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    On Concentration and Revisited Large Deviations Analysis of Binary Hypothesis Testing

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    This paper first introduces a refined version of the Azuma-Hoeffding inequality for discrete-parameter martingales with uniformly bounded jumps. The refined inequality is used to revisit the large deviations analysis of binary hypothesis testing.Comment: This paper (7 pages) is closely related to a presentation at the 2012 Workshop on Information Theory and Applications, La Jolla, California, USA, February 201
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