A Renyi Entropy Power Inequality for Log-Concave Vectors and Parameters in [0, 1]

Arnaud Marsiglietti, James Melbourne

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

11 Scopus citations

Abstract

Using a sharp version of the reverse Young inequality, and a Renyi entropy comparison result due to Fradelizi, Madiman, and Wang, the authors derive a Renyi entropy power inequality for log-concave random vectors when Renyi parameters belong to [0, 1]. A discussion of symmetric decreasing rearrangements of random variables strengthens the inequality and guides the exploration as to its sharpness.

Original languageEnglish (US)
Title of host publication2018 IEEE International Symposium on Information Theory, ISIT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1964-1968
Number of pages5
ISBN (Print)9781538647806
DOIs
StatePublished - Aug 15 2018
Event2018 IEEE International Symposium on Information Theory, ISIT 2018 - Vail, United States
Duration: Jun 17 2018Jun 22 2018

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2018-June
ISSN (Print)2157-8095

Other

Other2018 IEEE International Symposium on Information Theory, ISIT 2018
CountryUnited States
CityVail
Period6/17/186/22/18

Keywords

  • Entropy power inequality
  • Log-concave
  • Renyi entropy

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