New robust exponential stability analysis for uncertain neural networks with time-varying delay

被引：4
|
作者：
Chen Y.-G. [1 ]
Bi W.-P. [2 ]
机构：
[1] Department of Mathematics, Henan Institute of Science and Technology
[2] College of Mathematics and Information Science, Henan Normal University
来源：
Int. J. Autom. Comput. | 2008年 / 4卷 / 395-400期
关键词：
Linear matrix inequalities (LMIs); Lyapunov functional method; Robust exponential stability; Time-varying delay; Uncertain neural networks;
D O I：
10.1007/s11633-008-0395-2
中图分类号：
学科分类号：
摘要：
In this paper, the global robust exponential stability is considered for a class of neural networks with parametric uncertainties and time-varying delay. By using Lyapunov functional method, and by resorting to the new technique for estimating the upper bound of the derivative of the Lyapunov functional, some less conservative exponential stability criteria are derived in terms of linear matrix inequalities (LMIs). Numerical examples are presented to show the effectiveness of the proposed method. © 2008 Institute of Automation, Chinese Academy of Sciences and Springer-Verlag GmbH.
引用
收藏
页码：395 / 400
页数：5
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