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Title: Particle filter with adaptive sample size (English)
Author: Straka, Ondřej
Author: Šimandl, Miroslav
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 47
Issue: 3
Year: 2011
Pages: 385-400
Summary lang: English
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Category: math
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Summary: The paper deals with the particle filter in state estimation of a discrete-time nonlinear non-Gaussian system. The goal of the paper is to design a sample size adaptation technique to guarantee a quality of a filtering estimate produced by the particle filter which is an approximation of the true filtering estimate. The quality is given by a difference between the approximate filtering estimate and the true filtering estimate. The estimate may be a point estimate or a probability density function estimate. The proposed technique adapts the sample size to keep the difference within pre-specified bounds with a pre-specified probability. The particle filter with the proposed sample size adaptation technique is illustrated in a numerical example. (English)
Keyword: stochastic systems
Keyword: nonlinear filtering
Keyword: particle filter
Keyword: sample size
Keyword: adaptation
idZBL: Zbl 1221.93261
idMR: MR2857196
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Date available: 2011-06-23T12:54:23Z
Last updated: 2013-09-22
Stable URL: http://hdl.handle.net/10338.dmlcz/141592
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