Exponential Stability of the Neural Networks with Discrete and Distributed Time-Varying Delays

被引：0
|
作者：
Li, Qingbo [1 ]
Xing, Peixu [1 ]
Wu, Yuanyuan [2 ]
机构：
[1] Zhengzhou Univ Light Ind, Dept Math & Informat Sci, Zhengzhou 450002, Peoples R China
[2] Zhengzhou Univ Light Ind, Sch Elect & Elect Engn, Zhengzhou 450052, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2010, PT 1, PROCEEDINGS | 2010年 / 6063卷
关键词：
Neural networks; Exponential stability; Delay-dependent; Free-weighting matrix; LMIs; ROBUST STABILITY;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Hot a class of generalized neural networks(NNs) with discrete and distributed time-varying delays, this paper is concerned with the problem of the global exponential stability analysis. By introducing a novel augmented Lyapunov-Krasovskii functional and some appropriate free-weighting matrices, a new delay-dependent stability criterion is derived in terms of linear matrix inequalities (LMIs). Finally, a numerical example is given to show the superiority of the obtained results.
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页码：569 / +
页数：2
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