Improved results on passivity analysis of discrete-time stochastic neural networks with time-varying delay  

作　　者：于建江 张侃健 费树岷 

机构地区：[1]School of Information Science and Technology,Yancheng Teachers University [2]School of Automation,Southeast University

出　　处：《中南大学学报（自然科学版）》2009年第S1期63-67,共5页Journal of Central South University:Science and Technology

基　　金：Projects(60874030,60835001,60574006)supported by the National Natural Science Foundation of China;Projects(07KJB510125,08KJD510008)supported by the Natural Science Foundation of Jiangsu Higher Education Institutions of China;Project supported by the Qing Lan Program,Jiangsu Province,China

摘　　要：The problem of passivity analysis for a class of discrete-time stochastic neural networks (DSNNs) with time-varying interval delay was investigated. The delay-dependent sufficient criteria were derived in terms of linear matrix inequalities (LMIs). The results are shown to be generalization of some previous results and are less conservative than the existing works. Meanwhile, the computational complexity of the obtained stability conditions is reduced because less variables are involved. A numerical example is given to show the effectiveness and the benefits of the proposed method.The problem of passivity analysis for a class of discrete-time stochastic neural networks (DSNNs) with time-varying interval delay was investigated. The delay-dependent sufficient criteria were derived in terms of linear matrix inequalities (LMIs). The results are shown to be generalization of some previous results and are less conservative than the existing works. Meanwhile, the computational complexity of the obtained stability conditions is reduced because less variables are involved. A numerical example is given to show the effectiveness and the benefits of the proposed method.

关 键 词：PASSIVITY DISCRETE-TIME stochastic neural networks (DSNNs) INTERVAL delay linear matrix INEQUALITIES (LMIs) 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]