Systems and Means of Informatics
2017, Volume 27, Issue 1, pp 20-45
PARAMETRIC ANALYTICAL MODELING OF WIDE BAND PROCESSES IN STOCHASTIC SYSTEMS WITH UNSOLVED DERIVATIVES
Abstract
Methods of parametric analytical modeling (AMM) of stochastic processes in finite dimensional nonlinear stationary and nonstationary stochastic systems with unsolved derivatives are presented. Such models describe technical systems in control and informatics if one neglects transient processes. For analytical modeling and accuracy and sensitivity analysis, the author developed autocorrelated methods based on normal approximation and statistical linearization (NAM and SLM), orthogonal expansions (OEM), and other parametric methods for one- and multidimensional densities. Special attention is paid to AMM for discrete systems by OEM based on the Poisson distribution. Typical nonlinearities with unsolved derivatives and statistical linearization coefficients are given. Test examples are discussed. Algorithms are the basis of experimental software tools for safety and reliability analysis of technical systems that are being developed by the authors.
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[+] About this article
Title
PARAMETRIC ANALYTICAL MODELING OF WIDE BAND PROCESSES IN STOCHASTIC SYSTEMS WITH UNSOLVED DERIVATIVES
Journal
Systems and Means of Informatics
Volume 27, Issue 1, pp 20-45
Cover Date
2017-03-30
DOI
10.14357/08696527170102
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
accuracy and sensitivity analysis; analytical modeling method; normal approximation method (NAM); one- and multidimensional densities; orthogonal expansions method (OEM); statistical linearization method (SLM); stochastic process (StP); stochastic system (StS); stochastic system with unsolved derivatives
Authors
I. N. Sinitsyn 
Author Affiliations
Institute of Informatics Problems, Federal Research Center "Computer Science
and Control", Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
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