Point Divergence Gain and Multidimensional Data Sequences Analysis

Abstract

We introduce novel information-entropic variables -- a Point Divergence Gain (${\Omega}^{(l \rightarrow m)}_\alpha$), a Point Divergence Gain Entropy ($I_\alpha$), and a Point Divergence Gain Entropy Density ($P_\alpha$) -- which are derived from the R\'{e}nyi entropy and describe spatio-temporal changes between two consecutive discrete multidimensional distributions. The behavior of ${\Omega}^{(l \rightarrow m)}_\alpha$ is simulated for typical distributions and, together with $I_\alpha$ and $P_\alpha$, applied in analysis and characterization of series of multidimensional datasets of computer-based and real images.