Informatics and Applications
2024, Volume 18, Issue 4, pp 2-9
CONDITIONALLY OPTIMAL FILTERING AND EXTRAPOLATION METHODS FOR OBSERVABLE IMPLICIT STOCHASTIC SYSTEMS
Abstract
The paper is devoted to the development of Pugachev’s conditionally optimal filtering and extrapolation
methods for implicit stochastic systems (StS) reducible to explicit continuous and discrete StS. A special review
in the field of suboptimal and conditionally optimal filtering and extrapolation for continuous and discrete StS
with unsolved derivatives (differences) is given.Mathematical models of implicit continuous and discrete Gaussian
and non-Gaussian StS reducible to explicit StS are presented. It is supposed that observations do not influence
implicit objects of observation and are described by explicit differential (difference) equations. Basic methods
for conditionally optimal filtering and extrapolation in implicit StS reducible to explicit StS at Gaussian and
non-Gaussian noises are developed. Three examples are discussed. Some generalizations are given.
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[+] About this article
Title
CONDITIONALLY OPTIMAL FILTERING AND EXTRAPOLATION METHODS FOR OBSERVABLE IMPLICIT STOCHASTIC SYSTEMS
Journal
Informatics and Applications
2024, Volume 18, Issue 4, pp 2-9
Cover Date
2024-12-26
DOI
10.14357/19922264240401
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
conditionally optimal extrapolation; conditionally optimal filtering; implicit stochastic systems; explicit stochastic systems
Authors
I. N. Sinitsyn 
Author Affiliations
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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