• DocumentCode
    2937801
  • Title

    Maximum mutual information vector quantization

  • Author

    Wilcox, Lynn D. ; Niles, Les T.

  • Author_Institution
    Xerox PARC, Palo Alto, CA, USA
  • fYear
    1995
  • fDate
    17-22 Sep 1995
  • Firstpage
    434
  • Abstract
    A method is proposed for designing a maximum mutual information (MMI) vector quantizer, for applications in which quantization is used to extract a set of discrete features for use in classification
  • Keywords
    vector quantisation; feature classification; feature extraction; maximum mutual information; vector quantization; Data mining; Distortion measurement; Entropy; Euclidean distance; Feature extraction; Mutual information; Training data; Vector quantization; Yield estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 1995. Proceedings., 1995 IEEE International Symposium on
  • Conference_Location
    Whistler, BC
  • Print_ISBN
    0-7803-2453-6
  • Type

    conf

  • DOI
    10.1109/ISIT.1995.550421
  • Filename
    550421
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2937801