Dynamics of a class of Cohen-Grossberg neural networks with time-varying delays

被引：41

作者：

Huang, Chuangxia ^{[1
]}

Huang, Lihong ^{[1
]}

机构：

[1] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China

来源：

NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS | 2007年 / 8卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Cohen-Grossberg neural networks; exponential stability; periodic solution; coincidence degree;

D O I：

10.1016/j.nonrwa.2005.04.008

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Without assuming the boundedness, monotonicity, and differentiability of activation functions and any symmetry of interconnections, we establish some sufficient conditions for the global exponential stability of a unique equilibrium and the existence of periodic solution for the Cohen-Grossberg neural network with time-varying delays. Brouwer's fixed point theorem, matrix theory, a continuation theorem of the coincidence degree and inequality analysis are employed. Our results are all independent of the delays and maybe more convenient to design a circuit network. (c) 2005 Elsevier Ltd. All rights reserved.

引用

页码：40 / 52

页数：13

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