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Entropy 2016, 18(10), 372; doi:10.3390/e18100372

Point Information Gain and Multidimensional Data Analysis

1
Institute of Complex Systems, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Faculty of Fisheries and Protection of Waters (FFWP), University of South Bohemia in České Budějovice, Zámek 136, Nové Hrady 373 33, Czech Republic
2
Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Břehová 7, Prague 155 19, Czech Republic
*
Author to whom correspondence should be addressed.
Academic Editor: Kevin H. Knuth
Received: 1 August 2016 / Revised: 17 September 2016 / Accepted: 14 October 2016 / Published: 19 October 2016
(This article belongs to the Section Information Theory)
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Abstract

We generalize the point information gain (PIG) and derived quantities, i.e., point information gain entropy (PIE) and point information gain entropy density (PIED), for the case of the Rényi entropy and simulate the behavior of PIG for typical distributions. We also use these methods for the analysis of multidimensional datasets. We demonstrate the main properties of PIE/PIED spectra for the real data with the examples of several images and discuss further possible utilizations in other fields of data processing. View Full-Text
Keywords: point information gain (PIG); Rényi entropy; data processing point information gain (PIG); Rényi entropy; data processing
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MDPI and ACS Style

Rychtáriková, R.; Korbel, J.; Macháček, P.; Císař, P.; Urban, J.; Štys, D. Point Information Gain and Multidimensional Data Analysis. Entropy 2016, 18, 372.

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