• DocumentCode
    1298816
  • Title

    Field theory of self-organizing neural nets

  • Author

    Amari, Shun-ichi

  • Author_Institution
    Dept. of Math. Engng. & Instrumentation Phys., Univ. of Tokyo, Tokyo, Japan
  • Issue
    5
  • fYear
    1983
  • Firstpage
    741
  • Lastpage
    748
  • Abstract
    A field theory is proposed as a mathematical method for analyzing learning and self-organizing nerve nets and systems in a unified manner. It is shown by the use of the theory that a nerve net has an ability for automatically forming categorizers or signal detecting cells for the signals which the net receives from its environment. Moreover, when the set of signals has a topological structure, the detectors are arranged in the nerve system (or field) to preserve the topology, so that the topographical structure is introduced in the nerve system by self-organization.
  • Keywords
    brain models; learning systems; neural nets; self-adjusting systems; topology; field theory; self-organizing neural nets; signal detecting cells; Equations; Feature extraction; Mathematical model; Neurons; Organizations; Retina; Vectors;
  • fLanguage
    English
  • Journal_Title
    Systems, Man and Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9472
  • Type

    jour

  • DOI
    10.1109/TSMC.1983.6313068
  • Filename
    6313068