Delay-Dependent Exponential Stability of Cellular Neural Networks with Multi-Proportional Delays

被引：86

作者：

Zhou, Liqun ^{[1
]}

机构：

[1] Tianjin Normal Univ, Sci Math Coll, Tianjin 300387, Peoples R China

来源：

NEURAL PROCESSING LETTERS | 2013年 / 38卷 / 03期

基金：

美国国家科学基金会;

关键词：

Cellular neural networks; Proportional delay; Global exponential stability; Lyapunov functional; Spectral radius; GLOBAL ASYMPTOTIC STABILITY; EQUATIONS;

D O I：

10.1007/s11063-012-9271-8

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Global exponential stability of a class of cellular neural networks with multi-proportional delays is investigated. New delay-dependent sufficient conditions ensuring global exponential stability for the system presented here are related to the size of the proportional delay factor, by employing matrix theory and Lyapunov functional, and without assuming the differentiability, boundedness and monotonicity of the activation functions. Two examples and their simulation results are given to illustrate the effectiveness of the obtained results.

引用

页码：347 / 359

页数：13

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