Informatics and Applications
2022, Volume 16, Issue 1, pp 3238
NORMALIZATION OF SYSTEMS WITH STOCHASTICALLY UNSOLVED DERIVATIVES
Abstract
For a system with stochastically unsolved derivatives, two approaches for reduction of such systems to deterministic systems are developed. The first approach is based on equations for mathematical expectations and covariance characteristics. The second approach considers equations for mathematical expectations and coordinate functions for canonical expansions. The theory of normal stochastic systems is the basis of the developed approaches. An illustrative example is given. Applications to estimation, identification, and calibration problems are considered. Some generalizations are mentioned.
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[+] About this article
Title
NORMALIZATION OF SYSTEMS WITH STOCHASTICALLY UNSOLVED DERIVATIVES
Journal
Informatics and Applications
2022, Volume 16, Issue 1, pp 3238
Cover Date
20220330
DOI
10.14357/19922264220105
Print ISSN
19922264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
canonical expansion (CE); methods of analytical modeling (VFV); normalization by Pugachev; stochastic processes (StP); stochastic systems (StS); stochastic function system with stochastically unsolved derivatives
Authors
I. N. Sinitsyn
Author Affiliations
Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 442 Vavilov Str., Moscow 119333, Russian Federation
