DocumentCode
911568
Title
Nonparametric detection
Author
Thomas, John B.
Author_Institution
Princeton University, Princeton, N. J.
Volume
58
Issue
5
fYear
1970
fDate
5/1/1970 12:00:00 AM
Firstpage
623
Lastpage
631
Abstract
This paper considers some of the simpler nonparametric detection schemes and compares their asymptotic relative efficiencies to those of detectors which are optimal in the Neyman-Pearson sense. In the one-input case, the nonparametric sign and Wilcoxon detectors are compared to the linear detector which is optimal for the detection of a dc signal of unknown amplitude in Gaussian noise. For two-input systems the nonparametric polarity coincidence correlator is compared to the system which is optimal for the detection of a common random Gaussian component in two-input Gaussian noises. The nonparametric detectors are shown to offer advantages in simplicity of implementation and in insensitivity to changes in input statistics while performing moderately well compared to the parametric detectors. More impressive results can be obtained with more complicated detectors utilizing nonlinear rank statistics.
Keywords
Bibliographies; Correlators; Cost function; Detectors; Gaussian noise; Parametric statistics; Probability; Signal detection; Testing; Working environment noise;
fLanguage
English
Journal_Title
Proceedings of the IEEE
Publisher
ieee
ISSN
0018-9219
Type
jour
DOI
10.1109/PROC.1970.7718
Filename
1449648
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