Comments and further improvements on "New LMI conditions for delay-dependent asymptotic stability of delayed Hopfield neural networks"

被引：5
|
作者：
Lou, Xuyang [1 ]
Cui, Baotong [1 ]
机构：
[1] So Yangtze Univ, Res Ctr Control Sci & Engn, Wuxi 214122, Jiangsu, Peoples R China
来源：
NEUROCOMPUTING | 2007年 / 70卷 / 13-15期
基金：
中国国家自然科学基金;
关键词：
asymptotic stability; Hopfield neural networks; delay-dependent; nonlinear measure; linear matrix inequality;
D O I：
10.1016/j.neucom.2007.02.003
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we point out that global Lipschitz condition on the activation functions should be revised and the boundedness assumption of the activation functions in the above paper can be removed based on a nonlinear measure approach. Moreover, we present some improved sufficient conditions which are less conservative than those in the above paper in terms of linear matrix inequality (LMI). (C) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码：2566 / 2571
页数：6
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