Stochastic resonance in sequential detectors

  • Authors:

  • Marco Guerriero;Stefano Marano;Vincenzo Matta;Peter Willett

  • Affiliations:

  • Electrical and Computer Engineering Department, University of Connecticut, Storrs, CT;Department of Information and Electrical Engineering, University of Salerno, Fisciano, SA, Italy;Department of Information and Electrical Engineering, University of Salerno, Fisciano, SA, Italy;Electrical and Computer Engineering Department, University of Connecticut, Storrs, CT

  • Venue:
  • IEEE Transactions on Signal Processing
  • Year:
  • 2009

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Abstract

Stochastic resonance (SR) is a nonlinear phenomenon known in physics that has attracted recent interest in the signal-processing literature, and specifically in the context of detection. We investigate the SR effect arising in sequential detectors for shift-in-mean binary hypothesis testing and characterize the optimal resonance as the solution of specific optimization problems. One particular (and at first glance perhaps counterintuitive) finding is that certain sequential detection procedures can be made more efficient by randomly adding or subtracting a suitable constant value to the data at the input of the detector.