Mixed slow-fast stochastic differential equations: Averaging principle result

IF 2.9 2区 数学 Q1 MATHEMATICS Fractional Calculus and Applied Analysis Pub Date : 2025-01-17 DOI:10.1007/s13540-024-00368-z
Shitao Liu
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引用次数: 0

Abstract

This paper investigates stochastic averaging principle for a class of mixed slow-fast stochastic differential equations driven simultaneously by a multidimensional standard Brownian motion and a multidimensional fractional Brownian motion with Hurst parameter \(1/2<H<1\). The stochastic averaging principle shows that the slow component strongly converges to the solution of the corresponding averaged equations under a weaker condition than the Lipschitz one.

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混合慢快随机微分方程:平均原理结果
研究了一类由多维标准布朗运动和具有Hurst参数\(1/2<H<1\)的多维分数布朗运动同时驱动的慢速混合随机微分方程的随机平均原理。随机平均原理表明,在较弱的条件下,慢分量强收敛于相应平均方程的解。
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来源期刊
Fractional Calculus and Applied Analysis
Fractional Calculus and Applied Analysis MATHEMATICS, APPLIED-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
CiteScore
4.70
自引率
16.70%
发文量
101
期刊介绍: Fractional Calculus and Applied Analysis (FCAA, abbreviated in the World databases as Fract. Calc. Appl. Anal. or FRACT CALC APPL ANAL) is a specialized international journal for theory and applications of an important branch of Mathematical Analysis (Calculus) where differentiations and integrations can be of arbitrary non-integer order. The high standards of its contents are guaranteed by the prominent members of Editorial Board and the expertise of invited external reviewers, and proven by the recently achieved high values of impact factor (JIF) and impact rang (SJR), launching the journal to top places of the ranking lists of Thomson Reuters and Scopus.
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