• DocumentCode
    659155
  • Title

    Shannon entropy estimation from convergence results in the countable alphabet case

  • Author

    Silva, Jorge F. ; Parada, P.

  • Author_Institution
    Dept. of Electr. Eng., Univ. de Chile, Santiago, Chile
  • fYear
    2013
  • fDate
    9-13 Sept. 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In this paper new results for the Shannon entropy estimation and estimation of distributions, consistently in information divergence, are presented in the countable alphabet case. Sufficient conditions for the entropy convergence are adopted, including scenarios with both finitely and infinitely supported distributions. From this approach, new estimates, strong consistency results and rate of convergences are derived for various plug-in histogram-based schemes.
  • Keywords
    entropy; estimation theory; Shannon entropy estimation; countable alphabet case; entropy convergence; histogram-based scheme; information divergence; Convergence; Entropy; Estimation; Limiting; Loss measurement; Mutual information;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory Workshop (ITW), 2013 IEEE
  • Conference_Location
    Sevilla
  • Print_ISBN
    978-1-4799-1321-3
  • Type

    conf

  • DOI
    10.1109/ITW.2013.6691278
  • Filename
    6691278
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=659155