On Reverse Pinsker Inequalities
Abstract
New upper bounds on the relative entropy are derived as a function of the total variation distance. One bound refines an inequality by Verd\'{u} for general probability measures. A second bound improves the tightness of an inequality by Csisz\'{a}r and Talata for arbitrary probability measures that are defined on a common finite set. The latter result is further extended, for probability measures on a finite set, leading to an upper bound on the R\'{e}nyi divergence of an arbitrary non-negative order (including ) as a function of the total variation distance. Another lower bound by Verd\'{u} on the total variation distance, expressed in terms of the distribution of the relative information, is tightened and it is attained under some conditions. The effect of these improvements is exemplified.
Keywords
Cite
@article{arxiv.1503.07118,
title = {On Reverse Pinsker Inequalities},
author = {Igal Sason},
journal= {arXiv preprint arXiv:1503.07118},
year = {2015}
}
Comments
Version 3 has been submitted to the IEEE Trans. on Information Theory, March 2015. Version 4 includes a refinement of the inequalities in Theorems 3 and 4 with a new appendix that is included for this purpose, and a revision of Section III-B (in respect to these latter refinements). There is a text overlap with arXiv:1503.03417 and 1502.06428