Global stability analysis in delayed Hopfield neural network models

被引：209

作者：

Zhang, JY ^{[1
]}

Jin, XS ^{[1
]}

机构：

[1] SW Jiaotong Univ, Tract Power Natl Lab, Chengdu 610031, Peoples R China

来源：

NEURAL NETWORKS | 2000年 / 13卷 / 07期

基金：

中国国家自然科学基金;

关键词：

delay; neural network; global asymptotic stability; M-matrix;

D O I：

10.1016/S0893-6080(00)00050-2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, without assuming the boundedness, monotonicity and differentiability of the activation functions, we present new conditions ensuring existence, uniqueness, and global asymptotical stability of the equilibrium point of Hopfield neural network models with fixed time delays or distributed time delays. The results are applicable to both symmetric and nonsymmetric interconnection matrices, and all continuous nonmonotonic neuron activation functions. (C) 2000 Elsevier Science Ltd. All rights reserved.

引用

页码：745 / 753

页数：9

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