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.

中文翻译：

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分数布朗运动驱动的多尺度分布相关随机微分方程的大偏差原理

在本文中，我们同时关注由分数布朗运动（赫斯特指数\(H>\frac{1}{2}\)）和标准布朗运动驱动的多尺度分布相关随机微分方程。我们的目标是建立多尺度分布相关随机微分方程的大偏差原理。这是通过弱收敛方法完成的，我们的证明很大程度上基于分数阶微积分。