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Informatika i Ee Primeneniya [Informatics and its Applications], 2017, Volume 11, Issue 1, Pages 11–19
DOI: https://doi.org/10.14357/19922264170102 (Mi ia456) 		 
This article is cited in 2 scientific papers (total in 2 papers)

Classification by continuous-time observations in multiplicative noise I: formulae for Bayesian estimate

A. V. Borisov

Institute of Informatics Problems, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
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DOI: https://doi.org/10.14357/19922264170102
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.
Keywords: Bayesian estimate; optimal filtering; stochastic differential system; random jump process; multiplicative noise.
Funding agency Grant number
Russian Foundation for Basic Research 16-07-00677_а
15-37-20611_мол_а_вед
The work was supported in part by the Russian Foundation for Basic Research (projects Nos. 15-37-20611 and 16-07-00677).
Received: 05.12.2016
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: A. V. Borisov, “Classification by continuous-time observations in multiplicative noise I: formulae for Bayesian estimate”, Inform. Primen., 11:1 (2017), 11–19
Citation in format AMSBIB
\Bibitem{Bor17}
\by A.~V.~Borisov
\paper Classification by continuous-time observations in multiplicative noise~I: formulae for Bayesian estimate
\jour Inform. Primen.
\yr 2017
\vol 11
\issue 1
\pages 11--19
\mathnet{http://mi.mathnet.ru/ia456}
\crossref{https://doi.org/10.14357/19922264170102}
\elib{https://elibrary.ru/item.asp?id=29159452}
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    		Информатика и её применения
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