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Exponential Entropy for Simplified Neutrosophic Sets and Its Application in Decision Making

open access: yesEntropy, 2018
Entropy is one of many important mathematical tools for measuring uncertain/fuzzy information. As a subclass of neutrosophic sets (NSs), simplified NSs (including single-valued and interval-valued NSs) can describe incomplete, indeterminate, and ...
Jun Ye, Wenhua Cui
doaj   +1 more source

On Entropy of Some Fractal Structures

open access: yesFractal and Fractional, 2023
Shannon entropy, also known as information entropy or entropy, measures the uncertainty or randomness of probability distribution. Entropy is measured in bits, quantifying the average amount of information required to identify an event from the ...
Haleemah Ghazwani   +3 more
doaj   +1 more source

New Estimates of the Kullback-Leibler Distance and Applications [PDF]

open access: yes, 2000
New estimates of the Kullback-Leibler distance and applications for Shannon’s entropy and mutual information are ...
Dragomir, Sever S   +2 more
core   +3 more sources

The meanings of entropy

open access: yesEntropy, 2005
: Entropy is a basic physical quantity that led to various, and sometimes apparently conflicting interpretations. It has been successively assimilated to different concepts such as disorder and information.
Jean-Bernard Brissaud
doaj   +1 more source

Rényi Entropies of Dynamical Systems: A Generalization Approach [PDF]

open access: yesJournal of Mahani Mathematical Research, 2023
Entropy measures have received considerable attention in quantifying the structural complexity of real-world systems and are also used as measures of information obtained from a realization of the considered experiments. In the present study, new notions
Zahra Eslami Giski   +2 more
doaj   +1 more source

Information Entropy Measure for Evaluation of Image Quality [PDF]

open access: yesJournal of Digital Imaging, 2007
This paper presents a simple and straightforward method for synthetically evaluating digital radiographic images by a single parameter in terms of transmitted information (TI). The features of our proposed method are (1) simplicity of computation, (2) simplicity of experimentation, and (3) combined assessment of image noise and resolution (blur).
Du-Yih Tsai, Yongbum Lee, Eri Matsuyama
openaire   +2 more sources

MAXIMIZABLE INFORMATIONAL ENTROPY AS A MEASURE OF PROBABILISTIC UNCERTAINTY [PDF]

open access: yesInternational Journal of Modern Physics B, 2010
In this work, we consider a recently proposed entropy S defined by a variational relationship [Formula: see text] as a measure of uncertainty of random variable x. The entropy defined in this way underlies an extension of virtual work principle [Formula: see text] leading to the maximum entropy [Formula: see text].
Ou, C. J.   +6 more
openaire   +4 more sources

The Information Loss of a Stochastic Map

open access: yesEntropy, 2021
We provide a stochastic extension of the Baez–Fritz–Leinster characterization of the Shannon information loss associated with a measure-preserving function. This recovers the conditional entropy and a closely related information-theoretic measure that we
James Fullwood, Arthur J. Parzygnat
doaj   +1 more source

Entropy Region and Network Information Theory [PDF]

open access: yes, 2011
This dissertation takes a step toward a general framework for solving network information theory problems by studying the capacity region of networks through the entropy region.
Sormeh Shadbakht, Shadbakht, Sormeh
core   +1 more source

Entropy Measures of Probabilistic Linguistic Term Sets

open access: yesInternational Journal of Computational Intelligence Systems, 2018
The probabilistic linguistic term sets (PLTSs) are powerful to deal with the hesitant linguistic situation in which each provided linguistic term has a probability.
Hongbin Liu, Le Jiang, Zeshui Xu
doaj   +1 more source

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