Fisher information as a metric of locally optimal processing and stochastic resonance.
The 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 nois...
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Public Library of Science (PLoS)
2012
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oai:doaj.org-article:f61edc9f7a3c4f07a8c1e1e1001a8b6d2021-11-18T07:23:02ZFisher information as a metric of locally optimal processing and stochastic resonance.1932-620310.1371/journal.pone.0034282https://doaj.org/article/f61edc9f7a3c4f07a8c1e1e1001a8b6d2012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22493686/?tool=EBIhttps://doaj.org/toc/1932-6203The 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.Fabing DuanFrançois Chapeau-BlondeauDerek AbbottPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 4, p e34282 (2012) |
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Medicine R Science Q Fabing Duan François Chapeau-Blondeau Derek Abbott Fisher information as a metric of locally optimal processing and stochastic resonance. |
description |
The 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. |
format |
article |
author |
Fabing Duan François Chapeau-Blondeau Derek Abbott |
author_facet |
Fabing Duan François Chapeau-Blondeau Derek Abbott |
author_sort |
Fabing Duan |
title |
Fisher information as a metric of locally optimal processing and stochastic resonance. |
title_short |
Fisher information as a metric of locally optimal processing and stochastic resonance. |
title_full |
Fisher information as a metric of locally optimal processing and stochastic resonance. |
title_fullStr |
Fisher information as a metric of locally optimal processing and stochastic resonance. |
title_full_unstemmed |
Fisher information as a metric of locally optimal processing and stochastic resonance. |
title_sort |
fisher information as a metric of locally optimal processing and stochastic resonance. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2012 |
url |
https://doaj.org/article/f61edc9f7a3c4f07a8c1e1e1001a8b6d |
work_keys_str_mv |
AT fabingduan fisherinformationasametricoflocallyoptimalprocessingandstochasticresonance AT francoischapeaublondeau fisherinformationasametricoflocallyoptimalprocessingandstochasticresonance AT derekabbott fisherinformationasametricoflocallyoptimalprocessingandstochasticresonance |
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