Period-adding and spiral organization of the periodicity in a Hopfield neural network

Bibliographic Details
Main Author: Rech P.C.*
Publication Date: 2015
Format: Article
Language: eng
Source: Repositório Institucional da Udesc
dARK ID: ark:/33523/0013000003m31
Download full: https://repositorio.udesc.br/handle/UDESC/8113
Summary: © 2013, Springer-Verlag Berlin Heidelberg.This work reports two-dimensional parameter space plots, concerned with a three-dimensional Hopfield-type neural network with a hyperbolic tangent as the activation function. It shows that typical periodic structures embedded in a chaotic region, called shrimps, organize themselves in two independent ways: (i) as spirals that individually coil up toward a focal point while undergo period-adding bifurcations and, (ii) as a sequence with a well-defined law of formation, constituted by two different period-adding sequences inserted between.
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spelling Period-adding and spiral organization of the periodicity in a Hopfield neural network© 2013, Springer-Verlag Berlin Heidelberg.This work reports two-dimensional parameter space plots, concerned with a three-dimensional Hopfield-type neural network with a hyperbolic tangent as the activation function. It shows that typical periodic structures embedded in a chaotic region, called shrimps, organize themselves in two independent ways: (i) as spirals that individually coil up toward a focal point while undergo period-adding bifurcations and, (ii) as a sequence with a well-defined law of formation, constituted by two different period-adding sequences inserted between.2024-12-06T13:58:52Z2015info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlep. 1 - 61868-808X10.1007/s13042-013-0222-0https://repositorio.udesc.br/handle/UDESC/8113ark:/33523/0013000003m31International Journal of Machine Learning and Cybernetics61Rech P.C.*engreponame:Repositório Institucional da Udescinstname:Universidade do Estado de Santa Catarina (UDESC)instacron:UDESCinfo:eu-repo/semantics/openAccess2024-12-07T20:56:27Zoai:repositorio.udesc.br:UDESC/8113Biblioteca Digital de Teses e Dissertaçõeshttps://pergamumweb.udesc.br/biblioteca/index.phpPRIhttps://repositorio-api.udesc.br/server/oai/requestri@udesc.bropendoar:63912024-12-07T20:56:27Repositório Institucional da Udesc - Universidade do Estado de Santa Catarina (UDESC)false
dc.title.none.fl_str_mv Period-adding and spiral organization of the periodicity in a Hopfield neural network
title Period-adding and spiral organization of the periodicity in a Hopfield neural network
spellingShingle Period-adding and spiral organization of the periodicity in a Hopfield neural network
Rech P.C.*
title_short Period-adding and spiral organization of the periodicity in a Hopfield neural network
title_full Period-adding and spiral organization of the periodicity in a Hopfield neural network
title_fullStr Period-adding and spiral organization of the periodicity in a Hopfield neural network
title_full_unstemmed Period-adding and spiral organization of the periodicity in a Hopfield neural network
title_sort Period-adding and spiral organization of the periodicity in a Hopfield neural network
author Rech P.C.*
author_facet Rech P.C.*
author_role author
dc.contributor.author.fl_str_mv Rech P.C.*
description © 2013, Springer-Verlag Berlin Heidelberg.This work reports two-dimensional parameter space plots, concerned with a three-dimensional Hopfield-type neural network with a hyperbolic tangent as the activation function. It shows that typical periodic structures embedded in a chaotic region, called shrimps, organize themselves in two independent ways: (i) as spirals that individually coil up toward a focal point while undergo period-adding bifurcations and, (ii) as a sequence with a well-defined law of formation, constituted by two different period-adding sequences inserted between.
publishDate 2015
dc.date.none.fl_str_mv 2015
2024-12-06T13:58:52Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv 1868-808X
10.1007/s13042-013-0222-0
https://repositorio.udesc.br/handle/UDESC/8113
dc.identifier.dark.fl_str_mv ark:/33523/0013000003m31
identifier_str_mv 1868-808X
10.1007/s13042-013-0222-0
ark:/33523/0013000003m31
url https://repositorio.udesc.br/handle/UDESC/8113
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv International Journal of Machine Learning and Cybernetics
6
1
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv p. 1 - 6
dc.source.none.fl_str_mv reponame:Repositório Institucional da Udesc
instname:Universidade do Estado de Santa Catarina (UDESC)
instacron:UDESC
instname_str Universidade do Estado de Santa Catarina (UDESC)
instacron_str UDESC
institution UDESC
reponame_str Repositório Institucional da Udesc
collection Repositório Institucional da Udesc
repository.name.fl_str_mv Repositório Institucional da Udesc - Universidade do Estado de Santa Catarina (UDESC)
repository.mail.fl_str_mv ri@udesc.br
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