Global robust exponential stability of interval neural networks with delays

被引：71

作者：

Sun, CY ^{[1
]}

Feng, CB ^{[1
]}

机构：

[1] Southeast Univ, Res Inst Automat, Nanjing 210096, Peoples R China

来源：

NEURAL PROCESSING LETTERS | 2003年 / 17卷 / 01期

关键词：

activation function; interval neural networks; Robust exponential stability;

D O I：

10.1023/A:1022999219879

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this Letter, based on globally Lipschitz continous activation functions, new conditions ensuring existence, uniqueness and global robust exponential stability of the equilibrium point of interval neural networks with delays are obtained. The delayed Hopfield network, Bidirectional associative memory network and Cellular neural network are special cases of the network model considered in this Letter.

引用

页码：107 / 115

页数：9

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