• DocumentCode
    2617082
  • Title

    Implementing the fuzzy quadratic classifier

  • Author

    Kersten, Paul R.

  • Author_Institution
    Weapons Div., Naval Air Warfare Center, China Lake, CA, USA
  • fYear
    1997
  • fDate
    21-24 Sep 1997
  • Firstpage
    205
  • Lastpage
    210
  • Abstract
    The fuzzy quadratic classifier (FQC) extends the quadratic classifier to accommodate a sequence of fuzzy numbers as data. The fuzzy data induces a fuzzy quadratic discriminant (QD) that is then compared to other fuzzy discriminants to produce a decision. To generate the fuzzy data, conversion of batches of data vectors, or signals, into sequences of fuzzy signal vectors is developed base on fuzzy order statistics. In data rich environment, this conversion both condenses and refines the data stream. An efficient implementation of the FQC is presented based upon a diagonal form of the quadratic classifier and robust estimation of the parameters. A two class problem illustrates the procedure
  • Keywords
    decision theory; estimation theory; fuzzy set theory; parameter estimation; pattern classification; data vectors; decision; diagonal form; fuzzy discriminants; fuzzy numbers; fuzzy quadratic classifier; fuzzy quadratic discriminant; quadratic classifier; robust estimation; Additive noise; Gaussian distribution; Gaussian noise; Lakes; Noise robustness; Parameter estimation; Signal generators; Statistics; Target recognition; Weapons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society, 1997. NAFIPS '97., 1997 Annual Meeting of the North American
  • Conference_Location
    Syracuse, NY
  • Print_ISBN
    0-7803-4078-7
  • Type

    conf

  • DOI
    10.1109/NAFIPS.1997.624038
  • Filename
    624038