2013arXiv (Cornell University)Open access

A new entropy power inequality for integer-valued random variables

Saeid Haghighatshoar, Emmanuel Abbé, Emre Telatar

Open full text 0 citations

Abstract

The entropy power inequality (EPI) provides 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 provides a sharp inequality $H(X+X')-H(X)\geq 1/2 -o(1)$ when $X,X'$ are i.i.d. with high entropy. This paper provides the inequality $H(X+X')-H(X) \geq g(H(X))$, where $X,X'$ are arbitrary i.i.d. integer-valued random variables and where $g$ is a universal strictly positive function on $\mR_+$ satisfying $g(0)=0$. Extensions to non identically distributed random variables and to conditional entropies are also obtained.

Open-access reader

About this research paper

What this paper is about

The entropy power inequality (EPI) provides 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 provides a sharp inequality $H(X+X')-H(X)\geq 1/2 -o(1)$ when $X,X'$ are i.i.d. with high entropy. This paper provides the inequality $H(X+X')-H(X) \geq g(H(X))$, where $X,X'$ are arbitrary i.i.d. integer-valued random variables and where $g$ is a universal strictly positive function on $\mR_+$ satisfying $g(0)=0$. Extensions to non identically distributed random variables and to conditional entropies are also obtained.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The entropy power inequality (EPI) provides 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 provides a sharp inequality $H(X+X')-H(X)\geq 1/2 -o(1)$ when $X,X'$ are i.i.d. with high entropy. This paper provides the inequality $H(X+X')-H(X) \geq g(H(X))$, where $X,X'$ are arbitrary i.i.d. integer-valued random variables and where $g$ is a universal strictly positive function on $\mR_+$ satisfying $g(0)=0$. Extensions to non identically distributed random variables and to conditional entropies are also obtained.

Key concepts: Entropy power inequality, Mathematics, Differential entropy, Random variable, Independent and identically distributed random variables, Conditional entropy, Entropy (arrow of time), Binary entropy function

Related papers

Back to paper searchBrowse research topicsOriginal source
A new entropy power inequality for integer-valued random variables — Research Paper | ScholarLens