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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/95112
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dc.contributor.authorXu, L.-
dc.contributor.authorVladusich, T.-
dc.contributor.authorDuan, F.-
dc.contributor.authorGunn, L.-
dc.contributor.authorAbbott, D.-
dc.contributor.authorMcDonnell, M.-
dc.date.issued2015-
dc.identifier.citationPhysics Letters A: General Physics, Nonlinear Science, Statistical Physics, Atomic, Molecular and Cluster Physics, Plasma and Fluid Physics, Condensed Matter, Cross-disciplinary Physics, Biological Physics, Nanosciences, Quantum Physics, 2015; 379(38):2277-2283-
dc.identifier.issn0375-9601-
dc.identifier.issn1873-2429-
dc.identifier.urihttp://hdl.handle.net/2440/95112-
dc.description.abstractAbstract not available-
dc.description.statementofresponsibilityLiyan Xu, Tony Vladusich, Fabing Duan, Lachlan J.Gunn, Derek Abbott, Mark D. McDonnell-
dc.language.isoen-
dc.publisherElsevier-
dc.rights© 2015 Elsevier B.V. All rights reserved.-
dc.source.urihttp://dx.doi.org/10.1016/j.physleta.2015.05.032-
dc.subjectSuprathreshold stochastic resonance; binary quantizer; mean square error distortion; stochastic quantization; least squares regression; information transmission-
dc.titleDecoding suprathreshold stochastic resonance with optimal weights-
dc.typeJournal article-
dc.identifier.doi10.1016/j.physleta.2015.05.032-
dc.relation.granthttp://purl.org/au-research/grants/arc/DP1093425-
pubs.publication-statusPublished-
dc.identifier.orcidAbbott, D. [0000-0002-0945-2674]-
dc.identifier.orcidMcDonnell, M. [0000-0002-7009-3869]-
Appears in Collections:Aurora harvest 7
Electrical and Electronic Engineering publications

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