• DocumentCode
    527493
  • Title

    A novel DoubleMinOver classifier based On second-order tensor

  • Author

    Wang, Zhe ; Han, Rui ; Pan, Zhisong ; Ni, Xuelei

  • Author_Institution
    Dept. of Comput. Sci. & Eng., East China Univ. of Sci. & Technol., Shanghai, China
  • Volume
    2
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    1053
  • Lastpage
    1057
  • Abstract
    It is well-known that the DoubleMinOver classifier as an extendibility of MinOver was developed to provide a maximum margin solution with a bias. But, it can be found that the DoubleMinOver algorithm only classifies the vector pattern and fails to work in the pattern represented with the second-order tensor. In this paper, we propose a novel DoubleMinOver classifier named STDoubleMinOver that can directly classify the second-order tensor pattern. Compared with the existing DoubleMinOver with only one weight w, the proposed STDoubleMinOver induces two weight vectors u and v so as to deal with the second-order tensor. The experiments here have demonstrated that the proposed STDoubleMinOver has a superior classification to the vectorized DoubleMinOver.
  • Keywords
    feature extraction; neural nets; pattern classification; STDoubleMinOver; doubleminover classifier; second-order tensor; Accuracy; Artificial neural networks; Feature extraction; Iris; Lenses; Tensile stress; Training; Classifier Design; DoubleMinOver; Second-order Tensor; Vector Pattern;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5582980
  • Filename
    5582980