Exponential Stability of Cellular Neural Networks with Time-varying Delay

被引：0
|
作者：
Meng Hua [1 ]
Wang Yanhong [1 ]
Lv Xuan [1 ]
Wu, Xue-Li [1 ]
机构：
[1] Hebei Univ Sci & Technol, Shijiazhuang 050054, Peoples R China
来源：
CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS | 2009年
关键词：
delayed cellular neural networks (DCNNs); Lyapunov functional; LMI; Exponential stability; GLOBAL ASYMPTOTIC STABILITY;
D O I：
10.1109/CCDC.2009.5195209
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A novel method is proposed in this note for exponential stability of cellular neural networks with time-varying delay. New delay-dependent exponential stability conditions of cellular neural network with time-varying delay is presented by constructing Lyapunov function and using linear matrix inequality (LMI). Finally, a numerical example is given to demonstrate the effect of the proposed method.
引用
收藏
页码：5669 / 5674
页数：6
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