On additive-combinatorial affine inequalities for Shannon entropy and differential entropy

Ashok Vardhan Makkuva, Yihong Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To be considered for the 2016 IEEE Jack Keil Wolf ISIT Student Paper Award. This paper addresses the question of to what extent do discrete entropy inequalities for weighted sums of independent group-valued random variables continue to hold for differential entropies. We show that all balanced affine inequalities (with the sum of coefficients being zero) of Shannon entropy extend to differential entropy; conversely, any affine inequality for differential entropy must be balanced. In particular, this result recovers recently proved differential entropy inequalities by Kontoyiannis and Madiman [1] from their discrete counterparts due to Tao [2] in a unified manner. Our proof relies on a result of Rényi which relates the Shannon entropy of a finely discretized random variable to its differential entropy and also helps in establishing the entropy of the sum of quantized random variables is asymptotically equal to that of the quantized sum.

Original languageEnglish (US)
Title of host publicationProceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1053-1057
Number of pages5
ISBN (Electronic)9781509018062
DOIs
StatePublished - Aug 10 2016
Event2016 IEEE International Symposium on Information Theory, ISIT 2016 - Barcelona, Spain
Duration: Jul 10 2016Jul 15 2016

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2016-August
ISSN (Print)2157-8095

Other

Other2016 IEEE International Symposium on Information Theory, ISIT 2016
Country/TerritorySpain
CityBarcelona
Period7/10/167/15/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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