Informatics and Applications
2026, Volume 20, Issue 2, pp 63-73
FILTERING OF SPECIAL MARKOV JUMP PROCESSES BY DISCRETIZED OBSERVATIONS
- A. V. Borisov
- Yu. N. Kurinov
Abstract
The paper continues a series of studies devoted to the analysis and estimation problems for a class of special Markov jump processes. It addresses the filtering problem for special Markov jump processes based on discretized observations represented by increments of a diffusion process whose drift and diffusion coefficients depend on the state of the signal process. The objective is to determine the conditional distribution of the estimated signal with respect to the available observations. The equations of optimal filtering are derived and a numerical algorithm for their implementation is proposed based on constructing analytical approximations of the corresponding conditional densities. A statement characterizing the approximation accuracy as a function of the approximation order is proven. The performance of the proposed estimates is illustrated by a numerical example.
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[+] About this article
Title
FILTERING OF SPECIAL MARKOV JUMP PROCESSES BY DISCRETIZED OBSERVATIONS
Journal
Informatics and Applications
2026, Volume 20, Issue 2, pp 63-73
Cover Date
2026-10-07
DOI
10.14357/19922264260205
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
special Markovjump process; discretized observations; observation with multiplicative noise; conditional probability density; analytical approximation of filtering estimate
Authors
A. V. Borisov  ,  and Yu. N. Kurinov
Author Affiliations
Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
M. V Lomonosov Moscow State University, 1-52 Leninskie Gory, GSP-1, Moscow 119991, Russian Federation
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