Tight Bounds for Symmetric Divergence Measures and a Refined Bound for Lossless Source Coding
Information Theory
2016-11-17 v7 math.IT
Probability
Abstract
Tight bounds for several symmetric divergence measures are derived in terms of the total variation distance. It is shown that each of these bounds is attained by a pair of 2 or 3-element probability distributions. An application of these bounds for lossless source coding is provided, refining and improving a certain bound by Csisz\'{a}r. Another application of these bounds has been recently introduced by Yardi. et al. for channel-code detection.
Cite
@article{arxiv.1403.7164,
title = {Tight Bounds for Symmetric Divergence Measures and a Refined Bound for Lossless Source Coding},
author = {Igal Sason},
journal= {arXiv preprint arXiv:1403.7164},
year = {2016}
}
Comments
Appears in the IEEE Trans. on Information Theory, February 2015. arXiv admin note: substantial text overlap with arXiv:1502.06428