Concatenated retrieval of correlated stored information in neural networks
Autor(a) principal: | |
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Data de Publicação: | 2006 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/101624 |
Resumo: | We consider a coupled map lattice defined on a hypercube in M dimensions, taken here as the information space, to model memory retrieval and information association by a neural network. We assume that both neuronal activity and spike timing may carry information. In this model the state of the network at a given time t is completely determined by the intensity y(σ,t) with which the information pattern represented by the integer is being expressed by the network. Logistic maps, coupled in the information space, are used to describe the evolution of the intensity function y(σ,t) with the intent to model memory retrieval in neural systems. We calculate the phase diagram of the system regarding the model ability to work as an associative memory. We show that this model is capable of retrieving simultaneously a correlated set of memories, after a relatively long transient that may be associated to the retrieving of concatenated memorized patterns that lead to a final attractor. |
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Almeida, Rita Maria Cunha deEspinosa, Alexandre Luis FernandesIdiart, Marco Aurelio Pires2014-08-22T02:11:09Z20061539-3755http://hdl.handle.net/10183/101624000564129We consider a coupled map lattice defined on a hypercube in M dimensions, taken here as the information space, to model memory retrieval and information association by a neural network. We assume that both neuronal activity and spike timing may carry information. In this model the state of the network at a given time t is completely determined by the intensity y(σ,t) with which the information pattern represented by the integer is being expressed by the network. Logistic maps, coupled in the information space, are used to describe the evolution of the intensity function y(σ,t) with the intent to model memory retrieval in neural systems. We calculate the phase diagram of the system regarding the model ability to work as an associative memory. We show that this model is capable of retrieving simultaneously a correlated set of memories, after a relatively long transient that may be associated to the retrieving of concatenated memorized patterns that lead to a final attractor.application/pdfengPhysical review. E, Statistical, nonlinear, and soft matter physics. Ridge. Vol. 74, no. 4 (Oct. 2006), 041912, 12 p.Redes neuraisMemóriaMecânica estatísticaMemória de curta duraçãoSincronizacaoConcatenated retrieval of correlated stored information in neural networksEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL000564129.pdf000564129.pdfTexto completo (inglês)application/pdf587482http://www.lume.ufrgs.br/bitstream/10183/101624/1/000564129.pdfa5a1650a84a20666a62e07f78681da70MD51TEXT000564129.pdf.txt000564129.pdf.txtExtracted Texttext/plain51980http://www.lume.ufrgs.br/bitstream/10183/101624/2/000564129.pdf.txt4b0931c12cf38ba0291d7665e228c279MD52THUMBNAIL000564129.pdf.jpg000564129.pdf.jpgGenerated Thumbnailimage/jpeg2083http://www.lume.ufrgs.br/bitstream/10183/101624/3/000564129.pdf.jpg40dd418912a64bfe9542dd9d89ddec28MD5310183/1016242023-10-28 03:33:10.527245oai:www.lume.ufrgs.br:10183/101624Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-10-28T06:33:10Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Concatenated retrieval of correlated stored information in neural networks |
title |
Concatenated retrieval of correlated stored information in neural networks |
spellingShingle |
Concatenated retrieval of correlated stored information in neural networks Almeida, Rita Maria Cunha de Redes neurais Memória Mecânica estatística Memória de curta duração Sincronizacao |
title_short |
Concatenated retrieval of correlated stored information in neural networks |
title_full |
Concatenated retrieval of correlated stored information in neural networks |
title_fullStr |
Concatenated retrieval of correlated stored information in neural networks |
title_full_unstemmed |
Concatenated retrieval of correlated stored information in neural networks |
title_sort |
Concatenated retrieval of correlated stored information in neural networks |
author |
Almeida, Rita Maria Cunha de |
author_facet |
Almeida, Rita Maria Cunha de Espinosa, Alexandre Luis Fernandes Idiart, Marco Aurelio Pires |
author_role |
author |
author2 |
Espinosa, Alexandre Luis Fernandes Idiart, Marco Aurelio Pires |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Almeida, Rita Maria Cunha de Espinosa, Alexandre Luis Fernandes Idiart, Marco Aurelio Pires |
dc.subject.por.fl_str_mv |
Redes neurais Memória Mecânica estatística Memória de curta duração Sincronizacao |
topic |
Redes neurais Memória Mecânica estatística Memória de curta duração Sincronizacao |
description |
We consider a coupled map lattice defined on a hypercube in M dimensions, taken here as the information space, to model memory retrieval and information association by a neural network. We assume that both neuronal activity and spike timing may carry information. In this model the state of the network at a given time t is completely determined by the intensity y(σ,t) with which the information pattern represented by the integer is being expressed by the network. Logistic maps, coupled in the information space, are used to describe the evolution of the intensity function y(σ,t) with the intent to model memory retrieval in neural systems. We calculate the phase diagram of the system regarding the model ability to work as an associative memory. We show that this model is capable of retrieving simultaneously a correlated set of memories, after a relatively long transient that may be associated to the retrieving of concatenated memorized patterns that lead to a final attractor. |
publishDate |
2006 |
dc.date.issued.fl_str_mv |
2006 |
dc.date.accessioned.fl_str_mv |
2014-08-22T02:11:09Z |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10183/101624 |
dc.identifier.issn.pt_BR.fl_str_mv |
1539-3755 |
dc.identifier.nrb.pt_BR.fl_str_mv |
000564129 |
identifier_str_mv |
1539-3755 000564129 |
url |
http://hdl.handle.net/10183/101624 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Physical review. E, Statistical, nonlinear, and soft matter physics. Ridge. Vol. 74, no. 4 (Oct. 2006), 041912, 12 p. |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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