New Robust Stability of Uncertain Neutral-Type Neural Networks with Discrete Interval and Distributed Time-Varying Delays

被引：9
|
作者：
Liu, Guoquan [1 ]
Yang, Simon X. [2 ]
Fu, Wei [3 ]
机构：
[1] Chongqing Univ, Coll Automat, Chongqing, Peoples R China
[2] Univ Guelph, Sch Engn, Guelph, ON, Canada
[3] Chongqing Univ, Coll Automat, Chongqing, Peoples R China
来源：
JOURNAL OF COMPUTERS | 2012年 / 7卷 / 01期
关键词：
Neural networks; Robust stability; Linear matrix inequality; Neutral-type; Lyapunov-krasoviskii functional;
D O I：
10.4304/jcp.7.1.264-271
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper develops a novel robust stability criterion for a class of uncertain neutral-type neural networks with discrete interval and distributed time-varying delays. By constructing a general form of Lyapunov-Krasovskii functional, using the linear matrix inequality (LMI) approach and introducing some free-weight matrices, the delay-dependent robust stability criteria are derived in terms of LMI. Number examples are given to illustrate the effectiveness of the proposed method.
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页码：264 / 271
页数：8
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