Delay-Dependent Stability Analysis for Recurrent Neural Networks with Time-Varying Delays

被引：4
作者：
Lv, Shu [1 ]
Tian, Junkang [1 ]
Zhong, Shouming [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Sichuan, Peoples R China
来源：
MATHEMATICAL PROBLEMS IN ENGINEERING | 2012年 / 2012卷
关键词：
GLOBAL ASYMPTOTIC STABILITY; EXPONENTIAL STABILITY; STATE ESTIMATION; CRITERIA; DISCRETE;
D O I：
10.1155/2012/910140
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper concerns the problem of delay-dependent stability criteria for recurrent neural networks with time varying delays. By taking more information of states and activation functions as augmented vectors, a new class of the Lyapunov functional is proposed. Then, some less conservative stability criteria are obtained in terms of linear matrix inequalities (LMIs). Finally, two numerical examples are given to illustrate the effectiveness of the proposed method.
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页数：14
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