Global asymptotic stability of a larger class of neural networks with constant time delay

被引：248

作者：

Arik, S ^{[1
]}

机构：

[1] Istanbul Univ, Dept Elect & Elect Engn, TR-34850 Istanbul, Turkey

来源：

PHYSICS LETTERS A | 2003年 / 311卷 / 06期

关键词：

delayed neural networks; equilibrium analysis; Lyapunov-Krasovskii functional; global asymptotic stability;

D O I：

10.1016/S0375-9601(03)00569-3

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

This Letter presents some new sufficient conditions for the uniqueness and global asymptotic stability (GAS) of the equilibrium point for a larger class of neural networks with constant time delay. It is shown that the use of a more general type of Lyapunov-Krasovskii functional enables us to establish global asymptotic stability of a larger class of delayed neural networks than those considered in some previous papers. (C) 2003 Elsevier Science B.V. All rights reserved.

引用

页码：504 / 511

页数：8

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