分数布朗运动驱动的多尺度分布依赖性随机微分方程的大偏差原理

IF 1.1 3区数学 Q1 MATHEMATICS

Journal of Evolution Equations Pub Date : 2024-04-02 DOI:10.1007/s00028-024-00960-z

Guangjun Shen, Huan Zhou, Jiang-Lun Wu

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引用次数: 0

摘要

在本文中，我们关注的是由分数布朗运动（Hurst index （H>\frac{1}{2}\）和标准布朗运动同时驱动的多尺度分布依赖随机微分方程。我们的目标是建立多尺度分布依赖随机微分方程的大偏差原理。这是通过弱收敛方法实现的，我们的证明主要基于分数微积分。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Large deviation principle for multi-scale distribution-dependent stochastic differential equations driven by fractional Brownian motions

In this paper, we are concerned with multi-scale distribution-dependent stochastic differential equations driven by fractional Brownian motion (with Hurst index \(H>\frac{1}{2}\)) and standard Brownian motion, simultaneously. Our aim is to establish a large deviation principle for the multi-scale distribution-dependent stochastic differential equations. This is done via the weak convergence approach and our proof is based heavily on the fractional calculus.

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来源期刊

Journal of Evolution Equations 数学-数学

CiteScore

2.30

自引率

7.10%

发文量

审稿时长

>12 weeks

期刊介绍： The Journal of Evolution Equations (JEE) publishes high-quality, peer-reviewed papers on equations dealing with time dependent systems and ranging from abstract theory to concrete applications. Research articles should contain new and important results. Survey articles on recent developments are also considered as important contributions to the field. Particular topics covered by the journal are: Linear and Nonlinear Semigroups Parabolic and Hyperbolic Partial Differential Equations Reaction Diffusion Equations Deterministic and Stochastic Control Systems Transport and Population Equations Volterra Equations Delay Equations Stochastic Processes and Dirichlet Forms Maximal Regularity and Functional Calculi Asymptotics and Qualitative Theory of Linear and Nonlinear Evolution Equations Evolution Equations in Mathematical Physics Elliptic Operators