Abstract

This paper presents a general histogram based divergence estimator based on data-dependent partition. Sufficient conditions for the universal strong consistency of the data-driven divergence estimator, using Lugosi and Nobel's combinatorial notions for partition families, are presented. As a corollary this result is particularized for the emblematic case of l m-spacing quantization scheme.

Date

June 24, 2007

Authors

Jorge Silva, Shrikanth Narayanan

Conference

2007 IEEE International Symposium on Information Theory

Pages

2021-2025

Publisher

IEEE