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dc.contributor.authorAlmeida, Rita Maria Cunha dept_BR
dc.contributor.authorEspinosa, Alexandre Luis Fernandespt_BR
dc.contributor.authorIdiart, Marco Aurelio Pirespt_BR
dc.date.accessioned2014-08-22T02:11:09Zpt_BR
dc.date.issued2006pt_BR
dc.identifier.issn1539-3755pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/101624pt_BR
dc.description.abstractWe 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.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofPhysical review. E, Statistical, nonlinear, and soft matter physics. Ridge. Vol. 74, no. 4 (Oct. 2006), 041912, 12 p.pt_BR
dc.rightsOpen Accessen
dc.subjectRedes neuraispt_BR
dc.subjectMemóriapt_BR
dc.subjectMecânica estatísticapt_BR
dc.subjectMemória de curta duraçãopt_BR
dc.subjectSincronizacaopt_BR
dc.titleConcatenated retrieval of correlated stored information in neural networkspt_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb000564129pt_BR
dc.type.originEstrangeiropt_BR


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