LMI-based stability criteria for neural networks with multiple time-varying delays

被引：108

作者：

He, Y

Wang, QG

Wu, M

机构：

[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 119260, Singapore

[2] Cent S Univ, Sch Informat Sci & Engn, Changsha 410083, Peoples R China

来源：

PHYSICA D-NONLINEAR PHENOMENA | 2005年 / 212卷 / 1-2期

关键词：

neural networks; stability; delay-dependent; time-varying delay; linear Matrix inequality (LMI);

D O I：

10.1016/j.physd.2005.09.013

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, the stability of neural networks with multiple time-varying delays is studied. A new class of Lyapunov-Krasovskii functionals is constructed and the S-procedure and free-weighting matrix method are employed to derive a delay-dependent stability criterion, from which a delay-independent criterion is obtained as a special case. Moreover, the result is also extended to delay-dependent and rate-independent stability criteria for multiple unknown time-varying delays. Finally, numerical examples are given to illustrate the effectiveness of our methods and improvement over the existing ones. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：126 / 136

页数：11

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