Point Divergence Gain and Multidimensional Data Sequences Analysis
Renata Rychtáriková,
Jan Korbel,
Petr Macháček,
Dalibor Štys
Affiliations
Renata Rychtáriková
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
Jan Korbel
Section for Science of Complex Systems, CeMSIIS, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria
Petr Macháček
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
Dalibor Štys
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
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.
