New entropy bounds via uniformly convex functions

Yamin Sayyari

Chaos, Solitons & Fractals, 2020, vol. 141, issue C

Abstract: In this paper we give extensions of Jensen’s discrete inequality considering the class of uniformly convex functions. We also introduce lower and upper bounds for Jensen’s inequality (for uniformly convex functions), and we apply this results in information theory and obtain new and strong bounds for Shannon’s entropy of a probability distribution.

Keywords: Shannon’s entropy; Jensen’s inequality; Uniformly convex function; Bounds; Refinements (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:141:y:2020:i:c:s0960077920307554

DOI: 10.1016/j.chaos.2020.110360

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