Robust passivity analysis for neutral-type neural networks with mixed and leakage delays

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• 作者：R. Samidurai^aAuthor Vitae ; S. Rajavel^aAuthor Vitae ; Quanxin Zhu^bAuthor Vitae ; R. Raja^cAuthor Vitae ; Hongwei Zhou^d ; ^{hwzhou122@163.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Neutral-type neural network ; Passivity ; Lyapunov&ndash ; Krasovskii functional ; Leakage delay ; Convex combination technique
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：29 January 2016
• 年：2016
• 卷：175
• 期：part_PA
• 页码：635-643
• 全文大小：523 K

文摘

This paper investigates the problem of passivity of neutral-type neural networks with mixed and leakage delays. By establishing a suitable augmented Lyapunov functional and combining a new integral inequality with the reciprocally convex combination technique, we obtain some sufficient passivity conditions, which are formulated in terms of linear matrix inequalities (LMIs). Here, some useful information on the neuron activation function ignored in the existing literature is taken into account. Finally, some numerical examples are given to demonstrate the effectiveness of the proposed method.