• DocumentCode
    303226
  • Title

    About perceptron realizations of Bayesian decisions

  • Author

    Vajda, I.

  • Author_Institution
    Inst. of Inf. Theory & Autom., Prague, Czech Republic
  • Volume
    1
  • fYear
    1996
  • fDate
    3-6 Jun 1996
  • Firstpage
    253
  • Abstract
    It is shown that one can imitate the Bayesian discrimination and classification of exponentially distributed random signals by the perceptrons with one hidden layer. The number of unknown weights just by 2 exceeds the number of parameters figuring in the exponential distribution. Learning is thus relatively easy
  • Keywords
    Bayes methods; Bayesian decisions; Bayesian discrimination; classification; exponentially distributed random signals; perceptron realizations; Acoustics; Bayesian methods; Computer aided analysis; Content addressable storage; Feature extraction; Information theory; Linearity; Random processes; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1996., IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-7803-3210-5
  • Type

    conf

  • DOI
    10.1109/ICNN.1996.548900
  • Filename
    548900
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=303226