Fisher information and noise-aided power estimation from one-bit quantizers
Digital Signal Processing
Stochastic resonance in sequential detectors
IEEE Transactions on Signal Processing
Stochastic resonance and improvement by noise in optimal detection strategies
Digital Signal Processing
Neural signal-detection noise benefits based on error probability
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Noise-enhanced clustering and competitive learning algorithms
Neural Networks
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A novel instance of a stochastic resonance effect, under the form of a noise-improved performance, is shown to be possible for an optimal Bayesian estimator. Estimation of the frequency of a periodic signal corrupted by a phase noise is considered. The optimal Bayesian estimator, achieving the minimum of the mean square estimation error, is explicitly derived. Conditions are exhibited where this minimal error is reduced when the noise level is raised, over some ranges, where this occurs essentially with non-Gaussian noise, in the tested configurations. These results contribute a new step in the exploration of stochastic resonance and its potentialities for signal processing.