Published June 2018 | Version public
Book Section - Chapter

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

  • 1. ROR icon California Institute of Technology
  • 2. ROR icon University of Minnesota

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.

Additional Information

© 2018 IEEE. Supported by the Walter S. Baer and Jeri Weiss CMI Postdoctoral Fellowship. Supported by NSF grants 1248100 and CNS 1544721.

Additional details

Identifiers

Eprint ID
91195
DOI
10.1109/ISIT.2018.8437877
Resolver ID
CaltechAUTHORS:20181126-153826742

Related works

Funding

Center for the Mathematics of Information, Caltech
NSF
CCF-1248100
NSF
CNS-1544721

Dates

Created
2018-11-27
Created from EPrint's datestamp field
Updated
2021-11-16
Created from EPrint's last_modified field