Global stability analysis of a class of delayed cellular neural networks

Global stability analysis of a class of delayed cellular neural networks
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DOI：
10.1016/j.matcom.2005.06.001
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发表时间：
2005-11
期刊：
Math. Comput. Simul.
影响因子：
--
通讯作者：
Chuangxia Huang;Lihong Huang;Zhaohui Yuan
Chuangxia Huang;Lihong Huang;Zhaohui Yuan
中科院分区：
其他
文献类型：
--
作者：
Chuangxia Huang;Lihong Huang;Zhaohui Yuan

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利用Brouwer不动点定理、矩阵理论、重合度延拓定理和不等式分析，进一步研究了一类时滞细胞神经网络（DCNNs）的全局指数稳定性和周期解的存在性.给出了DCNN的全局指数稳定性和周期解存在性的一组充分条件。这些结果推广和改进了以前的出版物。
Employing Brouwer’s fixed point theorem, matrix theory, a continuation theorem of the coincidence degree and inequality analysis, the authors study further global exponential stability and the existence of periodic solutions of a class of cellular neural networks with delays (DCNNs) in this paper. A family of sufficient conditions is given for checking global exponential stability and the existence of periodic solutions of DCNNs. The results extend and improve the earlier publications.