Abstract There are three classical divergence measures exist in the literature on information theory and statistics. These are namely, Jeffryes-Kullback-Leiber [6], [8] J-divergence. SibsonBurbea-Rao [9], [3] Jensen-Shannon divegernce and Taneja [11] Arithmetic-Geometric divergence. These three measures bear an interesting relationship among each other. The divergence measures like Hellinger [5...

Abstract. In this paper we shall consider one parametric generalization of some nonsymmetric divergence measures. The non-symmetric divergence measures are such as: Kullback-Leibler relative information, χ2−divergence, relative J – divergence, relative Jensen – Shannon divergence and relative Arithmetic – Geometric divergence. All the generalizations considered can be written as particular case...

There are three classical divergence measures in the literature on information theory and statistics, namely, Jeffryes-Kullback-Leiber’s J-divergence, Sibson-Burbea-Rao’s JensenShannon divegernce and Taneja’s arithemtic geometric mean divergence. These bear an interesting relationship among each other and are based on logarithmic expressions. The divergence measures like Hellinger discriminatio...

Inder Jeet Taneja Departamento de Matemática Universidade Federal de Santa Catarina 88.040-900 Florianópolis, SC, Brazil. e-mail: [email protected] http://www.mtm.ufsc.br/∼taneja Abstract There are three classical divergence measures exist in the literature on information theory and statistics. These are namely, Jeffryes-Kullback-Leiber [5, 6] J-divergence. Sibson-BurbeaRao [1] Jensen-Shannon ...

Measures of divergence or discrepancy are used either to measure mutual information concerning two variables or to construct model selection criteria. In this paper we are focusing on divergence measures that are based on a class of measures known as Csiszar’s divergence measures. In particular, we propose a measure of divergence between residual lives of two items that have both survived up to...

This paper presents a sequence of fuzzy mean difference divergence measures. The validity of these fuzzy mean difference divergence measures is proved axiomatically. In addition, it introduces a sequence of inequalities among some of these fuzzy mean difference divergence measures. The applications of proposed fuzzy mean difference divergence measures in the context of pattern recognition have ...

In this paper, the concept of the classical f -divergence for a pair of measures is extended to the mixed f -divergence for multiple pairs of measures. The mixed f -divergence provides a way to measure the difference between multiple pairs of (probability) measures. Properties for the mixed f -divergence are established, such as permutation invariance and symmetry in distributions. An Alexandro...

Abstract Recently, Taneja [7] studied two one parameter generalizations of J-divergence, Jensen-Shannon divergence and Arithmetic-Geometric divergence. These two generalizations in particular contain measures like: Hellinger discrimination, symmetric chi-square divergence, and triangular discrimination. These measures are well known in the literature of Statistics and Information theory. In thi...

Abstract There are three classical divergence measures exist in the literature on information theory and statistics. These are namely, Jeffryes-Kullback-Leiber J-divergence. Burbea-Rao [1] Jensen-Shannon divegernce and Taneja [8] arithmetic-geometric mean divergence. These three measures bear an interesting relationship among each other and are based on logarithmic expressions. The divergence m...