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Symmetry 2011, 3(3), 487-502; doi:10.3390/sym3030487
Article

Classifying Entropy Measures

Received: 27 April 2011; in revised form: 6 July 2011 / Accepted: 6 July 2011 / Published: 20 July 2011
(This article belongs to the Special Issue Symmetry Measures on Complex Networks)
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Abstract: Our paper analyzes some aspects of Uncertainty Measures. We need to obtain new ways to model adequate conditions or restrictions, constructed from vague pieces of information. The classical entropy measure originates from scientific fields; more specifically, from Statistical Physics and Thermodynamics. With time it was adapted by Claude Shannon, creating the current expanding Information Theory. However, the Hungarian mathematician, Alfred Rényi, proves that different and valid entropy measures exist in accordance with the purpose and/or need of application. Accordingly, it is essential to clarify the different types of measures and their mutual relationships. For these reasons, we attempt here to obtain an adequate revision of such fuzzy entropy measures from a mathematical point of view.
Keywords: mathematical analysis; measure theory; fuzzy systems; information theory mathematical analysis; measure theory; fuzzy systems; information theory
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Garrido, A. Classifying Entropy Measures. Symmetry 2011, 3, 487-502.

AMA Style

Garrido A. Classifying Entropy Measures. Symmetry. 2011; 3(3):487-502.

Chicago/Turabian Style

Garrido, Angel. 2011. "Classifying Entropy Measures." Symmetry 3, no. 3: 487-502.


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