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Open AccessArticle

Point Divergence Gain and Multidimensional Data Sequences Analysis

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Institute of Complex Systems, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Kompetenzzentrum MechanoBiologie in Regenerativer Medizin, Faculty of Fisheries and Protection of Waters, University of South Bohemia in České Budějovice, Zámek 136, 373 33 Nové Hrady, Czech Republic
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Section for Science of Complex Systems, CeMSIIS, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria
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Complexity Science Hub Vienna, Josefstädter Strasse 39, 1080 Vienna, Austria
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Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Břehová 7, 115 19 Prague, Czech Republic
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Author to whom correspondence should be addressed.
Entropy 2018, 20(2), 106; https://doi.org/10.3390/e20020106
Received: 27 December 2017 / Revised: 28 January 2018 / Accepted: 30 January 2018 / Published: 3 February 2018
(This article belongs to the Section Information Theory, Probability and Statistics)
We introduce novel information-entropic variables—a Point Divergence Gain ( Ω α ( l m ) ), a Point Divergence Gain Entropy ( I α ), and a Point Divergence Gain Entropy Density ( P α )—which are derived from the Rényi entropy and describe spatio-temporal changes between two consecutive discrete multidimensional distributions. The behavior of Ω α ( l m ) is simulated for typical distributions and, together with I α and P α , applied in analysis and characterization of series of multidimensional datasets of computer-based and real images. View Full-Text
Keywords: point divergence gain (PDG); Rényi entropy; data processing point divergence gain (PDG); Rényi entropy; data processing
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MDPI and ACS Style

Rychtáriková, R.; Korbel, J.; Macháček, P.; Štys, D. Point Divergence Gain and Multidimensional Data Sequences Analysis. Entropy 2018, 20, 106.

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