On exponential stability of delayed neural networks with a general class of activation functions

被引：66
|
作者：
Sun, CY [1 ]
Zhang, KJ [1 ]
Fei, SM [1 ]
Feng, CB [1 ]
机构：
[1] Southeast Univ, Res Inst Automat, Nanjing 210096, Peoples R China
来源：
PHYSICS LETTERS A | 2002年 / 298卷 / 2-3期
基金：
中国国家自然科学基金;
关键词：
global exponential stability; neural networks; M-matrix; activation functions;
D O I：
10.1016/S0375-9601(02)00471-1
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
In this Letter, based on globally Lipschitz continuous activation functions, new conditions ensuring existence, uniqueness and global exponential stability of the equilibrium point of delayed neural networks are obtained. The delayed Hopfield network and bidirectional associative memory network are special cases of the network model considered in this Letter. So this work gives some improvements to the previous ones. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：122 / 132
页数：11
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