Nonextensivity in a memory network access mechanism

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Autor principal: Roseli S. Wedemann
Formato: Artículo científico
Lenguaje:en
Publicado: Sociedade Brasileira de Física 2009
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author Roseli S. Wedemann
author_facet Roseli S. Wedemann
contents Nonextensivity in a memory network access mechanism Roseli S. Wedemann Raul Donangelo Luís A. V. de Carvalho Física, Astronomía y Matemáticas Self Neuroses Consciousness unconsciousness Boltzmann machine We have previously described neurotic psychopathology and psychoanalytic working-through by an associative memory mechanism, based on a neural network. Memory was initially modelled by a Boltzmann machine (BM). We simulated known microscopic mechanisms that control synaptic properties and showed that the network self-organizes to a hierarchical, clustered structure. Some properties of the complex networks which result from this self-organization indicate that a generalization of the BM may be necessary to model memory. We have thus generalized the memory model, using Generalized Simulated Annealing, derived from the nonextensive formalism, and show some properties of the resulting memory access mechanism. 2009 artículo científico 0103-9733 https://www.redalyc.org/articulo.oa?id=46413559027 en http://www.redalyc.org/revista.oa?id=464 Brazilian Journal of Physics application/pdf Sociedade Brasileira de Física Brazilian Journal of Physics (Brasil) Num.2A Vol.39
format Artículo científico
id redalyc_46413559027
institution Redalyc
language en
publishDate 2009
publisher Sociedade Brasileira de Física
spellingShingle Nonextensivity in a memory network access mechanism
Roseli S. Wedemann
Física, Astronomía y Matemáticas
Self
Neuroses
Consciousness
unconsciousness
Boltzmann machine
Nonextensivity in a memory network access mechanism Roseli S. Wedemann Raul Donangelo Luís A. V. de Carvalho Física, Astronomía y Matemáticas Self Neuroses Consciousness unconsciousness Boltzmann machine We have previously described neurotic psychopathology and psychoanalytic working-through by an associative memory mechanism, based on a neural network. Memory was initially modelled by a Boltzmann machine (BM). We simulated known microscopic mechanisms that control synaptic properties and showed that the network self-organizes to a hierarchical, clustered structure. Some properties of the complex networks which result from this self-organization indicate that a generalization of the BM may be necessary to model memory. We have thus generalized the memory model, using Generalized Simulated Annealing, derived from the nonextensive formalism, and show some properties of the resulting memory access mechanism. 2009 artículo científico 0103-9733 https://www.redalyc.org/articulo.oa?id=46413559027 en http://www.redalyc.org/revista.oa?id=464 Brazilian Journal of Physics application/pdf Sociedade Brasileira de Física Brazilian Journal of Physics (Brasil) Num.2A Vol.39
title Nonextensivity in a memory network access mechanism
topic Física, Astronomía y Matemáticas
Self
Neuroses
Consciousness
unconsciousness
Boltzmann machine
url https://www.redalyc.org/articulo.oa?id=46413559027