Title :
A note on robust hypothesis testing
Author :
Devroye, Luc ; Györfi, László ; Lugosi, Gábor
Author_Institution :
Sch. of Comput. Sci., McGill Univ., Montreal, Que., Canada
fDate :
7/1/2002 12:00:00 AM
Abstract :
We introduce a simple new hypothesis testing procedure, which, based on an independent sample drawn from a certain density, detects which of k nominal densities is the true density closest to, under the total variation (L1) distance. We obtain a density-free uniform exponential bound for the probability of false detection
Keywords :
error statistics; signal detection; density-free uniform exponential bound; error probability; false detection probability; independent sample; nominal densities; robust detection; robust hypothesis testing; total variation distance; Bayesian methods; Clutter; Lagrangian functions; Quantization; Radar detection; Robustness; Sensor fusion; Signal detection; Signal processing algorithms; Testing;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2002.1013154
