• DocumentCode
    327665
  • Title

    A new robust quadratic discriminant function

  • Author

    Sakai, Mitsuru ; Yoneda, Masaaki ; Hase, Hiroyuki

  • Author_Institution
    Fac. of Eng., Toyama Univ., Japan
  • Volume
    1
  • fYear
    1998
  • fDate
    16-20 Aug 1998
  • Firstpage
    99
  • Abstract
    We propose a new quadratic discriminant function. It is devised based on the fact that eigenvalues of a sample covariance matrix are biased estimates of true eigenvalues. First, we rectify the biased eigenvalues. Then we construct a new covariance matrix whose eigenvalues are the rectified ones. Our quadratic discriminant function uses the covariance matrix. In a two-dimensional normal case, we show by a Monte Carlo method that our discriminant function works effectively, especially in the case of a small sample size
  • Keywords
    covariance matrices; eigenvalues and eigenfunctions; normal distribution; pattern recognition; Monte Carlo method; biased estimates; eigenvalues; robust quadratic discriminant function; sample covariance matrix; Covariance matrix; Eigenvalues and eigenfunctions; Estimation error; Gaussian distribution; Parameter estimation; Performance analysis; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
  • Conference_Location
    Brisbane, Qld.
  • ISSN
    1051-4651
  • Print_ISBN
    0-8186-8512-3
  • Type

    conf

  • DOI
    10.1109/ICPR.1998.711089
  • Filename
    711089