Informatics and Applications
2017, Volume 11, Issue 1, pp 11-19
CLASSIFICATION BY CONTINUOUS-TIME OBSERVATIONS IN MULTIPLICATIVE NOISE I: FORMULAE FOR BAYESIAN ESTIMATE
Abstract
The two-part paper is devoted to the estimation of a finite-state random vector given the continuous-time noised observations. The key feature is that the observation noise intensity is a function of the estimated vector that makes useless the known results in the optimal filtering. The estimate is obtained both in the explicit integral form and as a solution to a stochastic differential system with some jump processes in the right-hand side.
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[+] About this article
Title
CLASSIFICATION BY CONTINUOUS-TIME OBSERVATIONS IN MULTIPLICATIVE NOISE I: FORMULAE FOR BAYESIAN ESTIMATE
Journal
Informatics and Applications
2017, Volume 11, Issue 1, pp 11-19
Cover Date
2017-02-30
DOI
10.14357/19922264170102
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
Bayesian estimate; optimal filtering; stochastic differential system; random jump process; multiplicative noise
Authors
A. V. Borisov 
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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