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On exponential stability of delayed neural networks with globally Lipschitz continuous activation functions

被引：0
|
作者：
Sun, CY [1 ]
Feng, CB [1 ]
机构：
[1] SE Univ, Res Inst Automat, Nanjing 210096, Peoples R China
来源：
PROCEEDINGS OF THE 4TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-4 | 2002年
关键词：
D O I：
10.1109/WCICA.2002.1021425
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, based on globally Lipschitz continous activation functions, new conditions ensuring existence, uniqueness and global exponential stability of the equilibrium point of delayed neural networks are obtained. The delayed Hopfield network and Bidirectional associative memory network are special cases of the network model considered in this paper. So this work gives some improvements to the previous ones.
引用
收藏
页码：1953 / 1957
页数：5
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