Stabilizing Hopfield neural networks via inhibitory self-connections
type: Item
instance of: scholarly article
title: Stabilizing Hopfield neural networks via inhibitory self-connections
zbMATH Open document ID: 1062.34087
author: Lin Wang
published in: Journal of Mathematical Analysis and Applications
publication date: 2004-08-06T00:00:00Z
review text: The author studies Hopfield-type neural networks with finite distributed delays. He shows how to stabiize the Hopfield neural network with general activation functions and finite distributed delays via self-inhibitory connections. To this end the author uses the theory of monotone dynamical systems.
Mathematics Subject Classification ID: 34K20
Mathematics Subject Classification ID: 34K60
Mathematics Subject Classification ID: 92B20
zbMATH DE Number: 2081787
zbMATH Keywords: attractivity
zbMATH Keywords: distributed delay
zbMATH Keywords: monotone dynamical system
zbMATH Keywords: neural network
reviewed by: Messoud Efendiev
MaRDI profile type: Publication
full work available at URL: j.jmaa.2003.11.048
OpenAlex ID: W2022254042
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DOI: 10.1016/J.JMAA.2003.11.048
description: scientific article; zbMATH DE number 2081787