DEVELOPMENT OF METHODOLOGICAL AND SOFTWARE SUPPORT FOR ANALYTICAL MODELING OF STOCHASTIC SYSTEMS WITH ELLIPTIC NONLINEARITIES
Journal Title: Современные информационные технологии и ИТ-образование - Year 2017, Vol 13, Issue 1
Abstract
The article deals with methodical, algorithmic and experimental software developed on the basis of approximate methods of normal approximation and statistical linearization. The software is designed for analytical modeling of normal (Gaussian) processes in differential stochastic systems with elliptic nonlinearities described by Jacobian functions, Weierstrass functions etc. A bank of statistical linearization coefficients is created for typical elliptic nonlinearities. Software tools based on methods of normal approximation are designed in MATLAB-MAPLE. Test example is given.
Authors and Affiliations
Igor Sinitsyn
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