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Supervised training approach using spiking neural networks

dc.contributor.authorSilva, S. M.
dc.contributor.authorRuano, Antonio
dc.date.accessioned2013-02-13T09:08:35Z
dc.date.available2013-02-13T09:08:35Z
dc.date.issued2006
dc.date.updated2013-01-28T16:17:10Z
dc.description.abstractOne of the basic aspects of some neural networks is their attempt to approximate as much as possible their biological counterparts. The goal is to achieve a simple and robust network, easy to understand and able of simulating the human brain at a computational level. Recently a third generation of neural networks (NN) [1], called Spiking Neural Networks(SNN) was appeared. This new kind of networks use the time of a electrical pulse, or spike, to encode the information. In the first and second generation of NN analog values are used in the communication between neurons.pt_PT
dc.identifier.citationSilva, S. M.; Ruano, A. E. Supervised training approach using spiking neural networks, Trabalho apresentado em Global Education Techology Symposium (GETS 2006), In Proceedings of the Global Education Techology Symposium (GETS 2006), Faro, 2006.por
dc.identifier.otherAUT: ARU00698;
dc.identifier.urihttp://hdl.handle.net/10400.1/2326
dc.language.isoengpor
dc.peerreviewedyespor
dc.titleSupervised training approach using spiking neural networkspor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceFaropor
oaire.citation.endPage2por
oaire.citation.startPage1por
oaire.citation.titleGlobal Education Techology Symposium (GETS 2006)por
person.familyNameRuano
person.givenNameAntonio
person.identifier.orcid0000-0002-6308-8666
person.identifier.ridB-4135-2008
person.identifier.scopus-author-id7004284159
rcaap.rightsrestrictedAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication13813664-b68b-40aa-97a9-91481a31ebf2
relation.isAuthorOfPublication.latestForDiscovery13813664-b68b-40aa-97a9-91481a31ebf2

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