Stability Analysis for Generalized Neutral-type Neural Networks

被引：0
|
作者：
Liu, Guoquan [1 ]
Yang, Simon X. [1 ]
机构：
[1] Chongqing Univ, Coll Automat, Chongqing 400044, Peoples R China
来源：
FRONTIERS OF MANUFACTURING AND DESIGN SCIENCE II, PTS 1-6 | 2012年 / 121-126卷
关键词：
neutral-type; generalized neural networks; linear matrix inequality; asymptotic stability; EXPONENTIAL STABILITY;
D O I：
10.4028/www.scientific.net/AMM.121-126.1387
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The issue of asymptotic stability is discussed for generalized neutral-type neural networks with time-varying delays. A new stability condition is presented based on the Lyapunov-Krasovskii method and the inequality technique, which is dependent on the amount of delay. The proposed result is given in the form of a linear matrix inequality (LMI). Finally, an example is given to illustrate our result. This result is of great significance in designs and applications of globally stable of generalized neutral-type neural networks.
引用
收藏
页码：1387 / 1391
页数：5
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