• DocumentCode
    3334218
  • Title

    Pattern recognition properties of neural networks

  • Author

    Makhoul, John

  • Author_Institution
    BBN Syst. & Technol., Cambridge, MA, USA
  • fYear
    1991
  • fDate
    30 Sep-1 Oct 1991
  • Firstpage
    173
  • Lastpage
    187
  • Abstract
    Artificial neural networks have been applied largely to solving pattern recognition problems. The authors point out that a firm understanding of the statistical properties of neural nets is important for using them in an effective manner for pattern recognition problems. The author gives an overview of pattern recognition properties for feedforward neural nets, with emphasis on two topics: partitioning of the input space into classes and the estimation of posterior probabilities for each of the classes
  • Keywords
    feedforward neural nets; pattern recognition; feedforward neural nets; neural networks; pattern recognition; Artificial neural networks; Feedforward neural networks; Humans; Mirrors; Neural networks; Pattern analysis; Pattern recognition; Probability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks for Signal Processing [1991]., Proceedings of the 1991 IEEE Workshop
  • Conference_Location
    Princeton, NJ
  • Print_ISBN
    0-7803-0118-8
  • Type

    conf

  • DOI
    10.1109/NNSP.1991.239524
  • Filename
    239524