Further Stability Analysis for Neural Networks with Time-Varying Interval Delay

被引：0
|
作者：
Cai, Qiufeng [1 ]
Yu, Jianjiang [1 ]
机构：
[1] Yancheng Teachers Univ, Sch Informat Sci & Technol, Yancheng 224002, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 1, PROCEEDINGS | 2009年 / 5551卷
关键词：
Neural networks (NNs); Lyapunov-Krasovskii functional; Delay-dependent; Time-varying interval delay; EXPONENTIAL STABILITY; ROBUST STABILITY; GLOBAL STABILITY; CRITERIA;
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：
This paper provides improved results on stability condition for a class of neural networks (NNs) with time-varying interval delay. The activation functions of the NNs are assumed to be more general. Based on a new augmented Lyapunov-Krasovskii functional, the improved delay-dependent, stability criterion for delay NNs is obtained in terms of linear matrix inequalities (LMIs). It is shown that the new criterion can provide less conservative results than some existing ones. A numerical example is given to demonstrate the effectiveness and the benefits of the proposed method.
引用
收藏
页码：423 / 432
页数：10
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