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Concatenated retrieval of correlated stored information in neural networks

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Concatenated retrieval of correlated stored information in neural networks

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Título Concatenated retrieval of correlated stored information in neural networks
Autor Almeida, Rita Maria Cunha de
Espinosa, Alexandre Luis Fernandes
Idiart, Marco Aurelio Pires
Abstract 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.
Contido em Physical review. E, Statistical, nonlinear, and soft matter physics. Vol. 74, no. 4 (Oct. 2006), 041912 12p.
Assunto Mecânica estatística
Memória
Memória de curta duração
Redes neurais
Sincronizacao
Origem Estrangeiro
Tipo Artigo de periódico
URI http://hdl.handle.net/10183/101624
Arquivos Descrição Formato
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