Systems and Means of Informatics
2024, Volume 34, Issue 4, pp 16-30
DISCRETE CONDITIONALLY-OPTIMAL ESTIMATION IN OBSERVABLE IMPLICIT STOCHASTIC SYSTEMS
Abstract
The paper is devoted to the approximate methods of nonlinear conditionally-optimal (by Pugachev) estimation (filtering, extrapolation, and interpolation) of stochastic processes in discrete implicit stochastic systems (StS) reducible to explicit StS. The methods are based on equivalent linearization of implicit functions. It is supposed that observations do not influence objects and are described by nonlinear equations with noncorrelated and autocorrelated noises. A survey of publications in the field of conditionally-optimal filtering and extrapolation for explicit and implicit StS is given. Two discrete mathematical models of implicit StS and equivalent linearization methods are considered.
For reducible implicit StS, conditionally-optimal filtering and extrapolation basic algorithms are presented. Special attention is paid to the known types of interpolation. Implementation to reduced autoregression equations is presented.
Main conclusions and directions of future investigation are discussed.
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[+] About this article
Title
DISCRETE CONDITIONALLY-OPTIMAL ESTIMATION IN OBSERVABLE IMPLICIT STOCHASTIC SYSTEMS
Journal
Systems and Means of Informatics
Volume 34, Issue 4, pp 16-30
Cover Date
2024-12-10
DOI
10.14357/08696527240402
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
autoregression system; conditionally-optimal extrapolator (COE); conditionally-optimal filter (COF); conditionally-optimal interpolator; discrete filter; observable implicit stochastic systems; stochastic systems (StS)
Authors
I. N. Sinitsyn
Author Affiliations
Federal Research Center "Computer Science and Control", Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
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