Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/141731
Title: Approximations in Mean Square Analysis of Stochastically Forced Equilibria for Nonlinear Dynamical Systems
Authors: Bashkirtseva, I.
Issue Date: 2024
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Citation: Bashkirtseva, I. (2024). Approximations in Mean Square Analysis of Stochastically Forced Equilibria for Nonlinear Dynamical Systems. Mathematics, 12(14), [2199]. https://doi.org/10.3390/math12142199
Abstract: Motivated by important applications to the analysis of complex noise-induced phenomena, we consider a problem of the constructive description of randomly forced equilibria for nonlinear systems with multiplicative noise. Using the apparatus of the first approximation systems, we construct an approximation of mean square deviations that explicitly takes into account the presence of multiplicative noises, depending on the current system state. A spectral criterion of existence and exponential stability of the stationary second moments for the solution of the first approximation system is presented. For mean square deviation, we derive an expansion in powers of the small parameter of noise intensity. Based on this theory, we derive a new, more accurate approximation of mean square deviations in a general nonlinear system with multiplicative noises. This approximation is compared with the widely used approximation based on the stochastic sensitivity technique. The general mathematical results are illustrated with examples of the model of climate dynamics and the van der Pol oscillator with hard excitement. © 2024 by the author.
Keywords: APPROXIMATIONS
DISPERSION
MULTIPLICATIVE NOISE
SECOND MOMENTS
STOCHASTIC EQUILIBRIA
URI: http://elar.urfu.ru/handle/10995/141731
Access: info:eu-repo/semantics/openAccess
cc-by
SCOPUS ID: 85199913396
WOS ID: 001277067200001
PURE ID: 61566411
ISSN: 2227-7390
DOI: 10.3390/math12142199
Sponsorship: Russian Science Foundation, RSF, (N 24-11-00097)
This work was supported by the Russian Science Foundation (N 24-11-00097).
RSCF project card: N 24-11-00097)
This work was supported by the Russian Science Foundation (N 24-11-00097).
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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