Global exponential stability and periodicity of cellular neural networks with variable delays

被引:52
作者
Zhao, HY [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Dept Math, Nanjing 210016, Peoples R China
[2] Xinjiang Normal Univ, Dept Math, Urumqi 830054, Peoples R China
基金
中国国家自然科学基金;
关键词
global exponential stability; periodic solution; cellular neural network; differential inequality; fixed point;
D O I
10.1016/j.physleta.2004.12.001
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The Letter presents sufficient conditions ensuring the global exponential stability and existence of the periodic solution for cellular neural networks with variable delays. The results allow for the consideration of all unbounded neuron activation functions (but not necessarily surjective), in particular, can analyze the exponential stability and periodicity for the linear cellular neural networks. The work provides one such method which can be applied to cellular neural networks systems with variable delays. The method, based on the theory of fixed point and differential inequality technique. The applicability of the present results is demonstrated by two examples. (C) 2004 Published by Elsevier B.V.
引用
收藏
页码:331 / 341
页数:11
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