Nonlinear estimation by particle filters and Cramér-Rao bound
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F02%3A00072011" target="_blank" >RIV/49777513:23520/02:00072011 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Nonlinear estimation by particle filters and Cramér-Rao bound
Original language description
A solution of the Bayesian recursive relations by the particle filter approach is treated. The stress is laid on the sample size setting as the main user design problem. The Cramér-Rao bound was chosen as a tool for setting the sample size for the threebasic types of the state estimation, for prediction, filtering and smoothing. The mean square error matrices of particle filter state estimates for different sample sizes and the CR bounds are compared. Quality of the aprticle filter and their computational load are illustrated in a numerical example.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BC - Theory and management systems
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA102%2F01%2F0021" target="_blank" >GA102/01/0021: Nonlinear estimation and change detection for stochastic systems</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2002
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Nonlinear estimation by particle filters and Cramér-Rao bound
ISBN
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ISSN
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e-ISSN
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Number of pages
6
Pages from-to
1
Publisher name
Neuveden
Place of publication
Neuveden
Event location
Neuveden
Event date
Jan 1, 2002
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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