Point Divergence Gain and Multidimensional Data Sequences Analysis

We introduce novel information-entropic variables – a Point Divergence Gain (${\mathrm{\Omega }}_{\alpha }^{(l\to m)}$), 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 ${\mathrm{\Omega }}_{\alpha }^{(l\to m)}$ 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.