Title :
The asymptotic performance of two-sample nonparametric detectors when detecting nonfluctuating signals in non-Gaussian noise (Corresp.)
Author :
Al-Hussaini, Emad K. ; Turner, Laurence F.
fDate :
1/1/1979 12:00:00 AM
Abstract :
The asymptotic relative efficiencies (ARE) of generalized sign (GS), Mann-Whitney (MW), modified Savage (MS), and modified rank squared (MRS) two-sample nonparametric detectors are compared with those of the mean and median parametric detectors. The signal is assumed to be nonfluctuating, and the background noise is assumed to be lognormal or to be characterized by a contaminated normal distribution. It is shown that using the asymptotic relative efficiency measure the performance of nonparametric detectors increases appreciably as the noise distribution deviates from normality.
Keywords :
Nonparametric detection; Background noise; Detectors; Gaussian noise; Least squares approximation; Noise robustness; Probability; Signal detection; Smoothing methods; Stochastic processes; Working environment noise;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.1979.1055995