Global exponential stability of a class of impulsive recurrent neural networks with proportional delays via fixed point theory

详细信息    查看全文

• 作者：Liqun Zhou ; ^{zhouliqun20000@163.com" class="auth_mail" title="E-mail the corresponding author} ; Yanyan Zhang
• 刊名：Journal of The Franklin Institute
• 出版年：2016
• 出版时间：January 2016
• 年：2016
• 卷：353
• 期：2
• 页码：561-575
• 全文大小：404 K

文摘

In this paper, we study the stability of a class of impulsive recurrent neural networks with proportional delays. Here the proportional delay is a kind of unbounded variable delay, which is different from others delays. By using the fixed point theory and some analysis techniques, the stability of the system is investigated, two novel sufficient conditions are obtained to ensure the existence and uniqueness of a solution and the global exponential stability of the considered system. The results obtained in this paper extend and improve the results in previous literature. An example and its simulations are given to illustrate the effectiveness of the proposed results.