MAXIMIZABLE INFORMATIONAL ENTROPY AS A MEASURE OF PROBABILISTIC UNCERTAINTY.

Autor: CONGJIE OU, EL KAABOUCHI, AZIZ, NIVANEN, LAURENT, CHEN, JINCAN, TSOBNANG, FRANOIS, LE MÉHAUTÉ, ALAIN, WANG, QIUPING A.
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Zdroj: International Journal of Modern Physics B: Condensed Matter Physics; Statistical Physics; Applied Physics; 7/10/2010, Vol. 24 Issue 17, p3461-3468, 8p, 1 Graph
Abstrakt: In this work, we consider a recently proposed entropy S defined by a variational relationship $dI=d\bar{x}-\overline{dx}$ as a measure of uncertainty of random variable x. The entropy defined in this way underlies an extension of virtual work principle $\overline{dx}=0$ leading to the maximum entropy $d(I-\bar x)=0$. 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. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index