Moderate Deviations Analysis of Binary Hypothesis Testing

Abstract

This paper is focused on the moderate-deviations analysis of binary hypothesis testing. The analysis relies on a concentration inequality for discrete-parameter martingales with bounded jumps, where this inequality forms a refinement to the Azuma-Hoeffding inequality. Relations of the analysis to the moderate deviations principle for i.i.d. random variables and to the relative entropy are considered.

Presented at the 2012 IEEE International Symposium on Information Theory (ISIT 2012) at MIT, Boston, July 2012. It appears in the Proceedings of ISIT 2012 on pages 826-830

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