On Data-Processing and Majorization Inequalities for <i>f</i>-Divergences with Applications
This paper is focused on the derivation of data-processing and majorization inequalities for <i>f</i>-divergences, and their applications in information theory and statistics. For the accessibility of the material, the main results are first introduced without proofs, followed by exempli...
Main Author: | Igal Sason |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-10-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/21/10/1022 |
Similar Items
-
Tight Bounds on the Rényi Entropy via Majorization with Applications to Guessing and Compression
by: Igal Sason
Published: (2018-11-01) -
A Direct Link between Rényi–Tsallis Entropy and Hölder’s Inequality—Yet Another Proof of Rényi–Tsallis Entropy Maximization
by: Hisa-Aki Tanaka, et al.
Published: (2019-05-01) -
Refinement of Jensen’s inequality and estimation of f- and Rényi divergence via Montgomery identity
by: Khuram Ali Khan, et al.
Published: (2018-11-01) -
On Relations Between the Relative Entropy and <em>χ</em><sup>2</sup>-Divergence, Generalizations and Applications
by: Tomohiro Nishiyama, et al.
Published: (2020-05-01) -
Inequalities for Information Potentials and Entropies
by: Ana Maria Acu, et al.
Published: (2020-11-01)