Existence and global exponential stability of anti-periodic solutions for competitive neural networks with delays in the leakage terms on time scales
详细信息 查看全文
- 作者：Yang Liu czliuyanzi@yahoo.com" class="auth_mailAuthor Vitae ; Yongqing Yang ; yyq640613@gmail.com" class="auth_mailAuthor Vitae ; Tian LiangAuthor Vitae ; Li LiAuthor Vitae
- 关键词：Competitive neural networks ; Anti-periodic solution ; Coincidence degree ; Stability ; Leakage terms ; Time scales
- 刊名：Neurocomputing
- 出版年：10 June, 2014
- 年：2014
- 卷：133
- 期：Complete
- 页码：471-482
- 全文大小：757 K
文摘
In this paper, the existence and the global exponential stability of anti-periodic solution for competitive neural networks with delays in the leakage terms are investigated on time scales which unifies the continuous-time and the discrete-time competitive neural networks under the same framework. Firstly, the existence of anti-periodic solution is discussed by using the method of coincidence degree and M-matrices. Then some sufficient conditions are obtained to guarantee the global exponential stability of anti-periodic solution for such neural networks. The obtained results are new and improve some earlier publications. Finally, two examples are given to illustrate the effectiveness of the theoretical results.