Almost Sure Asymptotical Adaptive Synchronization for Neutral-Type Neural Networks with Stochastic Perturbation and Markovian Switching. (16th April 2014)

• Record Type: Journal Article
• Authors: Zhou, Wuneng; Yang, Xueqing; Yang, Jun; Dai, Anding; Liu, Huashan
• Other Names: Wu Zhengguang Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2014(2014)
• Publication Date: 2014-04-16
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2014/479084
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : The problem of almost sure (a.s.) asymptotic adaptive synchronization for neutral-type neural networks with stochastic perturbation and Markovian switching is researched. Firstly, we proposed a new criterion of a.s. asymptotic stability for a general neutral-type stochastic differential equation which extends the existing results. Secondly, based upon this stability criterion, by making use of Lyapunov functional method and designing an adaptive controller, we obtained a condition of a.s. asymptotic adaptive synchronization for neutral-type neural networks with stochastic perturbation and Markovian switching. The synchronization condition is expressed as linear matrix inequality which can be easily solved by Matlab. Finally, we introduced a numerical example to illustrate the effectiveness of the method and result obtained in this paper.