AMOEBA-BASED NEUROCOMPUTING WITH CHAOTIC DYNAMICS.

This article describes amoeba-based neurocomputing as a deadlock-breaking form of parallel computing used to search for reasonable solutions. The contraction-relaxation rhythmic oscillations of this unicellular organism uses shape deformations as an integrated computational capacity. The article dis...

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Published in:Communications of the ACM Vol. 50; no. 9; pp. 69 - 73
Main Authors: Aono, Masashi, Hara, Masahiko, Aihara, Kazuyuki
Format: Article
Published: Association for Computing Machinery Sep2007
Subjects:
Online Access:View this record in EBSCOhost
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        10.1145/1284621.1284651
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        atl: AMOEBA-BASED NEUROCOMPUTING WITH CHAOTIC DYNAMICS.
      aug:
        au:
          Aono, Masashi
          Hara, Masahiko
          Aihara, Kazuyuki
        affil:
          Researcher, Local Spatio-Temporal Functions Lab, RIKEN, Wako, Japan.
          Team Leader, Local Spatio-Temporal Functions Lab, RIKEN, Wako, Japan.
          Professor, Institute of Industrial Science, University of Tokyo, Japan.
      su:
        Fluctuations (Physics)
        Parallel computers
        Amoeba
        Artificial neural networks
        Postural balance
        Neural computers
        Oscillations
        Evolutionary computation
      sug:
        subj:
          Fluctuations (Physics)
          Parallel computers
          Amoeba
          Artificial neural networks
          Postural balance
          Neural computers
          Oscillations
          Evolutionary computation
      ab: This article describes amoeba-based neurocomputing as a deadlock-breaking form of parallel computing used to search for reasonable solutions. The contraction-relaxation rhythmic oscillations of this unicellular organism uses shape deformations as an integrated computational capacity. The article discusses experiments in which a neural network is modeled on the amoeba's photoavoidance-based shape deformation under optical feedback control. This system is the first non-silicon based implementation of chaotic neural computing. The capability of spontaneously escaping from equilibrium and stability is essential for our biologically inspired computing, and amoeba chaotic dynamics achieve that.
      pubtype: Periodical
      doctype: Article
      src: R
    language: English
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