A new weighted (α,β)-norm information measure with application in coding theory

Rajesh Joshi and Satish Kumar

Physica A: Statistical Mechanics and its Applications, 2018, vol. 510, issue C, 538-551

Abstract: In the present communication, we introduce a quantity which is called weighted (α,β)-norm entropy and discuss its some major properties with Shannon and other entropies in the literature. Corresponding to the proposed entropy, a new weighted directed divergence measure has been introduced and its validity is established. Further, we give the application of (α,β)-norm entropy in coding theory and a coding theorem analogous to the ordinary coding theorem for a noiseless channel has been proved. The theorem states that the proposed entropy is the lower bound of mean code word length.

Keywords: α-norm entropy; Shannon’s entropy; Convex and concave function; (α,β)-norm information measure; (α,β)-norm directed divergence measure; Mean codeword length (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:510:y:2018:i:c:p:538-551

DOI: 10.1016/j.physa.2018.07.015

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