• DocumentCode
    67612
  • Title

    On the Conditional Rényi Entropy

  • Author

    Fehr, Serge ; Berens, Stefan

  • Author_Institution
    Wiskunde & Inf., Amsterdam, Netherlands
  • Volume
    60
  • Issue
    11
  • fYear
    2014
  • fDate
    Nov. 2014
  • Firstpage
    6801
  • Lastpage
    6810
  • Abstract
    The Rényi entropy of general order unifies the well-known Shannon entropy with several other entropy notions, like the min-entropy or collision entropy. In contrast to the Shannon entropy, there seems to be no commonly accepted definition for the conditional Rényi entropy: several versions have been proposed and used in the literature. In this paper, we reconsider the definition for the conditional Rényi entropy of general order as proposed by Arimoto in the seventies. We show that this particular notion satisfies several natural properties. In particular, we show that it satisfies monotonicity under conditioning, meaning that conditioning can only reduce the entropy, and (a weak form of) chain rule, which implies that the decrease in entropy due to conditioning is bounded by the number of bits one conditions on. None of the other suggestions for the conditional Rényi entropy satisfies both these properties. Finally, we show a natural interpretation of the conditional Rényi entropy in terms of (unconditional) Rényi divergence, and we show consistency with a recently proposed notion of conditional Rényi entropy in the quantum setting.
  • Keywords
    minimum entropy methods; Rényi divergence; Shannon entropy; collision entropy; conditional Rényi entropy; minentropy entropy; quantum setting; Biomedical measurement; Entropy; Information theory; Joints; Measurement uncertainty; Random variables; Uncertainty; Conditial R??nyi entropy; R??nyi divergence; monotonicity and chain rule; quantum R??nyi entropy;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2014.2357799
  • Filename
    6898022