On exponential stability of delayed neural networks with a general class of activation functions

In this Letter, based on globally Lipschitz continuous 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...

Full description

Saved in:
Bibliographic Details
Published in:Physics letters. A 2002-06, Vol.298 (2), p.122-132
Main Authors: Sun, Changyin, Zhang, Kanjian, Fei, Shumin, Feng, Chun-Bo
Format: Article
Language:English
Subjects:
Activation functions
Global exponential stability
M-matrix
Neural networks
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this Letter, based on globally Lipschitz continuous 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 Letter. So this work gives some improvements to the previous ones.
ISSN:0375-9601
1873-2429
DOI:10.1016/S0375-9601(02)00471-1