• DocumentCode
    535307
  • Title

    Local invariant projection

  • Author

    Tan, Lu ; Guo, Hongfeng

  • Author_Institution
    Inst. of Stat. & Math., Shandong Univ. of Finance, Jinan, China
  • Volume
    8
  • fYear
    2010
  • fDate
    16-18 Oct. 2010
  • Firstpage
    3909
  • Lastpage
    3913
  • Abstract
    The paper proposed the method of the local invariant projection for dealing with high-dimensional data sets. The method not only has the nature to maintain the geometry and topology structure of the data sets unchanged in the dimension reduction of the high-dimensional data, but the advantages of convenient and rapid calculation in the linear dimension reduction method. What´s more, the regular treatment made the method has good robustness. The results show that the method has the ability to find out the non-linear structure of the data sets.
  • Keywords
    invariance; signal processing; high dimensional data set; linear dimension reduction method; local invariant projection; topology structure; Eigenvalues and eigenfunctions; Laplace equations; Manifolds; Mathematical model; Nearest neighbor searches; Noise; Principal component analysis; Dimension Reduction; Geometrical Structure; Regularization; Robustness; Topological Structure;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2010 3rd International Congress on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4244-6513-2
  • Type

    conf

  • DOI
    10.1109/CISP.2010.5647620
  • Filename
    5647620