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
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.
引用
收藏
页码:264 / 271
页数:8
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