Delay-interval-dependent passivity analysis of stochastic neural networks with Markovian jumping parameters and time delay in the leakage term

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• 作者：S. Senthilraj^a ; ^{senthilraj106@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; R. Raja^b ; ^{antony.raja67@yahoo.com" class="auth_mail" title="E-mail the corresponding author} ; Quanxin Zhu^c ; ^d ; ^{zqx22@126.com" class="auth_mail" title="E-mail the corresponding author} ; R. Samidurai^a ; ^{samidurair@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Zhangsong Yao^e
• 关键词：Passivity analysis ; Stochastic neural network ; Markovian jumping parameters ; Leakage delay ; Linear matrix inequality
• 刊名：Nonlinear Analysis: Hybrid Systems
• 出版年：2016
• 出版时间：November 2016
• 年：2016
• 卷：22
• 期：Complete
• 页码：262-275
• 全文大小：487 K

文摘

In this paper, the problem of passivity analysis is investigated for a class of stochastic neural networks with Markovian jumping parameters and time delay in the leakage term. The discrete delay is assumed to be time-varying and belongs to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. By constructing appropriate Lyapunov–Krasovskii functionals, and employing Newton–Leibniz formulation and the free weighting matrix method, several delay-dependent criteria for checking the passivity of the addressed neural networks are established in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Two examples are given to show the effectiveness and less conservatism of the proposed criteria.