Global asymptotic stability of delayed Cohen-Grossberg neural networks

被引：58

作者：

Chen, Y ^{[1
]}

机构：

[1] Wilfrid Laurier Univ, Dept Math, Waterloo, ON N2L 3C5, Canada

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS | 2006年 / 53卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Cohen-Grossberg neural network; discrete delay; distributed delay; equilibrium; global (asymptotic) stability; M-matrix;

D O I：

10.1109/TCSI.2005.856047

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, we study the Cohen-Grossberg neural networks with discrete and distributed delays. For a general class of internal decay functions, without assuming the boundedness, differentiability, and monotonicity of the activation functions, we establish some sufficient conditions for the existence of a unique equilibrium and its global asymptotic stability. Theory of M-matrices and Lyapunov functional technique are employed. The criteria are independent of delays and hence delays are harmless in our case. Our results improve and generalize some existing ones.

引用

页码：351 / 357

页数：7

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