On the periodic dynamics of memristor-based neural networks with leakage and time-varying delays

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• 作者：Ping Jiang^a ; ^b ; ^cAuthor Vitae ; Zhigang Zeng^a ; ^c ; ^{zgzeng@mail.hust.edu.cn}Author Vitae ; Jiejie Chen^dAuthor Vitae
• 关键词：Memristor-based neural networks ; Leakage delays ; Time-varying delays ; Periodic solution ; Global exponential stability
• 刊名：Neurocomputing
• 出版年：2017
• 出版时间：5 January 2017
• 年：2017
• 卷：219
• 期：Complete
• 页码：163-173
• 全文大小：877 K
• 卷排序：219

文摘

In this paper, the periodic dynamics have been studied for a general kind of memristor-based neural networks with leakage and time-varying delays. Some new sufficient conditions have been derived ensuring that the existence, uniqueness and globally exponential stability of the periodic solution for the neural network by using differential inclusions theory, the topological degree theory in set-valued analysis and Lyapunov function technique and so on. As a special case, we have shown that the existence, uniqueness and global exponential stability of equilibrium point for the autonomous neural networks with leakage delays.