• DocumentCode
    3424570
  • Title

    Possibilistic C-Spherical Shell clustering algorithm based on conformai geometric algebra

  • Author

    Li Maokuan ; Guan Jian

  • Author_Institution
    Dept. of Electron. & Inf. Eng., Naval Aeronaut. & Astronaut. Univ., Yantai, China
  • fYear
    2010
  • fDate
    24-28 Oct. 2010
  • Firstpage
    1347
  • Lastpage
    1350
  • Abstract
    In this paper, a new Possibilistic C-Spherical Shell clustering (PCSS) algorithm based on conformal geometric algebra is proposed. The probability and simplicity of using the conformal geometric algebra to analyse spherical shell clustering algorithm is discussed firstly. By the conformal geometric algebra theory, patterns and prototypes in spherical shell clustering can be represented as vectors, then the objective function for clustering analysis can be expressed effectively, and a new solution to minimize the objective function is deduced. The experimental results show that the proposed algorithm can cluster the spherical shell data effectively, and is robust for noise.
  • Keywords
    algebra; pattern clustering; possibility theory; clustering analysis; conformal geometric algebra theory; objective function; possibilistic c-spherical shell clustering algorithm; spherical shell clustering algorithm; spherical shell data; Algebra; Algorithm design and analysis; Clustering algorithms; Partitioning algorithms; Pattern recognition; Prototypes; Silicon; Pattern Recognition; Possibilistic C-Spherical Shell Clustering; conformai geometric algebra;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing (ICSP), 2010 IEEE 10th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-5897-4
  • Type

    conf

  • DOI
    10.1109/ICOSP.2010.5656991
  • Filename
    5656991