Almost periodic attractor of delayed neural networks with variable coefficients

被引：70

作者：

Cao, JD ^{[1
]}

Chen, AP ^{[1
]}

Huang, X ^{[1
]}

机构：

[1] Xiangtan Univ, Dept Math, Chengzhou 423000, Hunan, Peoples R China

来源：

PHYSICS LETTERS A | 2005年 / 340卷 / 1-4期

基金：

中国国家自然科学基金;

关键词：

neural networks; variable coefficients; time-varying delay; exponential dichotomy; Lyapunov function; almost periodic attractor; Halanay inequality;

D O I：

10.1016/j.physleta.2005.04.021

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

In this Letter, several sufficient conditions are obtained for the almost periodic attractor of delayed neural networks with variable coefficients based on the theory of exponential dichotomy, Lyapunov method and Halanay inequality technique. Many previous results reported in the literature are extended or improved for neural networks with or without delays. The obtained results are helpful to design globally stable almost periodic oscillatory neural networks. A numerical example is also given in the end to show the feasibility of our results. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：104 / 120

页数：17

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