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dc.contributor.authorOrtín González, Silvia
dc.contributor.authorSoriano, Miguel C.
dc.contributor.authorPesquera González, Luis 
dc.contributor.authorBrunner, Daniel
dc.contributor.authorSan Martín Segura, Daniel
dc.contributor.authorFischer, Ingo
dc.contributor.authorMirasso, Claudio
dc.contributor.authorGutiérrez Llorente, José Manuel
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2015-11-10T10:21:02Z
dc.date.available2015-11-10T10:21:02Z
dc.date.issued2015-10-08
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/10902/7593
dc.description.abstractIn this paper we present a unified framework for extreme learning machines and reservoir computing (echo state networks), which can be physically implemented using a single nonlinear neuron subject to delayed feedback. The reservoir is built within the delay-line, employing a number of “virtual” neurons. These virtual neurons receive random projections from the input layer containing the information to be processed. One key advantage of this approach is that it can be implemented efficiently in hardware. We show that the reservoir computing implementation, in this case optoelectronic, is also capable to realize extreme learning machines, demonstrating the unified framework for both schemes in software as well as in hardware.es_ES
dc.format.extent11 p.es_ES
dc.language.isoenges_ES
dc.publisherMacmillanes_ES
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceScientific Reports 5, Article number: 14945 (2015)es_ES
dc.subject.otherDynamical systemses_ES
dc.subject.otherLearning algorithmses_ES
dc.subject.otherOptoelectronic devices and componentses_ES
dc.titleA Unified Framework for Reservoir Computing and Extreme Learning Machines based on a Single Time-delayed Neurones_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttp://dx.doi.org/10.1038/srep14945es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1038/srep14945
dc.type.versionpublishedVersiones_ES


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Atribución 4.0 InternacionalExcept where otherwise noted, this item's license is described as Atribución 4.0 Internacional