Point Divergence Gain and Multidimensional Data Sequences Analysis

Abstract

We introduce novel information-entropic variables -- a Point Divergence Gain ($Ω^{(l \rightarrow m)}_α$), 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 $Ω^{(l \rightarrow m)}_α$ 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.