期刊
PHYSICA D-NONLINEAR PHENOMENA
卷 369, 期 -, 页码 1-17出版社
ELSEVIER
DOI: 10.1016/j.physd.2017.12.009
关键词
Fokker-Planck equation; Stationary measure; Limit measure; Concentration; Stochastic stability; White noise perturbation
资金
- NSFC [11371339, 11431012, 11731003, 11571344, 11271151, 11522104]
- Dalian University of Technology
- NSF [DMS1109201]
- NSERC [1257749]
- University of Alberta
- Jilin University
In this paper, we study limit behaviors of stationary measures of the Fokker-Planck equations associated with a system of ordinary differential equations perturbed by a class of multiplicative noise including additive white noise case. As the noises are vanishing, various results on the invariance and concentration of the limit measures are obtained. In particular, we show that if the noise perturbed systems admit a uniform Lyapunov function, then the stationary measures form a relatively sequentially compact set whose weak*-limits are invariant measures of the unperturbed system concentrated on its global attractor. In the case that the global attractor contains a strong local attractor, we further show that there exists a family of admissible multiplicative noises with respect to which all limit measures are actually concentrated on the local attractor; and on the contrary, in the presence of a strong local repeller in the global attractor, there exists a family of admissible multiplicative noises with respect to which no limit measure can be concentrated on the local repeller. Moreover, we show that if there is a strongly repelling equilibrium in the global attractor, then limit measures with respect to typical families of multiplicative noises are always concentrated away from the equilibrium. As applications of these results, an example of stochastic Hopf bifurcation and an example with non-decomposable omega-limit sets are provided. Our study is closely related to the problem of noise stability of compact invariant sets and invariant measures of the unperturbed system. (C) 2017 Elsevier B.V. All rights reserved.
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