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Neural Computing and Applications
Published in: Neural Computing and Applications 1/2013

01-01-2013 | Original Article

Stability of Hopfield neural networks with time delays and variable-time impulses

Authors: Chao Liu, Chuandong Li, Tingwen Huang, Chaojie Li

Published in: Neural Computing and Applications | Issue 1/2013

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Abstract

The stability of Hopfield neural networks with fixed-time impulses has been intensively investigated in recent years. However, few existing publications addressed the stability of delayed neural networks with variable-time impulses. In this paper, we consider the case of variable-time impulses and attempt to establish the general stability criteria. It shows that the proposed results can also be applied to the case of fixed-time impulses, which provide a new stability condition for the case of fixed-time impulses. To illustrate the effectiveness of our theoretical results, numerical examples and simulations are also presented.
previous article Research of assembling optimized classification algorithm by neural network based on Ordinary Least Squares (OLS)

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Metadata
Title
Stability of Hopfield neural networks with time delays and variable-time impulses
Authors
Chao Liu
Chuandong Li
Tingwen Huang
Chaojie Li
Publication date
01-01-2013
Publisher
Springer-Verlag
Published in
Neural Computing and Applications / Issue 1/2013
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-011-0695-2

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