Stability analysis for high-order dynamic neural networks with time delays

被引：0

作者：

Shen, WM ^{[1
]}

Gu, J ^{[1
]}

Shen, YJ ^{[1
]}

机构：

[1] Dalhousie Univ, Dept Elect & Comp Engn, Halifax, NS, Canada

来源：

IEEE ROBIO 2004: PROCEEDINGS OF THE IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS | 2004年

关键词：

time delay; high-order dynamic neural networks; stability analysis; linear matrix inequality;

D O I：

暂无

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

This paper studies the problem of asymptotic stability for a class of high-order dynamic neural networks with time delays. Several useful lemmas are proved in this paper first. After that, the sufficient conditions for the asymptotic stability of the system with constant time delays are introduced, and also this asymptotic stability problem for the system with time-varying delays is put forward. In order to obtain above results, the Lyapunov-Krasovskii stability theory for functional differential equations and the linear matrix inequality (LMI) approach are employed to investigate this kind of problems. Finally, some numerical examples are given to illustrate the advantages of our approach.

引用

页码：966 / 971

页数：6

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