Adaptive Particle Filter with Fixed Empirical Density Quality

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F08%3A00502293" target="_blank" >RIV/49777513:23520/08:00502293 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Adaptive Particle Filter with Fixed Empirical Density Quality
Original language description
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 the quality of an empirical probability density function (pdf) which approximates a target filtering pdf. The quality is measured by inaccuracy (cross-information) between the empirical pdf and the filtering pdf. It is shown that for increasing sample size the inaccuracy converges to the Shannon differential entropy (SDE) of the filtering pdf. The proposed technique adapts the sample size to keep a difference between the inaccuracy and the SDE 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.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BC - Theory and management systems
OECD FORD branch
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Project
<a href="/en/project/1M0572" target="_blank" >1M0572: Data, algorithms, decision making</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2008
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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