Stability Analysis of Impulsive Stochastic Reaction-Diffusion Cellular Neural Network with Distributed Delay via Fixed Point Theory. (25th September 2017)

• Record Type: Journal Article
• Authors: Rao, Ruofeng; Zhong, Shouming
• Other Names: Yang Chenguang Academic Editor.
• Is Part Of: Complexity. Volume 2017(2017)
• Publication Date: 2017-09-25
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2017/6292597
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : This paper investigates the stochastically exponential stability of reaction-diffusion impulsive stochastic cellular neural networks (CNN). The reaction-diffusion pulse stochastic system model characterizes the complexity of practical engineering and brings about mathematical difficulties, too. However, the difficulties have been overcome by constructing a new contraction mapping and an appropriate distance on a product space which is guaranteed to be a complete space. This is the first time to employ the fixed point theorem to derive the stability criterion of reaction-diffusion impulsive stochastic CNN with distributed time delays. Finally, an example is provided to illustrate the effectiveness of the proposed methods.