Stochastic Resonance n Adding Noise to a signal can help in its detection. n Just the right amount of noise must be added (resonance) n SR in Nature –Periodic.

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Presentation transcript:

Stochastic Resonance n Adding Noise to a signal can help in its detection. n Just the right amount of noise must be added (resonance) n SR in Nature –Periodic ice age prediction –Crayfish warnings of approaching bass - a periodic fin motion –Dogfish spit noise to better detection. –Neurons

Stochastic Resonance n What Causes SR? –Non-Additive Noise –Nonlinearities n Mathematical Definition –There is none

n Example: Miyamoto Resonance Add noise to image and threshold. Vary noise

Most Studied System 1/s dx / dt x ax-bx 3 ++  sin(  t) (t)(t)

Numerics (Mataim et al. 1998)

Comparison of NP Optimal Detector n Coherent NP Correlator vs. Stochastic Resonance n Assumptions –Compared NP on input and after SR nonlinearity n Detector COHERENT n Noise = White Gaussian Galdi, Pierro, Pinto (Phys Review E, June 1998).

Comparison of NP Optimal Detectors n Coherent NP Correlator vs. Stochastic Resonance (4 dB) Galdi, Pierro, Pinto (Phys Review E, June 1998).

Noncoherent n Noncoherent SR sign detector Galdi, Pierro, Pinto (Phys Review E, June 1998).

Noncoherent Results n Noncoherent correlator is about 3dB worse than coherent. n Noncoherent SR is better than noncoherent correlator for low SNR Galdi, Pierro, Pinto (Phys Review E, June 1998).