New Exponential Stability Criterion for Neural Networks With Time-varying Delay

被引：0
|
作者：
Ji, Meng-Di [1 ,2 ]
He, Yong [1 ,2 ]
Wu, Min [1 ,2 ]
Zhang, Chuan-Ke [1 ,2 ]
机构：
[1] Cent S Univ, Sch Informat Sci & Engn, Changsha 410083, Peoples R China
[2] Hunan Engn Lab Adv Control & Intelligent Automat, Changsha 410083, Peoples R China
来源：
2014 33RD CHINESE CONTROL CONFERENCE (CCC) | 2014年
关键词：
Exponential stability; neural networks; time-varying delay; Lyapunov-Krasovskii functional; GLOBAL ASYMPTOTIC STABILITY;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper investigates the exponential stability for neural networks with time-varying delay based on Wirtinger-based inequality. Firstly, a simple Lyapunov-Krasovskii functional (LKF) containing a triple integral term is constructed. Then, the treatment to the derivation of the triple integral term leads to a great effect combining with Wirtinger-based inequality. As a result, an improved delay-dependent exponential stability criterion is obtained. Two numerical examples are given to demonstrate its effectiveness.
引用
收藏
页码：6119 / 6123
页数：5
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