• DocumentCode
    3281304
  • Title

    Improving Nonparametric Detectors via Stochastic Resonance

  • Author

    Chen, Hao ; Varshney, Pramod K. ; Kay, Steven ; Michels, James H.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., NY
  • fYear
    2006
  • fDate
    22-24 March 2006
  • Firstpage
    56
  • Lastpage
    61
  • Abstract
    This paper investigates the problem of stochastic resonance in some non-parametric detection schemes such as the sign detector, Wilcoxon detector and dead-zone limiter detector. Detection performance comparisons are made between the original detectors and noise modified detectors. Potential improvement of detection performance via stochastic resonance (SR) for each detection scheme is determined. The optimal SR noise for the sign detector is derived. Asymptotic detection performance is evaluated for the three detectors. For the finite sample size problem, we demonstrate improvability via some detection examples where the detection performance of these detectors can be improved when suitable noise is added.
  • Keywords
    nonparametric statistics; signal detection; stochastic processes; SR; asymptotic detection performance; noise modified detectors; nonparametric detectors; stochastic resonance; Background noise; Detectors; Gaussian noise; Noise robustness; Nonlinear systems; Signal detection; Signal to noise ratio; Stochastic resonance; Strontium; System testing; Hypothesis Testing; Non-parametric Detection; Stochastic Resonance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Sciences and Systems, 2006 40th Annual Conference on
  • Conference_Location
    Princeton, NJ
  • Print_ISBN
    1-4244-0349-9
  • Electronic_ISBN
    1-4244-0350-2
  • Type

    conf

  • DOI
    10.1109/CISS.2006.286430
  • Filename
    4067776