Error-probability noise benefits in threshold neural signal detection

DOI10.1016/j.neunet.2009.06.044zbMath1335.94017OpenAlexW2000021165WikidataQ46107286 ScholiaQ46107286MaRDI QIDQ280379

Ashok Patel, Bart Kosko

Publication date: 10 May 2016

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2009.06.044

zbMATH Keywords

optimal noise intensitysignal detectionstochastic resonanceerror probabilityarray detectionthreshold neurons

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Detection theory in information and communication theory (94A13)

Related Items (3)

Error-probability noise benefits in threshold neural signal detection ⋮ Benefits of noise in M-estimators: optimal noise level and probability density ⋮ Noise-enhanced convolutional neural networks

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