Further Investigations of the Maximum Entropy of the Sum of Two Dependent Random Variables

Jiange Li; James Melbourne

doi:10.1109/ISIT.2018.8437870

Further Investigations of the Maximum Entropy of the Sum of Two Dependent Random Variables

Jiange Li, James Melbourne

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Scopus citations

Abstract

Cover and Zhang proved a certain reversal of the Entropy Power Inequality for the sum of (possibly dependent) random variables possessing the same log-concave density, and what is more that log-concave densities were the only densities that satisfied such an inequality. In this work the authors consider the analogous reversal of recent Renyi Entropy Power Inequalities for random vectors and again show that not only do they hold for s-concave densities, but that s-concave densities are characterized by satisfying said inequalities.

Original language	English (US)
Title of host publication	2018 IEEE International Symposium on Information Theory, ISIT 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1969-1972
Number of pages	4
ISBN (Print)	9781538647806
DOIs	https://doi.org/10.1109/ISIT.2018.8437870
State	Published - Aug 15 2018
Event	2018 IEEE International Symposium on Information Theory, ISIT 2018 - Vail, United States Duration: Jun 17 2018 → Jun 22 2018

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings
Volume	2018-June
ISSN (Print)	2157-8095

Other

Other	2018 IEEE International Symposium on Information Theory, ISIT 2018
Country	United States
City	Vail
Period	6/17/18 → 6/22/18

Keywords

Convex measures
Renyi entropy
Reverse entropy power inequality

Access

10.1109/ISIT.2018.8437870

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Li, J., & Melbourne, J. (2018). Further Investigations of the Maximum Entropy of the Sum of Two Dependent Random Variables. In 2018 IEEE International Symposium on Information Theory, ISIT 2018 (pp. 1969-1972). [8437870] (IEEE International Symposium on Information Theory - Proceedings; Vol. 2018-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2018.8437870

Further Investigations of the Maximum Entropy of the Sum of Two Dependent Random Variables. / Li, Jiange; Melbourne, James.

2018 IEEE International Symposium on Information Theory, ISIT 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1969-1972 8437870 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2018-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Li, J & Melbourne, J 2018, Further Investigations of the Maximum Entropy of the Sum of Two Dependent Random Variables. in 2018 IEEE International Symposium on Information Theory, ISIT 2018., 8437870, IEEE International Symposium on Information Theory - Proceedings, vol. 2018-June, Institute of Electrical and Electronics Engineers Inc., pp. 1969-1972, 2018 IEEE International Symposium on Information Theory, ISIT 2018, Vail, United States, 6/17/18. https://doi.org/10.1109/ISIT.2018.8437870

Li J, Melbourne J. Further Investigations of the Maximum Entropy of the Sum of Two Dependent Random Variables. In 2018 IEEE International Symposium on Information Theory, ISIT 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1969-1972. 8437870. (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.2018.8437870

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