Convergence of asymptotic systems of non-autonomous neural network models with infinite distributed delays
type: Item
instance of: scholarly article
title: Convergence of asymptotic systems of non-autonomous neural network models with infinite distributed delays
zbMATH Open document ID: 1382.34093
author: José J. Oliveira
published in: Journal of Nonlinear Science
publication date: 2017-12-06T00:00:00Z
full work available at URL: http://hdl.handle.net/1822/46289
review text: In this paper, a class of Hopfield neural networks with discrete time-varying and continuous distributed infinite delays is studied. Under some conditions it is proved that all solutions of the model with bounded initial condition are bounded. The definition of an asymptotic system introduces another model which is considered in the paper. It is proved that all solutions of this model are bounded as well. Several examples are provided and computer simulations illustrate the obtained theoretical results.
reviewed by: Angela Slavova
Mathematics Subject Classification ID: 34K60
Mathematics Subject Classification ID: 92B20
Mathematics Subject Classification ID: 34K25
Mathematics Subject Classification ID: 34K12
zbMATH DE Number: 6815943
zbMATH Keywords: neural networks
zbMATH Keywords: global convergence
zbMATH Keywords: asymptotic systems
zbMATH Keywords: infinite distributed delays
describes a project that uses: dde23
describes a project that uses: Matlab
MaRDI profile type: Publication
OpenAlex ID: W2591430550
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DOI: 10.1007/S00332-017-9371-8
description: scientific article; zbMATH DE number 6815943