Publication
Supervised training approach using spiking neural networks
dc.contributor.author | Silva, S. M. | |
dc.contributor.author | Ruano, Antonio | |
dc.date.accessioned | 2013-02-13T09:08:35Z | |
dc.date.available | 2013-02-13T09:08:35Z | |
dc.date.issued | 2006 | |
dc.date.updated | 2013-01-28T16:17:10Z | |
dc.description.abstract | One 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.citation | Silva, 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.other | AUT: ARU00698; | |
dc.identifier.uri | http://hdl.handle.net/10400.1/2326 | |
dc.language.iso | eng | por |
dc.peerreviewed | yes | por |
dc.title | Supervised training approach using spiking neural networks | por |
dc.type | conference object | |
dspace.entity.type | Publication | |
oaire.citation.conferencePlace | Faro | por |
oaire.citation.endPage | 2 | por |
oaire.citation.startPage | 1 | por |
oaire.citation.title | Global Education Techology Symposium (GETS 2006) | por |
person.familyName | Ruano | |
person.givenName | Antonio | |
person.identifier.orcid | 0000-0002-6308-8666 | |
person.identifier.rid | B-4135-2008 | |
person.identifier.scopus-author-id | 7004284159 | |
rcaap.rights | restrictedAccess | por |
rcaap.type | conferenceObject | por |
relation.isAuthorOfPublication | 13813664-b68b-40aa-97a9-91481a31ebf2 | |
relation.isAuthorOfPublication.latestForDiscovery | 13813664-b68b-40aa-97a9-91481a31ebf2 |