Global asymptotic stability conditions of delayed neural networks

被引：0
作者：
Zhou, DM
Cao, JD
Zhang, LM [1 ]
机构：
[1] Fudan Univ, Dept Elect Engn, Shanghai 200433, Peoples R China
[2] SE Univ, Dept Appl Math, Nanjing 210096, Peoples R China
[3] Yunnan Univ, Dept Elect Engn, Kunming 650091, Peoples R China
来源：
APPLIED MATHEMATICS AND MECHANICS-ENGLISH EDITION | 2005年 / 26卷 / 03期
关键词：
cellular neural network; global stability; inequality of matrix; delay;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Utilizing the Liapunov functional method and combining the inequality of matrices technique to analyze the existence of a unique equilibrium point and the global asymptotic stability for delayed cellular neural networks (DCNNs), a new sufficient criterion ensuring the global stability of DCNNs is obtained. Our criteria provide some parameters to appropriately compensate for the tradeoff between the matrix definite condition on feedback matrix and delayed feedback matrix. The criteria can easily be used to design and verify globally stable networks. Furthermore, the condition presented here is independent of the delay parameter and is less restrictive than that given in the references.
引用
收藏
页码：372 / 380
页数：9
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