Maximizing the number of polychronous groups in spiking networks
Data(s) |
2012
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Resumo |
In this paper we investigate the effect of biasing the axonal connection delay values in the number of polychronous groups produced for a spiking neuron network model. We use an estimation of distribution algorithm (EDA) that learns tree models to search for optimal delay configurations. Our results indicate that the introduced approach can be used to considerably increase the number of such groups. |
Formato |
application/pdf |
Identificador | |
Idioma(s) |
eng |
Publicador |
Facultad de Informática (UPM) |
Relação |
http://oa.upm.es/20294/1/INVE_MEM_2012_133768.pdf http://dl.acm.org/citation.cfm?doid=2330784.2331012 info:eu-repo/semantics/altIdentifier/doi/null |
Direitos |
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/openAccess |
Fonte |
Proceedings of the 14th Annual Genetic and Evolutionary Computation Conference (GECCO-2012) | 14th Annual Genetic and Evolutionary Computation Conference (GECCO-2012) | 07/07/2012 - 11/07/2013 | Philadelphia, PA, USA. |
Palavras-Chave | #Matemáticas |
Tipo |
info:eu-repo/semantics/conferenceObject Ponencia en Congreso o Jornada PeerReviewed |