Stochastic Resonance — Threshold Detection

Stochastic resonance (Benzi et al 1981, Wiesenfeld-Moss 1995): noise of optimal amplitude maximizes SNR. SNR peaks at σ* where noise bridges the threshold just often enough to track the signal. Applications: neural spike coding, sensory biology (hair cells, crayfish), image processing, quantum SR. Quantified: SNR = (power at f_signal) / (noise floor), peaks at intermediate σ — noise helps!