• DocumentCode
    1983034
  • Title

    2D-CCA based on pseudoinverse technique

  • Author

    Wu, Xiao-jun

  • Author_Institution
    Sch. of Inf. Eng., Jiangnan Univ., Wuxi
  • fYear
    2009
  • fDate
    11-13 May 2009
  • Firstpage
    277
  • Lastpage
    280
  • Abstract
    The recently proposed 2D-CCA is an important method for high dimensional data representation. The mathematical model of 2D-CCA based on pseudoinverse technique is investigated. The computational formulae for 2D-CCA based on pseudoinverse have been derived theoretically. The results of experiments show that the proposed method is effective for the computation of 2D-CCA.
  • Keywords
    correlation methods; data structures; statistics; 2D-CCA; canonical correlation analysis; data representation; mathematical model; pseudoinverse technique; Computational intelligence; Data analysis; Eigenvalues and eigenfunctions; Feature extraction; Information retrieval; Mathematical model; Pattern recognition; Statistics; Vectors; Yttrium; 2D-CCA; CCA; feature extraction; pattern recognition; pseudoinverse;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Measurement Systems and Applications, 2009. CIMSA '09. IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-3819-8
  • Electronic_ISBN
    978-1-4244-3820-4
  • Type

    conf

  • DOI
    10.1109/CIMSA.2009.5069965
  • Filename
    5069965