• DocumentCode
    2252952
  • Title

    Empirical context allocation for multiple dictionary data compression

  • Author

    Franaszek, Peter ; Thomas, Joy

  • Author_Institution
    IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
  • fYear
    1995
  • fDate
    17-22 Sep 1995
  • Firstpage
    15
  • Abstract
    A class of multiple dictionary Lempel-Ziv algorithms is described, where a set of context dependent dictionaries are maintained, and a dictionary chosen based on empirical performance data. These algorithms are conceptually simpler than an earlier approach based on dynamic programming and are also asymptotically optimal
  • Keywords
    data compression; grammars; optimisation; source coding; trees (mathematics); asymptotically optimal algorithms; context dependent dictionaries; empirical context allocation; empirical performance data; multiple dictionary Lempel-Ziv algorithms; multiple dictionary data compression; source coding; Arithmetic; Convergence; Data compression; Decoding; Dictionaries; Dynamic programming; Writing;
  • 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.1995.531117
  • Filename
    531117
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2252952