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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jog, V. Anantharam, V. |
| Copyright Year | 2013 |
| Description | Author affiliation: EECS, UC Berkeley, Berkeley, CA, USA (Jog, V.; Anantharam, V.) |
| Abstract | Shannon's Entropy Power Inequality (EPI) can be viewed as characterizing the minimum differential entropy achievable by the sum of two independent random variables with fixed differential entropies. The EPI is a powerful tool and has been used to resolve a number of problems in information theory. In this paper we examine the existence of a similar entropy inequality for discrete random variables. We obtain an entropy power inequality for random variables taking values in any group of order $2^{n},$ i.e. for such a group G we explicitly characterize the function $f_{G}(x,$ y) giving the minimum entropy of the group product of two independent G-valued random variables with respective entropies x and y. Random variables achieving the extremum in this inequality are thus the analogs of Gaussians, and these are also determined. It turns out that $f_{G}(x,$ y) is convex in x for fixed y and, by symmetry, convex in y for fixed x. This is a generalization to groups of order $2^{n}$ of the result known as Mrs. Gerber's Lemma. |
| Starting Page | 594 |
| Ending Page | 598 |
| File Size | 140555 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781479904464 |
| ISSN | 21578117 |
| DOI | 10.1109/ISIT.2013.6620295 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-07-07 |
| Publisher Place | Turkey |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Entropy Random variables Information theory Electronic mail Covariance matrices Equations Convolution Finite groups Entropy power inequality Mrs. Gerber's Lemma |
| Content Type | Text |
| Resource Type | Article |
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