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A Model for Hierarchical Associative Memories via Dynamically Coupled GBSB Neural Networks

  • Rogério M. Gomes
  • Antônio P. Braga
  • Henrique E. Borges
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3696)

Abstract

Many approaches have emerged in the attempt to explain the memory process. One of which is the Theory of Neuronal Group Selection (TNGS), proposed by Edelman [1]. In the present work, inspired by Edelman ideas, we design and implement a new hierarchically coupled dynamical system consisting of GBSB neural networks. Our results show that, for a wide range of the system parameters, even when the networks are weakly coupled, the system evolve towards an emergent global associative memory resulting from the correlation of the lowest level memories.

Keywords

Hierarchical memories Coupled neural networks Dynamical systems Artificial neural networks TNGS 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Rogério M. Gomes
    • 1
  • Antônio P. Braga
    • 2
  • Henrique E. Borges
    • 1
  1. 1.Laboratório de Sistemas InteligentesCEFET/MGBelo HorizonteBrasil
  2. 2.Laboratório de Inteligência e Técnicas ComputacionaisPPGEE-UFMGBelo HorizonteBrasil

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