一类慢-快随机演化方程平均原理的强收敛速率

IF 1.1 2区经济学 Q3 BUSINESS, FINANCE Finance and Stochastics Pub Date : 2022-07-01 DOI:10.1080/17442508.2022.2093112

Jie Xu, Qiqi Lian, Jicheng Liu

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引用次数: 0

摘要

摘要本文证明了由圆柱形Wiener过程驱动的一般双时间尺度随机演化方程的平均原理具有很强的收敛性。特别地，我们的一般结果可用于处理一类大的拟线性随机偏微分方程，如随机反应扩散方程、随机p-拉普拉斯方程、随机多孔介质方程等。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Strong convergence rate of the averaging principle for a class of slow–fast stochastic evolution equations

ABSTRACT We prove a strong convergence rate of the averaging principle for general two-time-scales stochastic evolution equations driven by cylindrical Wiener processes. In particular, our general result can be used to deal with a large class of quasi-linear stochastic partial differential equations, such as stochastic reaction–diffusion equations, stochastic p-Laplace equations, stochastic porous media equations, and so on.

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来源期刊

Finance and Stochastics 管理科学-数学跨学科应用

CiteScore

2.90

自引率

5.90%

发文量

审稿时长

>12 weeks

期刊介绍： The purpose of Finance and Stochastics is to provide a high standard publication forum for research - in all areas of finance based on stochastic methods - on specific topics in mathematics (in particular probability theory, statistics and stochastic analysis) motivated by the analysis of problems in finance. Finance and Stochastics encompasses - but is not limited to - the following fields: - theory and analysis of financial markets - continuous time finance - derivatives research - insurance in relation to finance - portfolio selection - credit and market risks - term structure models - statistical and empirical financial studies based on advanced stochastic methods - numerical and stochastic solution techniques for problems in finance - intertemporal economics, uncertainty and information in relation to finance.

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