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Research Article Open access CC BY 4.0

On Parametric Generalization of ‘Useful’ R-norm Information Measure

D. S. Hooda, Keerti Upadhyay, D. K. Sharma

Journal of Advances in Mathematics and Computer Science · pp. 1–15 · Published 4 Mar 2015

10.9734/BJMCS/2015/14791

Abstract

In the literature of information measure, there exist many well known parametric generalized information measures with their merits and limitations. In the present paper a ‘useful’ R-norm information measure of type and degree is introduce and characterized axiomatically. This new measure is parametric generalization of ‘useful’ R-norm information measures introduced and characterized by the authors earlier refer to Hooda et al. [11]. Properties of the new generalized ‘useful’ R-norm information measure of type and degree have also been studied. The new measure has been applied in studying the lower and upper bounds of a generalized ‘useful’ R-norm mean codeword length.

R-norm information mean codeword length Kraft’s inequality code alphabets and Holder’s inequality

Cited by 3

On ‘Useful’ R-norm Relative Information Measures and Applications

D. S. Hooda, D. K. Sharma · Oriental Journal of Physical Sciences · 2022

Slotting Learning Rate in Deep Neural Networks to Build Stronger Models

Dilip Kumar Sharma, Bhopendra Singh, Mamoona Anam · 2021 2nd International Conference on Smart Electronics and Communication (ICOSEC) · 2021

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