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Entropy Measures and Views of Information

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Granular, Soft and Fuzzy Approaches for Intelligent Systems

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 344))

Abstract

Among the countless papers written by Ronald R. Yager, those on Entropies and measures of information are considered, keeping in mind the notion of view of a set, in order to point out a similarity between the quantities introduced in various frameworks to evaluate a kind of entropy. We define the concept of entropy measure and we show that its main characteristic is a form of monotonicity, satisfied by quantities scrutinised by R.R. Yager.

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Notes

  1. 1.

    In the following, for the sake of simplicity, \(w_{x_i}\) will be denoted \(w_i\) when the meaning of i is clear.

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Author information

Authors and Affiliations

  1. Sorbonne Universités, UPMC Univ Paris 06, CNRS, LIP6 UMR 7606, 4 Place Jussieu, 75005, Paris, France

    Bernadette Bouchon-Meunier & Christophe Marsala

Authors
  1. Bernadette Bouchon-Meunier
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  2. Christophe Marsala
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Corresponding author

Correspondence to Bernadette Bouchon-Meunier .

Editor information

Editors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  2. Research and Innovation Center, Ford Motor Company, Dearborn, Michigan, USA

    Dimitar Filev

  3. Deakin University, Burwood, Victoria, Australia

    Gleb Beliakov

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Bouchon-Meunier, B., Marsala, C. (2017). Entropy Measures and Views of Information. In: Kacprzyk, J., Filev, D., Beliakov, G. (eds) Granular, Soft and Fuzzy Approaches for Intelligent Systems. Studies in Fuzziness and Soft Computing, vol 344. Springer, Cham. https://doi.org/10.1007/978-3-319-40314-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-40314-4_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40312-0

  • Online ISBN: 978-3-319-40314-4

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