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Stochastic averaging principle for distribution dependent stochastic differential equations

Guangjun Shen, Jie Song, Jiang-lun Wu Orcid Logo

Applied Mathematics Letters, Volume: 125, Start page: 107761

Swansea University Author: Jiang-lun Wu Orcid Logo

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Abstract

Due to the intrinsic link with (kinetic) nonlinear Fokker-Planck equations and many diverse applications, distribution dependent stochastic differential equations have been investigated intensively in recent years. The appearance of the probability distributions (or laws) of the random variables of...

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Published in: Applied Mathematics Letters
ISSN: 0893-9659
Published: Elsevier BV 2022
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa58448
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Abstract: Due to the intrinsic link with (kinetic) nonlinear Fokker-Planck equations and many diverse applications, distribution dependent stochastic differential equations have been investigated intensively in recent years. The appearance of the probability distributions (or laws) of the random variables of solutions in the coefficients is a distinct feature of distribution dependent stochastic differential equations. In this paper, under certain averaging conditions, we establish a stochastic averaging principle for distribution dependent stochastic differential equations.
Keywords: Stochastic averaging principle; distribution dependent stochastic differential equations; Wasserstein distance.
College: Faculty of Science and Engineering
Start Page: 107761