Stability analysis of reaction-diffusion uncertain memristive neural networks with time-varying delays and leakage term

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• 作者：Ruoxia Li ^{ruoxiali1227@163.com" class="auth_mail" title="E-mail the corresponding author} ; Jinde Cao ; ^{jdcao@seu.edu.cn" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Memristor ; Asymptotic stability ; Reaction-diffusion terms ; Leakage delay
• 刊名：Applied Mathematics and Computation
• 出版年：2016
• 出版时间：31 March 2016
• 年：2016
• 卷：278
• 期：Complete
• 页码：54-69
• 全文大小：840 K

文摘

In this paper, the stability problem is investigated for a class of reaction-diffusion uncertain memristive neural networks with time-varying delays and leakage term. To investigate the dynamic behavior of the memristive system, we turn to the qualitative analysis of a relevant differential inclusion under the framework of Filippov’s solution, which is easier to handle. By using Lyapunov stability theory, Jensen integral inequality, Schur complement Lemma, free-weighting matrix approach together with the linear matrix inequality (LMI) approach, the sufficient conditions are derived to ensure the stability of the considered systems. The easy-to-test stability criteria established in this paper depend on the leakage delay as well as the reaction-diffusion terms, which is more reasonable. Moreover, the existing stability criteria can be treated as a special case of this paper. Finally, two numerical examples are exploited to show the effectiveness of the derived LMI-based stability conditions.