• 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