On Delay-dependent Exponential Stability of Neutral-type Neural Networks with Interval Time-varying Delays

被引：6
作者：
Wu, Hongli [1 ]
Zhong, Yong [1 ]
Mai, Huanhuan [2 ]
机构：
[1] Hainan Normal Univ, Cheng Du Inst Comp Applicat, Chinese Acad Sci, Haikou, Peoples R China
[2] Chongqing Univ, Coll Comp Sci, Chongqing, Peoples R China
来源：
2009 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, VOL II, PROCEEDINGS | 2009年
关键词：
Interval time-varying delays; Exponential stability; Neutral-type; Neural networks; SYSTEMS; CRITERIA;
D O I：
10.1109/AICI.2009.134
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 deals with the problem of exponential stability for a class of neutral-type networks with interval time-varying delays. An approach combining the Lyapunov-Krasovskii functional with linear matrix inequality (LMI) is taken in our study. The theoretical analysis and numerical simulations show that our results are effectiveness. It is interested that there is a relationship between the exponential convergence rates with the bound of maximum value of interval time-varying delays.
引用
收藏
页码：563 / +
页数：3
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