• DocumentCode
    1229274
  • Title

    Generating random bits from an arbitrary source: fundamental limits

  • Author

    Vembu, Sridhar ; Verdu, Sergio

  • Author_Institution
    QualComm Inc., San Diego, CA, USA
  • Volume
    41
  • Issue
    5
  • fYear
    1995
  • fDate
    9/1/1995 12:00:00 AM
  • Firstpage
    1322
  • Lastpage
    1332
  • Abstract
    Suppose we are given a random source and want to use it as a random number generator; at what rate can we generate fair bits from it? We address this question in an information-theoretic setting by allowing for some arbitrarily small but nonzero deviation from “ideal” random bits. We prove our results with three different measures of approximation between the ideal and the obtained probability distributions: the variational distance, the d-bar distance, and the normalized divergence. Two different contexts are studied: fixed-length and variable-length random number generation. The fixed-length results of this paper provide an operational characterization of the inf-entropy rate of a source, defined in Han and Verdu (see ibid., vol.39, no.3, p.752-772, 1993) and the variable-length results characterize the liminf of the entropy rate, thereby establishing a pleasing duality with the fundamental limits of source coding. A feature of our results is that we do not restrict ourselves to ergodic or to stationary sources
  • Keywords
    approximation theory; channel capacity; entropy; information theory; probability; random number generation; source coding; statistical analysis; approximation measures; d-bar distance; entropy rate; ergodic sources; fixed-length random number generation; fundamental limits; information theory; normalized divergence; probability distributions; random bits generation; random number generator; random source; source coding; stationary sources; variable-length random number generation; variational distance; Approximation methods; Computational efficiency; Computer science; Entropy; Probability distribution; Random number generation; Source coding; Statistics; Upper bound;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/18.412679
  • Filename
    412679