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Kernel density estimates in particle filter

SYSNO ASEP	0442499
Document Type	V - Research Report
R&D Document Type	The record was not marked in the RIV
Title	Kernel density estimates in particle filter
Author(s)	Coufal, David (UIVT-O)_{RID, SAI, ORCID}
Issue data	Cornell University, 2015
Series	arXiv.org e-Print archive
Series number	arXiv:1402.3466 [stat.CO]
Number of pages	37 s.
Language	eng - English
Country	US - United States
Keywords	particle filter ; kernel methods ; Fourier transform
Subject RIV	BB - Applied Statistics, Operational Research
R&D Projects	LD13002 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
Institutional support	UIVT-O - RVO:67985807
Annotation	The paper deals with kernel density estimates of filtering densities in the particle filter. The convergence of the estimates is investigated by means of Fourier analysis. It is shown that the estimates converge to the theoretical filtering densities in the mean integrated squared error under a certain assumption on the Sobolev character of the filtering densities. A sufficient condition is presented for the persistence of this Sobolev char- acter over time. Both results are extended to partial derivatives of the estimates and filtering densities.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2015

Number of the records: 1