Title :
Tight Bounds for Symmetric Divergence Measures and a Refined Bound for Lossless Source Coding
Author_Institution :
Dept. of Electr. Eng., Technion - Israel Inst. of Technol., Haifa, Israel
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 two- or three-element probability distributions. An application of these bounds for lossless source coding is provided, refining and improving a certain bound by Csiszár. Another application of these bounds has been recently introduced by Yardi et al. for channel-code detection.
Keywords :
channel coding; source coding; Csiszár; channel code detection; lossless source coding; probability distributions; symmetric divergence measurement; tight bounds; total variation distance; Convex functions; Digital TV; Entropy; Loss measurement; Probability distribution; Source coding; Upper bound; $f$ -divergence; Bhattacharyya distance; Chernoff information; Jeffreys’ divergence; f-divergence; jeffreys??? divergence; lossless source coding; total variation distance;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2014.2387065
