• DocumentCode
    2389997
  • Title

    Principal curves with bounded turn

  • Author

    Sandilya, S. ; Kulkarni, S.R.

  • Author_Institution
    Dept. of Electr. Eng., Princeton Univ., NJ, USA
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    321
  • Abstract
    Principal curves, like principal components, are a tool used in multivariate analysis for ends like feature extraction. Defined in their original form, principal curves need not exist for general distributions. The existence of principal curves with bounded length and a learning algorithm for such curves for any distribution that satisfies some minimal regularity conditions has been shown. We define principal curves with bounded turn, show that they exist, and present a learning algorithm for them
  • Keywords
    feature extraction; information theory; statistical analysis; bounded turn; distribution; feature extraction; learning algorithm; multivariate analysis; principal curves; regularity conditions; Feature extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 2000. Proceedings. IEEE International Symposium on
  • Conference_Location
    Sorrento
  • Print_ISBN
    0-7803-5857-0
  • Type

    conf

  • DOI
    10.1109/ISIT.2000.866619
  • Filename
    866619
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2389997