Absolutely exponential stability in delayed cellular neural networks

被引：34
作者：
Zhang, JY [1 ]
机构：
[1] SW Jiaotong Univ, Natl Tract Power Lab, Chengdu 610031, Peoples R China
来源：
INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS | 2002年 / 30卷 / 04期
关键词：
delay; cellular neural network; globally exponential stability; absolutely exponential stability; M-matrix;
D O I：
10.1002/cta.182
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, without assuming the boundedness, monotonicity and differentiability of the activation functions, we present a necessary and sufficient condition ensuring the existence and uniqueness of the equilibrium point of cellular neural network with fixed time delays (DCNNs). Using M-matrix theory, Liapunov functionals and functions are constructed and employed to establish sufficient conditions for absolutely exponential stability of DCNNs. The results are applicable to DCNNs with both symmetric and non-symmetric interconnection matrices, and globally Lipschitz continuous activation functions. Copyright (C) 2002 John Wiley Sons, Ltd.
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收藏
页码：395 / 409
页数：15
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