Moderate Deviations Analysis of Binary Hypothesis Testing
Information Theory
2016-11-17 v3 math.IT
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.
Keywords
Cite
@article{arxiv.1111.1995,
title = {Moderate Deviations Analysis of Binary Hypothesis Testing},
author = {Igal Sason},
journal= {arXiv preprint arXiv:1111.1995},
year = {2016}
}
Comments
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