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A method for developing mathematical models of nonlinear non-stationary random processes in the form of stochastic differential equations is considered. Methods for synthesizing such equations for scalar and vector non-Gaussian random processes are presented. Examples of modeling for various probability density distributions are provided. These mathematical models find application in the study of various complex control and information transmission systems affected by random disturbances.
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Glushankov et al. (2024) studied this question.
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