Global stability of a class of neural networks with time-varying delay

被引：61

作者：

Ensari, T ^{[1
]}

Arik, S ^{[1
]}

机构：

[1] Univ Istanbul, Dept Comp Engn, TR-34320 Istanbul, Turkey

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS | 2005年 / 52卷 / 03期

关键词：

equilibrium and stability analysis; Lyapunov functionals; neural networks; time-varying delays;

D O I：

10.1109/TCSII.2004.842050

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a new sufficient condition for the uniqueness and global asymptotic stability of the equilibrium point for a class of neural networks with time-varying delays. The result is obtained by the use of a more general type of Lyapunov-Krasovskii functional, establishing a relation between the network parameters of the neural system and time-varying delay parameter. The result is also shown to be a generalization of a previously published result.

引用

页码：126 / 130

页数：5

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