• DocumentCode
    961856
  • Title

    Theory of the Stochastic Resonance Effect in Signal Detection: Part I—Fixed Detectors

  • Author

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

  • Author_Institution
    Syracuse Univ., Syracuse
  • Volume
    55
  • Issue
    7
  • fYear
    2007
  • fDate
    7/1/2007 12:00:00 AM
  • Firstpage
    3172
  • Lastpage
    3184
  • Abstract
    This paper develops the mathematical framework to analyze the stochastic resonance (SR) effect in binary hypothesis testing problems. The mechanism for SR noise enhanced signal detection is explored. The detection performance of a noise modified detector is derived in terms of the probability of detection PD and the probability of false alarm PFA. Furthermore, sufficient conditions are established to determine the improvability of a fixed detector using SR. The form of the optimal noise pdf is determined and the optimal stochastic resonance noise pdf which renders the maximum PD without increasing PFA is derived. Finally, an illustrative example is presented where performance comparisons are made between detectors where the optimal stochastic resonance noise, as well as Gaussian, uniform, and optimal symmetric noises are applied to enhance detection performance.
  • Keywords
    Gaussian noise; signal detection; binary hypothesis testing problems; fixed detectors; noise modified detector; nonGaussian noise; optimal noise pdf; signal detection; stochastic resonance effect; Detectors; Gaussian noise; Noise level; Noise robustness; Nonlinear systems; Signal analysis; Signal detection; Signal to noise ratio; Stochastic resonance; Strontium; Hypothesis testing; non-Gaussian noise; nonlinear systems; signal detection; stochastic resonance (SR);
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2007.893757
  • Filename
    4244681