Delay-Dependent Stability of Neural Networks with Time-Varying Delays

被引：0

作者：

Xiong, Jing-Jing ^{[1
]}

Zhang, Guobao ^{[1
]}

机构：

[1] Southeast Univ, Sch Automat, Minist Educ, Key Lab Measurement & Control CSE, Nanjing 210096, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017) | 2017年

关键词：

Neural networks; time-varying delays; stability analysis; Lyapunov-Krasovskii functional; GLOBAL 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 investigates the problem of delay-dependent stability for continuous neural networks with time-varying delays. By constructing an augmented Lyapunov-Krasovskii functional and employing the integral inequality, reciprocally convex combination inequality and free-weighting matrix method, a less conservative stability criterion is established in terms of linear matrix inequalities. It is found that the obtained stability criterion has lower computational burden. Finally, two numerical examples used in the literature are given to show the effectiveness and superiority of the obtained criterion.

引用

页码：4024 / 4028

页数：5

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