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Research PapersNo Access

MAXIMIZABLE INFORMATIONAL ENTROPY AS A MEASURE OF PROBABILISTIC UNCERTAINTY

Institut Supérieur des Matériaux et Mécaniques Avancés du Mans, 44, Avenue F.A. Bartholdi, 72000 Le Mans, France

College of Information Science and Engineering, Huaqiao University, Quanzhou 362021, China

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,

AZIZ EL KAABOUCHI

Institut Supérieur des Matériaux et Mécaniques Avancés du Mans, 44, Avenue F.A. Bartholdi, 72000 Le Mans, France

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,

LAURENT NIVANEN

Institut Supérieur des Matériaux et Mécaniques Avancés du Mans, 44, Avenue F.A. Bartholdi, 72000 Le Mans, France

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,

Institut Supérieur des Matériaux et Mécaniques Avancés du Mans, 44, Avenue F.A. Bartholdi, 72000 Le Mans, France

Department of Physics and Institute of Theoretical Physics and Astrophysics, Xiamen University, Xiamen 361005, China

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,

FRANOIS TSOBNANG

Institut Supérieur des Matériaux et Mécaniques Avancés du Mans, 44, Avenue F.A. Bartholdi, 72000 Le Mans, France

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,

ALAIN LE MÉHAUTÉ

Institut Supérieur des Matériaux et Mécaniques Avancés du Mans, 44, Avenue F.A. Bartholdi, 72000 Le Mans, France

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, and

QIUPING A. WANG

Institut Supérieur des Matériaux et Mécaniques Avancés du Mans, 44, Avenue F.A. Bartholdi, 72000 Le Mans, France

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https://doi.org/10.1142/S0217979210054713Cited by:6 (Source: Crossref)

Abstract

In this work, we consider a recently proposed entropy S defined by a variational relationship as a measure of uncertainty of random variable x. The entropy defined in this way underlies an extension of virtual work principle leading to the maximum entropy . This paper presents an analytical investigation of this maximizable entropy for several distributions such as the stretched exponential distribution, κ-exponential distribution, and Cauchy distribution.

Keywords:

PACS: 05.20.-y, 02.50.-r, 02.50.Tt

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Vol. 24, No. 17

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Received 4 November 2008

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