3 years ago

Stochastic averaging for two-time-scale stochastic partial differential equations with fractional Brownian motion

Zhi Li, Litan Yan

Publication date: February 2019

Source: Nonlinear Analysis: Hybrid Systems, Volume 31

Author(s): Zhi Li, Litan Yan


In this paper, we are concerned with a class of stochastic partial differential equations that have a slow component driven by a fractional Brownian motion with Hurst parameter 0<H<12 and a fast component driven by a fast-varying diffusion. We will establish an averaging principle in which the fast-varying diffusion process acts as a “noise” and is averaged out in the limit. The slow process is shown to have a limit in the L2 sense, which is characterized by the solution to a stochastic partial differential equation driven by a fractional Brownian motion with Hurst parameter 0<H<12 whose coefficients are averages of that of the original slow process with respect to the stationary measure of the fast-varying diffusion. In the end, one example is given to illustrate the feasibility and effectiveness of results obtained.

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