Global Asymptotic Robust Stability and Global Exponential Robust Stability of Neural Networks with Time-Varying Delays

被引：0
|
作者：
Jin-Liang Shao
Ting-Zhu Huang
Sheng Zhou
机构：
[1] University of Electronic Science and Technology of China,School of Applied Mathematics
来源：
Neural Processing Letters | 2009年 / 30卷
关键词：
Neural networks; Time-varying delays; Global robust stability;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, based on nonnegative matrix theory, the Halanay’s inequality and Lyapunov functional, some novel sufficient conditions for global asymptotic robust stability and global exponential robust stability of neural networks with time-varying delays are presented. It is shown that our results improve and generalize several previous results derived in the literatures. From the obtained results, some linear matrix inequality criteria are derived. Finally, a simulation is given to show the effectiveness of the results.
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页码：229 / 241
页数：12
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