DocumentCode
1343220
Title
A tight upper bound on discrete entropy
Author
Mow, Wai Ho
Author_Institution
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
Volume
44
Issue
2
fYear
1998
fDate
3/1/1998 12:00:00 AM
Firstpage
775
Lastpage
778
Abstract
The standard upper bound on discrete entropy was derived based on the differential entropy bound for continuous random variables. A tighter discrete entropy bound is derived using the transformation formula of Jacobi theta function. The new bound is applicable only when the probability mass function of the discrete random variable satisfies certain conditions. Its application to the class of binomial random variables is presented as an example
Keywords
entropy; functional equations; probability; random processes; Jacobi theta function; binomial random variables; continuous random variables; differential entropy bound; discrete entropy; discrete random variable; probability mass function; tight upper bound; transformation formula; Entropy; Information theory; Jacobian matrices; Random variables; Upper bound;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.661519
Filename
661519
Link To Document