(R, S)-Norm Information Measure and A Relation Between Coding and Questionnaire Theory

DOI10.1142/S1230161216500153zbMath1357.94047OpenAlexW2552947143MaRDI QIDQ5298329

Rajesh Joshi, Satish Kumar

Publication date: 14 December 2016

Published in: Open Systems & Information Dynamics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s1230161216500153

zbMATH Keywords

Shannon entropyconvex and concave functions\((R, S)\)-norm information measure\(R\)-norm entropyaverage charge\((R, S)\)-mean codeword length

Mathematics Subject Classification ID

Measures of information, entropy (94A17) Theory of questionnaires (94A50)

Related Items (8)

A new weighted \((\alpha, \beta)\)-norm information measure with application in coding theory ⋮ A new picture fuzzy information measure based on Tsallis-Havrda-Charvat concept with applications in presaging poll outcome ⋮ A new parametric intuitionistic fuzzy entropy and its applications in multiple attribute decision making ⋮ An intuitionistic fuzzy \((\delta , \gamma )\)-norm entropy with its application in supplier selection problem ⋮ Pythagorean fuzzy \((R, S)\)-norm information measure for multicriteria decision-making problem ⋮ An \((R, S)\)-norm information measure for hesitant fuzzy sets and its application in decision-making ⋮ An (\(R\),\(S\))-norm fuzzy information measure with its applications in multiple-attribute decision-making ⋮ Fuzzy Entropy Measure with an Applications in Decision Making Under Bipolar Fuzzy Environment based on TOPSIS Method

Cites Work

• The R-norm information measure
• Heterogeneous Questionnaire Theory
• Variable-length source coding with a cost depending only on the code word length
• Some Coding Theorems Based on Three Types of the Exponential Form of Cost Functions
• A Method for the Construction of Minimum-Redundancy Codes
• A coding theorem and Rényi's entropy

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