Systems and Means of Informatics
2017, Volume 27, Issue 3, pp 23-36
ANALYTICAL MODELING OF NORMAL PROCESSES IN STOCHASTIC SYSTEMS WITH INTEGRAL NONLINEARITIES (II)
Abstract
General methodological and algorithmical support for analytical modeling of normal processes in differential stochastic systems (StS) with probabilistic integral nonlinearities (PIN) and Wiener and Poisson noises is presented.
The support is based on the method of normal approximation (MNA) and the method of statistical linearization (MSL). Probabilistic integral nonlinearities were approximated by power and Hermite series. The MSL and MNA coefficients for PIN described by exponential, gamma, and x2-distributions are presented. The necessary information about the function of the parabolic cylinder is also presented. Two test examples are considered. Some generalizations are mentioned.
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[+] About this article
Title
ANALYTICAL MODELING OF NORMAL PROCESSES IN STOCHASTIC SYSTEMS WITH INTEGRAL NONLINEARITIES (II)
Journal
Systems and Means of Informatics
Volume 27, Issue 3, pp 23-36
Cover Date
2017-09-30
DOI
10.14357/08696527170303
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
analytical modeling; x2-distribution; exponential distribution; gamma-distribution; Hermite polynomial and power expansion; method of normal approximation (MNA); method of statistical linearization (MSL); probabilistic integral nonlinearities (PIN)
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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