A Survey of Reverse Inequalities for f-Divergence Measure in Information Theory

S. S. Dragomir ()
Additional contact information
S. S. Dragomir: Victoria University, School of Engineering and Science

A chapter in Computation, Cryptography, and Network Security, 2015, pp 209-251 from Springer

Abstract: Abstract In this paper we survey some discrete inequalities for the f-divergence measure in Information Theory by the use of recent reverses of the celebrated Jensen’s inequality. Applications in connection with Hölder’s inequality and for particular measures such as Kullback–Leibler divergence measure, Hellinger discrimination, χ 2-distance and variation distance are provided as well.

Keywords: Convex functions; Jensen’s inequality; Reverse of Jensen’s inequality; Reverse of Hölder’s inequality; f-Divergence measure; Kullback–Leibler divergence measure; Hellinger discrimination; χ 2-Distance; Variation distance; Grüss’ type inequality (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-18275-9_9

Ordering information: This item can be ordered from
http://www.springer.com/9783319182759

DOI: 10.1007/978-3-319-18275-9_9

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().