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dc.contributor.authorSimões, Alexandre da Silva [UNESP]
dc.contributor.authorReali Costa, Anna Helena
dc.contributor.authorZaverucha, G
dc.contributor.authorLoureiroDaCosta, A
dc.identifier.citationAdvances In Artificial Intelligence - Sbia 2008, Proceedings. Berlin: Springer-verlag Berlin, v. 5249, p. 227-236, 2008.
dc.description.abstractSpiking neural networks - networks that encode information in the timing of spikes - are arising as a new approach in the artificial neural networks paradigm, emergent from cognitive science. One of these new models is the pulsed neural network with radial basis function, a network able to store information in the axonal propagation delay of neurons. Learning algorithms have been proposed to this model looking for mapping input pulses into output pulses. Recently, a new method was proposed to encode constant data into a temporal sequence of spikes, stimulating deeper studies in order to establish abilities and frontiers of this new approach. However, a well known problem of this kind of network is the high number of free parameters - more that 15 - to be properly configured or tuned in order to allow network convergence. This work presents for the first time a new learning function for this network training that allow the automatic configuration of one of the key network parameters: the synaptic weight decreasing factor.en
dc.publisherSpringer-verlag Berlin
dc.relation.ispartofAdvances In Artificial Intelligence - Sbia 2008, Proceedings
dc.sourceWeb of Science
dc.titleA Learning Function for Parameter Reduction in Spiking Neural Networks with Radial Basis Functionen
dc.typeTrabalho apresentado em evento
dcterms.rightsHolderSpringer-verlag Berlin
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.description.affiliationSão Paulo State Univ UNESP, Automat & Integrated Syst Grp, BR-18087180 Sorocaba, SP, Brazil
dc.description.affiliationUnespSão Paulo State Univ UNESP, Automat & Integrated Syst Grp, BR-18087180 Sorocaba, SP, Brazil
dc.rights.accessRightsAcesso aberto
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Ciência e Tecnologia, Sorocabapt[1][2][1]
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