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JOURNALS // Informatika i Ee Primeneniya [Informatics and its Applications] // Archive

Inform. Primen., 2014 Volume 8, Issue 3, Pages 12–18 (Mi ia322)

This article is cited in 13 papers

Analytical modeling of normal processes in stochastic systems with complex nonlinearities

I. N. Sinitsyn, V. I. Sinitsyn

Institute of Informatics Problems, Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation

Abstract: Differential stochastic systems (DStS) with Wiener and Poisson noises and complex finite, differential, and integral nonlinearities and hereditary StS reducible to DStS are considered. Equations and algorithms of analytical modeling based on the normal approximation method (NAM) and the statistical linearization method (SLM) are given. The case of complex continuous and discontinuous nonlinearities of scalar and vector arguments is considered. Special attention is paid to NAM (SLM) typical integrals for finite rational and irrational nonlinear and integral scalar and vector nonlinear functions. The general case of integral nonlinearities reducible to linear is considered. Test examples are given.

Keywords: analytical modeling; complex finite differential and integral nonlinearities; complex irrational nonlinerarites differential stochastic system with Wiener and Poisson noises; method of normal approximation; method of statistical linearization; hereditary stochastic systems reducible to differential.

Received: 05.05.2014

DOI: 10.14375/19922264140302



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