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On generalized information and divergence measures and their applications: a brief review.

Inder Jeet Taneja, Leandro Pardo, Domingo Morales, María Luisa Menéndez (1989)

Qüestiió

The aim of this review is to give different two-parametric generalizations of the following measures: directed divergence (Kullback and Leibler, 1951), Jensen difference divergence (Burbea and Rao 1982 a,b; Rao, 1982) and Jeffreys invariant divergence (Jeffreys, 1946). These generalizations are put in the unified expression and their properties are studied. The applications of generalized information and divergence measures to comparison of experiments and the connections with Fisher information...

On generalized measures of relative information and inaccuracy

Inder Jeet Taneja, H. C. Gupta (1978)

Aplikace matematiky

Kullback's relative information and Kerridge's inaccuracy are two information-theoretic measures associated with a pair of probability distributions of a discrete random variable. The authors study a generalized measure which in particular contains a parametric generalization of relative information and inaccuracy. Some important properties of this generalized measure along with an inversion theorem are also studied.

On Graph-Based Cryptography and Symbolic Computations

V. A., Ustimenko (2007)

Serdica Journal of Computing

We have been investigating the cryptographical properties of in nite families of simple graphs of large girth with the special colouring of vertices during the last 10 years. Such families can be used for the development of cryptographical algorithms (on symmetric or public key modes) and turbocodes in error correction theory. Only few families of simple graphs of large unbounded girth and arbitrarily large degree are known. The paper is devoted to the more general theory of directed graphs of large...

On limiting towards the boundaries of exponential families

František Matúš (2015)

Kybernetika

This work studies the standard exponential families of probability measures on Euclidean spaces that have finite supports. In such a family parameterized by means, the mean is supposed to move along a segment inside the convex support towards an endpoint on the boundary of the support. Limit behavior of several quantities related to the exponential family is described explicitly. In particular, the variance functions and information divergences are studied around the boundary.

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