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dc.contributor.authorDuan, F.-
dc.contributor.authorChapeau-Blondeau, F.-
dc.contributor.authorAbbott, D.-
dc.contributor.editorPerc, M.-
dc.identifier.citationPLoS One, 2012; 7(4):1-6-
dc.description.abstractThe origins of Fisher information are in its use as a performance measure for parametric estimation. We augment this and show that the Fisher information can characterize the performance in several other significant signal processing operations. For processing of a weak signal in additive white noise, we demonstrate that the Fisher information determines (i) the maximum output signal-to-noise ratio for a periodic signal; (ii) the optimum asymptotic efficacy for signal detection; (iii) the best cross-correlation coefficient for signal transmission; and (iv) the minimum mean square error of an unbiased estimator. This unifying picture, via inequalities on the Fisher information, is used to establish conditions where improvement by noise through stochastic resonance is feasible or not.-
dc.description.statementofresponsibilityFabing Duan, François Chapeau-Blondeau and Derek Abbott-
dc.publisherPublic Library of Science-
dc.rightsCopyright: © 2012 Duan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.-
dc.subjectModels, Statistical-
dc.subjectStochastic Processes-
dc.subjectComputer Simulation-
dc.subjectSignal-To-Noise Ratio-
dc.titleFisher information as a metric of locally optimal processing and stochastic resonance-
dc.typeJournal article-
dc.identifier.orcidAbbott, D. [0000-0002-0945-2674]-
Appears in Collections:Aurora harvest 5
Electrical and Electronic Engineering publications

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