv-92	130	18	sciacchitano	sciacchitano	VERB
ispiv-92	130	19	et	et	PROPN
ispiv-92	130	20	al	al	PROPN
ispiv-92	130	21	.	.	PROPN
ispiv-92	131	1	(	(	PUNCT
ispiv-92	131	2	2021b	2021b	NUM
ispiv-92	131	3	)	)	PUNCT
ispiv-92	131	4	)	)	PUNCT
ispiv-92	132	1	and	and	CCONJ
ispiv-92	132	2	the	the	DET
ispiv-92	132	3	first	first	ADJ
ispiv-92	132	4	da	da	PROPN
ispiv-92	132	5	challenge	challenge	NOUN
ispiv-92	132	6	(	(	PUNCT
ispiv-92	132	7	sciacchitano	sciacchitano	VERB
ispiv-92	132	8	et	et	PROPN
ispiv-92	132	9	al	al	PROPN
ispiv-92	132	10	.	.	PROPN
ispiv-92	132	11	(	(	PUNCT
ispiv-92	132	12	2021a	2021a	NUM
ispiv-92	132	13	)	)	PUNCT
ispiv-92	132	14	)	)	PUNCT
ispiv-92	132	15	with	with	ADP
ispiv-92	132	16	good	good	ADJ
ispiv-92	132	17	results	result	NOUN
ispiv-92	132	18	.	.	PUNCT
ispiv-92	133	1	acknowledgements	acknowledgement	VERB
ispiv-92	133	2	the	the	DET
ispiv-92	133	3	project	project	NOUN
ispiv-92	133	4	leading	lead	VERB
ispiv-92	133	5	to	to	ADP
ispiv-92	133	6	this	this	DET
ispiv-92	133	7	contribution	contribution	NOUN
ispiv-92	133	8	has	have	AUX
ispiv-92	133	9	received	receive	VERB
ispiv-92	133	10	funding	funding	NOUN
ispiv-92	133	11	in	in	ADP
ispiv-92	133	12	the	the	DET
ispiv-92	133	13	frame	frame	NOUN
ispiv-92	133	14	of	of	ADP
ispiv-92	133	15	the	the	DET
ispiv-92	133	16	project	project	NOUN
ispiv-92	133	17	homer	homer	NOUN
ispiv-92	133	18	from	from	ADP
ispiv-92	133	19	the	the	DET
ispiv-92	133	20	european	european	PROPN
ispiv-92	133	21	union	union	PROPN
ispiv-92	133	22	’s	’s	PART
ispiv-92	133	23	horizon	horizon	NOUN
ispiv-92	133	24	2020	2020	NUM
ispiv-92	133	25	research	research	NOUN
ispiv-92	133	26	and	and	CCONJ
ispiv-92	133	27	innovation	innovation	NOUN
ispiv-92	133	28	program	program	NOUN
ispiv-92	133	29	under	under	ADP
ispiv-92	133	30	grant	grant	NOUN
ispiv-92	133	31	agreement	agreement	NOUN
ispiv-92	133	32	no	no	INTJ
ispiv-92	133	33	.	.	NOUN
ispiv-92	133	34	769237	769237	NUM
ispiv-92	133	35	.	.	PUNCT
ispiv-92	134	1	references	reference	NOUN
ispiv-92	134	2	gesemann	gesemann	VERB
ispiv-92	134	3	s	s	PROPN
ispiv-92	134	4	,	,	PUNCT
ispiv-92	134	5	huhn	huhn	PROPN
ispiv-92	134	6	f	f	PROPN
ispiv-92	134	7	,	,	PUNCT
ispiv-92	134	8	schanz	schanz	PROPN
ispiv-92	135	1	d	d	NOUN
ispiv-92	135	2	,	,	PUNCT
ispiv-92	135	3	and	and	CCONJ
ispiv-92	135	4	schröder	schröder	VERB
ispiv-92	135	5	a	a	DET
ispiv-92	135	6	(	(	PUNCT
ispiv-92	135	7	2016	2016	NUM
ispiv-92	135	8	)	)	PUNCT
ispiv-92	135	9	from	from	ADP
ispiv-92	135	10	noisy	noisy	ADJ
ispiv-92	135	11	particle	particle	NOUN
ispiv-92	135	12	tracks	track	NOUN
ispiv-92	135	13	to	to	ADP
