1Stochastic Resonance in Sequential Detectors

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. Index Terms—Stochastic Resonance, Sequential Detection I. INTRODUCTION AND MOTIVATIONS In a recent paper [1], Chen et al. established a mathematical theory to deal with the so-called stochastic resonance (SR) effect in the context of detection. In a nutshell, the SR phenomenon manifests itself by an increase of signal-to-noise ratio at the output of certain nonlinear devices, due to the injection of noise at the input. Thus, as regard to detection problems, the (at first glance) counterintuitive consequence o