Moderate deviations analysis of binary hypothesis testing

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

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