Point Divergence Gain and Multidimensional Data Sequences Analysis

Abstract

We introduce novel information-entropic variables -- a Point Divergence Gain (${\Omega }_{\alpha }^{(l\to m)}$), a Point Divergence Gain Entropy ($I_{\alpha }$), and a Point Divergence Gain Entropy Density ($P_{\alpha }$) -- which are derived from the Rényi entropy and describe spatio-temporal changes between two consecutive discrete multidimensional distributions. The behavior of ${\Omega }_{\alpha }^{(l\to m)}$ 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.

18 pages, 7 figures