• DocumentCode
    928598
  • Title

    Some equivalences between Shannon entropy and Kolmogorov complexity

  • Author

    Leung-Yan-Cheong, Sik K. ; Cover, Thomas M.

  • Volume
    24
  • Issue
    3
  • fYear
    1978
  • fDate
    5/1/1978 12:00:00 AM
  • Firstpage
    331
  • Lastpage
    338
  • Abstract
    It is known that the expected codeword length L_{UD} of the best uniquely decodable (UD) code satisfies H(X)\\leqL_{UD}< H(X)+1 . Let X be a random variable which can take on n values. Then it is shown that the average codeword length L_{1:1} for the best one-to-one (not necessarily uniquely decodable) code for X is shorter than the average codeword length L_{UD} for the best uniquely decodable code by no more than (\\log _{2} \\log _{2} n)+ 3 . Let Y be a random variable taking on a finite or countable number of values and having entropy H . Then it is proved that L_{1:1}\\geq H-\\log _{2}(H + 1)-\\log _{2}\\log _{2}(H + 1 )-\\cdots -6 . Some relations are established among the Kolmogorov, Chaitin, and extension complexities. Finally it is shown that, for all computable probability distributions, the universal prefix codes associated with the conditional Chaitin complexity have expected codeword length within a constant of the Shannon entropy.
  • Keywords
    Coding; Entropy functions; Concatenated codes; Decoding; Distributed computing; Encoding; Entropy; Information theory; Probability distribution; Random variables; Statistics;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.1978.1055891
  • Filename
    1055891