• DocumentCode
    3037719
  • Title

    Dynamics of clustering multiple backpropagation networks

  • Author

    Lincoln, William P. ; Skrzypek, Josef

  • Author_Institution
    Dept. of Comput. Sci., California Univ., Los Angeles, CA, USA
  • fYear
    1990
  • fDate
    4-7 Nov 1990
  • Firstpage
    385
  • Lastpage
    386
  • Abstract
    It is known that synergistic effects of clustering multiple backpropagation nets improves supervised learning, generalization, fault tolerance, and self-organization with respect to a comparably complex nonclustered system. A model that captures the underlying reasons for the synergy of clustering is outlined. The underlying ideas can apply to any net trained with a supervised learning rule
  • Keywords
    dynamics; learning systems; neural nets; clustering multiple backpropagation networks; dynamics; fault tolerance; learning systems; neural nets; self-organization; supervised learning rule; Backpropagation; Computer science; Convergence; Degradation; Error correction; Fault tolerance; Fault tolerant systems; Laboratories; Supervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 1990. Conference Proceedings., IEEE International Conference on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    0-87942-597-0
  • Type

    conf

  • DOI
    10.1109/ICSMC.1990.142134
  • Filename
    142134