An entropy functional bounded from above by one
Information Theory
2022-07-26 v3 math.IT
Probability
Statistics Theory
Statistics Theory
Abstract
Shannon entropy is widely used to quantify the uncertainty of discrete random variables. But when normalized to the unit interval, as is often done in practice, it no longer conveys the alphabet sizes of the random variables being studied. This work introduces an entropy functional based on Jensen-Shannon divergence that is naturally bounded from above by one. Unlike normalized Shannon entropy, this new functional is strictly increasing in alphabet size under uniformity and is thus well suited to the characterization of discrete random variables.
Keywords
Cite
@article{arxiv.2204.09723,
title = {An entropy functional bounded from above by one},
author = {John Çamkıran},
journal= {arXiv preprint arXiv:2204.09723},
year = {2022}
}
Comments
6 pages, 1 figure. Minor typographical issues resolved