On Concentration and Revisited Large Deviations Analysis of Binary Hypothesis Testing
classification
💻 cs.IT
math.IT
keywords
analysisbinarydeviationshypothesisinequalitylargerefinedtesting
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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.
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