Delay-dependent Exponential Stability of Neutral Neural Networks with Interval Time-Varying Delay

被引：0

作者：

Liu, Yajuan ^{[1
]}

Lee, S. M. ^{[1
]}

Park, Ju H. ^{[2
]}

机构：

[1] Daegu Univ, Sch Elect Engn, Gyongsan 712714, South Korea

[2] Yeungnam Univ, Dept Elect Engn, Kyongsan 712749, South Korea

来源：

2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2015年

关键词：

Neutral-type neural network; Interval time-varying delay; Exponential stability; ASYMPTOTIC STABILITY; CRITERIA;

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 presents a global stability criteria of neural networks with neutral-type time-varying delay. By constructing a new Lyapunov-Krasovskii function, where not only upper bound, but also lower bound of time delay is included, some less conservative delay-dependent exponential stability criteria is obtained by employing new technique of dealing with some integral terms. Numerical examples are presented to demonstrate the effectiveness and improvement of our results.

引用

页码：722 / 725

页数：4

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