A NEW NON-SYMMETRIC INFORMATION DIVERGENCE OF CSISZAR'S CLASS, PROPERTIES AND ITS BOUNDS

K.C.Jain, Praphull Chhabra

Abstract: Non-parametric measures give the amount of information supplied by the data for discriminating in favor of a probability distribution P against another Q , or for measuring the distance or affinity between P and Q . There are several generalized functional divergences, such as: Csiszar divergence, Renyi- like divergence, Bregman divergence, Burbea- Rao divergence etc. all. In this paper, a non-parametric non symmetric measure of divergence which belongs to the family of Csiszár’s f-divergence is proposed. Its properties are studied and get the bounds in terms of some well known divergence measures.

Keywords: Csiszars f divergence, convex and normalized function, non-symmetric divergence measure, information inequalities, bounds of divergence measure.

DOI: https://doi.org/10.15623/ijret.2014.0305123