ispiv-92	135	14	velocity	velocity	NOUN
ispiv-92	135	15	,	,	PUNCT
ispiv-92	135	16	acceleration	acceleration	NOUN
ispiv-92	135	17	and	and	CCONJ
ispiv-92	135	18	pressure	pressure	NOUN
ispiv-92	135	19	fields	field	NOUN
ispiv-92	135	20	using	use	VERB
ispiv-92	135	21	b	b	NOUN
ispiv-92	135	22	-	-	PUNCT
ispiv-92	135	23	splines	spline	NOUN
ispiv-92	135	24	and	and	CCONJ
ispiv-92	135	25	penalties	penalty	NOUN
ispiv-92	135	26	.	.	PUNCT
ispiv-92	136	1	in	in	ADP
ispiv-92	136	2	18th	18th	ADJ
ispiv-92	136	3	international	international	ADJ
ispiv-92	136	4	symposium	symposium	NOUN
ispiv-92	136	5	on	on	ADP
ispiv-92	136	6	applications	application	NOUN
ispiv-92	136	7	of	of	ADP
ispiv-92	136	8	laser	laser	NOUN
ispiv-92	136	9	and	and	CCONJ
ispiv-92	136	10	imaging	imaging	NOUN
ispiv-92	136	11	techniques	technique	NOUN
ispiv-92	136	12	to	to	ADP
ispiv-92	136	13	fluid	fluid	ADJ
ispiv-92	136	14	mechanics	mechanic	NOUN
ispiv-92	136	15	,	,	PUNCT
ispiv-92	136	16	lisbon	lisbon	PROPN
ispiv-92	136	17	,	,	PUNCT
ispiv-92	136	18	portugal	portugal	PROPN
ispiv-92	136	19	.	.	PUNCT
ispiv-92	137	1	pages	page	NOUN
ispiv-92	137	2	4–7	4–7	PROPN
ispiv-92	137	3	savitzky	savitzky	VERB
ispiv-92	137	4	a	a	PRON
ispiv-92	137	5	and	and	CCONJ
ispiv-92	137	6	golay	golay	VERB
ispiv-92	137	7	mje	mje	PROPN
ispiv-92	137	8	(	(	PUNCT
ispiv-92	137	9	1964	1964	NUM
ispiv-92	137	10	)	)	PUNCT
ispiv-92	137	11	smoothing	smoothing	NOUN
ispiv-92	137	12	and	and	CCONJ
ispiv-92	137	13	differentiation	differentiation	NOUN
ispiv-92	137	14	of	of	ADP
ispiv-92	137	15	data	datum	NOUN
ispiv-92	137	16	by	by	ADP
ispiv-92	137	17	simplified	simplified	ADJ
ispiv-92	137	18	least	least	ADJ
ispiv-92	137	19	squares	square	NOUN
ispiv-92	137	20	procedures	procedure	NOUN
ispiv-92	137	21	..	..	PUNCT
ispiv-92	137	22	analytical	analytical	ADJ
ispiv-92	137	23	chemistry	chemistry	NOUN
ispiv-92	137	24	36:1627–1639	36:1627–1639	PROPN
ispiv-92	137	25	sciacchitano	sciacchitano	VERB
ispiv-92	137	26	a	a	DET
ispiv-92	137	27	,	,	PUNCT
ispiv-92	137	28	leclaire	leclaire	ADJ
ispiv-92	137	29	b	b	NOUN
ispiv-92	137	30	,	,	PUNCT
ispiv-92	137	31	and	and	CCONJ
ispiv-92	137	32	schröder	schröder	VERB
ispiv-92	137	33	a	a	DET
ispiv-92	137	34	(	(	PUNCT
ispiv-92	137	35	2021a	2021a	NUM
ispiv-92	137	36	)	)	PUNCT
ispiv-92	137	37	main	main	ADJ
ispiv-92	137	38	results	result	NOUN
ispiv-92	137	39	of	of	ADP
ispiv-92	137	40	the	the	DET
ispiv-92	137	41	first	first	ADJ
ispiv-92	137	42	data	data	NOUN
ispiv-92	137	43	assimilation	assimilation	NOUN
ispiv-92	137	44	challenge	challenge	NOUN
ispiv-92	137	45	.	.	PUNCT
ispiv-92	138	1	in	in	ADP
