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Stochastic Resonance

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

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Stochastic Resonance

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

  2. Stochastic Resonance • What Causes SR? • Non-Additive Noise • Nonlinearities • Mathematical Definition • There is none

  3. Example: Miyamoto Resonance Add noise to image and threshold. Vary noise. 0 15 30 60 90 120 180 240

  4. dx/dt x 1/s ax-bx3 + +  sin(t) (t) Most Studied System

  5. Numerics (Mataim et al. 1998)

  6. Numerics (Mataim et al. 1998)

  7. Numerics (Mataim et al. 1998)

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

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

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

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

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