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

  • Guangjun Shen,
  • Huan Zhou,
  • Jiang-Lun Wu

摘要

In this paper, we are concerned with multi-scale distribution-dependent stochastic differential equations driven by fractional Brownian motion (with Hurst index \(H>\frac{1}{2}\) H > 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.