ispiv-92	138	2	14th	14th	ADJ
ispiv-92	138	3	international	international	ADJ
ispiv-92	138	4	symposium	symposium	NOUN
ispiv-92	138	5	on	on	ADP
ispiv-92	138	6	particle	particle	NOUN
ispiv-92	138	7	image	image	NOUN
ispiv-92	138	8	velocimetry	velocimetry	NOUN
ispiv-92	138	9	sciacchitano	sciacchitano	VERB
ispiv-92	138	10	a	a	DET
ispiv-92	138	11	,	,	PUNCT
ispiv-92	138	12	leclaire	leclaire	ADJ
ispiv-92	138	13	b	b	NOUN
ispiv-92	138	14	,	,	PUNCT
ispiv-92	138	15	and	and	CCONJ
ispiv-92	138	16	schröder	schröder	VERB
ispiv-92	138	17	a	a	DET
ispiv-92	138	18	(	(	PUNCT
ispiv-92	138	19	2021b	2021b	NUM
ispiv-92	138	20	)	)	PUNCT
ispiv-92	138	21	main	main	ADJ
ispiv-92	138	22	results	result	NOUN
ispiv-92	138	23	of	of	ADP
ispiv-92	138	24	the	the	DET
ispiv-92	138	25	first	first	ADJ
ispiv-92	138	26	lagrangian	lagrangian	ADJ
ispiv-92	138	27	particle	particle	NOUN
ispiv-92	138	28	tracking	tracking	NOUN
ispiv-92	138	29	challenge	challenge	NOUN
ispiv-92	138	30	.	.	PUNCT
ispiv-92	139	1	in	in	ADP
ispiv-92	139	2	14th	14th	ADJ
ispiv-92	139	3	international	international	ADJ
ispiv-92	139	4	symposium	symposium	NOUN
ispiv-92	139	5	on	on	ADP
ispiv-92	139	6	particle	particle	NOUN
ispiv-92	139	7	image	image	NOUN
ispiv-92	139	8	velocimetry	velocimetry	NOUN
ispiv-92	139	9	introduction	introduction	NOUN
ispiv-92	139	10	spectral	spectral	ADJ
ispiv-92	139	11	estimation	estimation	NOUN
ispiv-92	139	12	prefilter	prefilter	NOUN
ispiv-92	139	13	spectral	spectral	ADJ
ispiv-92	139	14	estimation	estimation	NOUN
ispiv-92	139	15	via	via	ADP
ispiv-92	139	16	auto	auto	NOUN
ispiv-92	139	17	-	-	PUNCT
ispiv-92	139	18	regressive	regressive	ADJ
ispiv-92	139	19	model	model	NOUN
ispiv-92	139	20	test	test	NOUN
ispiv-92	139	21	and	and	CCONJ
ispiv-92	139	22	comparison	comparison	NOUN
ispiv-92	139	23	of	of	ADP
ispiv-92	139	24	spectral	spectral	ADJ
ispiv-92	139	25	estimation	estimation	NOUN
ispiv-92	139	26	methods	method	NOUN
ispiv-92	139	27	spectral	spectral	PROPN
ispiv-92	139	28	estimation	estimation	NOUN
ispiv-92	139	29	test	test	NOUN
ispiv-92	139	30	on	on	ADP
ispiv-92	139	31	fluid	fluid	ADJ
ispiv-92	139	32	simulation	simulation	NOUN
ispiv-92	139	33	data	datum	NOUN
ispiv-92	139	34	filtering	filter	VERB
ispiv-92	139	35	with	with	ADP
ispiv-92	139	36	trackfit	trackfit	ADJ
ispiv-92	139	37	analysis	analysis	NOUN
ispiv-92	139	38	and	and	CCONJ
ispiv-92	139	39	comparison	comparison	NOUN
ispiv-92	139	40	uncertainty	uncertainty	NOUN
ispiv-92	139	41	estimation	estimation	NOUN
ispiv-92	139	42	summary	summary	NOUN
ispiv-92	139	43	and	and	CCONJ
ispiv-92	139	44	conclusion	conclusion	NOUN