Informatics and Applications
2016, Volume 10, Issue 2, pp 14-23
NORMAL PUGACHEV CONDITIONALLY-OPTIMAL FILTERS AND EXTRAPOLATORS FOR STATE LINEAR STOCHASTIC SYSTEMS
- I. N. Sinitsyn
- E. R. Korepanov
Abstract
The analytical synthesis theory of continuous and discrete sub- and Pugachev conditionally optimal filters and extrapolators for information processing in linear state stochastic systems (StS) is presented. For Gaussian StS, Liptzer and Shiraev performed the first works for filters and extrapolators synthesis. For non-Gaussian StS, the first works belong to Pugachev and Sinitsyn. Stochastic equatuins for state and observation of continuous and discrete StS are given. Algorithms for continuous normal sub- and conditionally optimal filters and extrapolators are presented. The corresponding algorithms for discrete StS are also given. The developed algorithms are the basis of the software tool "StS-Filter, 2016." The results maybe developed for autocorrelated noises and multiplicative noises.
[+] References (7)
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[+] About this article
Title
NORMAL PUGACHEV CONDITIONALLY-OPTIMAL FILTERS AND EXTRAPOLATORS FOR STATE LINEAR STOCHASTIC SYSTEMS
Journal
Informatics and Applications
2016, Volume 10, Issue 2, pp 14-23
Cover Date
2016-05-30
DOI
10.14357/19922264160202
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
Liptser-Shiraev filter (LSF); Liptser-Shiraev conditions; normal approximation method (NAM) for a posteriori density; normal conditionally optimal Pugachev filter (NPF); stochastic systems (StS); state linear StS; statistical linearization method (SLM)
Authors
I. N. Sinitsyn  and E. R. Korepanov
Author Affiliations
Institute of Informatics Problems, Federal Research Center “Computer Sciences and Control” of the Russian
Academy of Sciences, 44-2 Vavilov Str.,Moscow 119333, Russian Federation
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