New exponential stability results for delayed neural networks with time varying delays

被引：68
作者：
Yucel, E [1 ]
Arik, S [1 ]
机构：
[1] Istanbul Univ, Dept Comp Engn, TR-34320 Istanbul, Turkey
来源：
PHYSICA D-NONLINEAR PHENOMENA | 2004年 / 191卷 / 3-4期
关键词：
delayed neural networks; Lyapunov-Krasovskii functionals; linear matrix inequalities; exponential stability;
D O I：
10.1016/j.physd.2003.11.010
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper presents new sufficient conditions for the uniqueness and exponential stability of the equilibrium point for delayed neural networks with time varying delays. By employing a more general type of Lyapunov-Krasovskii functional and using LMI (linear matrix inequality), we derive new results for exponential stability of the equilibrium point for delayed neural networks. The results establish a relation between the delay time and the parameters of the network. The results are compared with the previous results derived in the literature. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码：314 / 322
页数：9
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