Moderate Deviations for Two-Time Scale Systems with Mixed Fractional Brownian Motion

IF 1.6 2区 数学 Q2 MATHEMATICS, APPLIED
Xiaoyu Yang, Yuzuru Inahama, Yong Xu
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引用次数: 0

Abstract

This work focuses on moderate deviations for two-time scale systems with mixed fractional Brownian motion. Our proof uses the weak convergence method which is based on the variational representation formula for mixed fractional Brownian motion. Throughout this paper, the Hurst parameter of fractional Brownian motion is larger than 1/2 and the integral along the fractional Brownian motion is understood as the generalized Riemann-Stieltjes integral. First, we consider single-time scale systems with fractional Brownian motion. The key of our proof is showing the weak convergence of the controlled system. Next, we extend our method to show moderate deviations for two-time scale systems. To this goal, we combine the Khasminskii-type averaging principle and the weak convergence approach.

具有混合分数布朗运动的两时间尺度系统的适度偏差
这项工作的重点是研究具有混合分数布朗运动的双时标系统的适度偏差。我们的证明使用了弱收敛方法,该方法基于混合分数布朗运动的变分表示公式。在本文中,分式布朗运动的赫斯特参数大于 1/2 ,沿分式布朗运动的积分被理解为广义黎曼-斯蒂尔杰斯积分。首先,我们考虑具有分数布朗运动的单时标系统。我们证明的关键是显示受控系统的弱收敛性。接下来,我们扩展我们的方法,以显示双时间尺度系统的适度偏差。为此,我们结合了哈斯明斯基式平均原理和弱收敛方法。
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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来源期刊
CiteScore
3.30
自引率
5.60%
发文量
103
审稿时长
>12 weeks
期刊介绍: The Applied Mathematics and Optimization Journal covers a broad range of mathematical methods in particular those that bridge with optimization and have some connection with applications. Core topics include calculus of variations, partial differential equations, stochastic control, optimization of deterministic or stochastic systems in discrete or continuous time, homogenization, control theory, mean field games, dynamic games and optimal transport. Algorithmic, data analytic, machine learning and numerical methods which support the modeling and analysis of optimization problems are encouraged. Of great interest are papers which show some novel idea in either the theory or model which include some connection with potential applications in science and engineering.
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