Lower bounds on Information Divergence

Details Lower bounds on Information Divergence Lower bounds on Information Divergence

2011-02-12

arxiv.org/abs/1102.2536v1

Computer Science

Information Theory

Submitted for the conference ISIT 2011

Scientific paper

In this paper we establish lower bounds on information divergence from a distribution to certain important classes of distributions as Gaussian, exponential, Gamma, Poisson, geometric, and binomial. These lower bounds are tight and for several convergence theorems where a rate of convergence can be computed, this rate is determined by the lower bounds proved in this paper. General techniques for getting lower bounds in terms of moments are developed.

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