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research article

A New Entropy Power Inequality for Integer-Valued Random Variables

Haghighatshoar, Saeid  
•
Abbe, Emmanuel  
•
Telatar, I. Emre
2014
Ieee Transactions On Information Theory

The entropy power inequality (EPI) yields lower bounds on the differential entropy of the sum of two independent real-valued random variables in terms of the individual entropies. Versions of the EPI for discrete random variables have been obtained for special families of distributions with the differential entropy replaced by the discrete entropy, but no universal inequality is known (beyond trivial ones). More recently, the sumset theory for the entropy function yields a sharp inequality H(X + X')-H(X) >= H(X) >= 1/2 - o(1) when X, X' are independent identically distributed (i.i.d.) with high entropy. This paper provides the inequality H(X + X') -H(X) >= g(H(X)), where X, X' are arbitrary i.i.d. integer-valued random variables and where g is a universal strictly positive function on R+ satisfying g(0) = 0. Extensions to nonidentically distributed random variables and to conditional entropies are also obtained.

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Type
research article
DOI
10.1109/Tit.2014.2317181
Web of Science ID

WOS:000341982200006

Author(s)
Haghighatshoar, Saeid  
Abbe, Emmanuel  
Telatar, I. Emre
Date Issued

2014

Publisher

Institute of Electrical and Electronics Engineers

Published in
Ieee Transactions On Information Theory
Volume

60

Issue

7

Start page

3787

End page

3796

Subjects

Entropy inequalities

•

entropy power inequality

•

Mrs. Gerber's Lemma

•

doubling constant

•

Shannon sumset theory

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LCM  
Available on Infoscience
October 23, 2014
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/107910
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