Global exponential stability for uncertain cellular neural networks with multiple time-varying delays via LMI approach

被引：33
作者：
Gau, R. S.
Lien, C. H. [1 ]
Hsieh, J. G.
机构：
[1] I Shou Univ, Dept Elect Engn, Kaohsiung 840, Taiwan
[2] Natl Sun Yat Sen Univ, Dept Elect Engn, Kaohsiung 804, Taiwan
来源：
CHAOS SOLITONS & FRACTALS | 2007年 / 32卷 / 04期
关键词：
D O I：
10.1016/j.chaos.2005.11.036
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
The global exponential stability for a class of uncertain delayed cellular neural networks (DCNN) with multiple time-varying delays is considered. Delay-dependent criteria are proposed to guarantee the robust stability of DCNN via linear matrix inequality (LMI) approach. Two classes of uncertainties on feedback matrices are investigated. Some numerical examples are given to illustrate the effectiveness of our results. From the numerical simulation, significant improvement over the recent results can be observed. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1258 / 1267
页数：10
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