Global exponential convergence for delayed cellular neural networks with a class of general activation functions

被引：4

作者：

Shao, Jianying ^{[1
]}

机构：

[1] Jiaxing Univ, Coll Math & Informat Engn, Jiaxing 314001, Zhejiang, Peoples R China

来源：

NONLINEAR ANALYSIS-REAL WORLD APPLICATIONS | 2009年 / 10卷 / 03期

关键词：

Cellular neural networks; Exponential convergence; Delays; General activation functions; STABILITY; CRITERIA;

D O I：

10.1016/j.nonrwa.2008.02.018

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we consider delayed cellular neural networks with a class of general activation functions. By using some mathematical analysis techniques, we establish new results to ensure that all solutions of the networks converge exponentially to zero point. (C) 2008 Elsevier Ltd. All rights reserved.

引用

页码：1816 / 1821

页数：6

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