DocumentCode
2231489
Title
Comparison of resampling schemes for particle filtering
Author
Douc, R. ; Cappe, Olivier
Author_Institution
Ecole Polytech., Palaiseau, France
fYear
2005
fDate
15-17 Sept. 2005
Firstpage
64
Lastpage
69
Abstract
This contribution is devoted to the comparison of various resampling approaches that have been proposed in the literature on particle filtering. It is first shown using simple arguments that the so-called residual and stratified methods do yield an improvement over the basic multinomial resampling approach. A simple counter-example showing that this property does not hold true for systematic resampling is given. Finally, some results on the large-sample behavior of the simple bootstrap filter algorithm are given. In particular, a central limit theorem is established for the case where resampling is performed using the residual approach.
Keywords
Monte Carlo methods; particle filtering (numerical methods); signal sampling; bootstrap filter algorithm; multinomial resampling approach; particle filtering; resampling schemes; residual methods; sequential Monte Carlo methods; stratified methods; Computational modeling; Density functional theory; Filtering; Filters; Image processing; Monte Carlo methods; Signal processing; Signal processing algorithms; Sliding mode control; State estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing and Analysis, 2005. ISPA 2005. Proceedings of the 4th International Symposium on
ISSN
1845-5921
Print_ISBN
953-184-089-X
Type
conf
DOI
10.1109/ISPA.2005.195385
Filename
1521264
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