Graph-theoretic method on exponential synchronization of stochastic coupled networks with Markovian switching. (February 2015)

• Record Type: Journal Article
• Authors: Zhang, Chunmei; Li, Wenxue; Wang, Ke
• Is Part Of: Nonlinear analysis. Volume 15(2015)
• Page Start: 37
• Page End: 51
• Publication Date: 2015-02
• Subjects: Exponential synchronization -- Stochastic coupled networks -- Cohen–Grossberg neural networks -- Graph theory; Nonlinear functional analysis -- Periodicals; Analyse fonctionnelle non linéaire -- Périodiques; Nonlinear functional analysis; Periodicals; 515.7248
• DOI: 10.1016/j.nahs.2014.07.003
• Languages: English
• ISSNs: 1751-570X

Abstract

Abstract: In this paper, the issue of exponential synchronization for a class of stochastic coupled networks with Markovian switching is investigated. Based on some results in graph theory, Lyapunov stability theory and state feedback control technique, several sufficient criteria have been derived to ensure the p th moment exponential stability and almost sure exponential stability for the error network. That is, under these sufficient criteria, drive–response coupled networks can be p th moment exponentially synchronized and almost surely exponentially synchronized, respectively. Finally, stochastic Cohen–Grossberg neural networks with Markovian switching is employed to illustrate our feasible results. Highlights: Drive–response concept and general feedback controller are used. White noise and color noise are considered in the response network. A new approach combining Lyapunov method and some graph theory is presented. Moment and almost sure exponential synchronization criteria are obtained. Stochastic Cohen–Grossberg neural networks with Markovian switching are studied.