ZČU
Publications
Detail of publication
Citation
: Nonlinear estimation by particle filters and Cramér-Rao bound . Proceedings of the 15th IFAC world congress, p. 79-84, Elsevier , Oxford, 2003.
Abstract
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 three basic types of the state estimation, for filtering, prediction 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 particle filters and their computational load are illustrated in a numerical example.
Detail of publication
| Title: | Nonlinear estimation by particle filters and Cramér-Rao bound |
|---|---|
| Author: | Šimandl, M. ; Straka, O. |
| Language: | English |
| Date of publication: | 21 Jul 2002 |
| Year: | 2003 |
| Type of publication: | Book Chapters |
| Title of journal or book: | Proceedings of the 15th IFAC world congress |
| Page: | 79 - 84 |
| ISBN: | 0-08-044221-8 |
| Publisher: | Elsevier |
| Address: | Oxford |
| Date: | 21 Jul 2002 - 26 Jul 2002 |
Keywords
Monte Carlo methods, Nonlinear filters, Cramér-Rao bound, Mean square error, Nonlinear systems
BibTeX
@INBOOK{SimandlM_2003_Nonlinearestimation,
author = {\v{S}imandl, M. and Straka, O.},
title = {Nonlinear estimation by particle filters and Cram\'{e}r-Rao bound},
year = {2003},
publisher = {Elsevier },
journal = {Proceedings of the 15th IFAC world congress},
address = {Oxford},
pages = {79-84},
ISBN = {0-08-044221-8},
url = {http://www.kky.zcu.cz/en/publications/SimandlM_2003_Nonlinearestimation},
}