Self-configuring spiking neural networks

dc.contributor.author	Rosselló, J.L.
dc.contributor.author	de Paúl, I.
dc.contributor.author	Canals, V.
dc.date.accessioned	2024-01-17T07:22:22Z
dc.date.available	2024-01-17T07:22:22Z
dc.identifier.uri	http://hdl.handle.net/11201/163739
dc.description.abstract	We present a simple architecture for Spiking Neural Networks self-conﬁguration. It consists in the hardware implementation of a simple Genetic Algorithm that may be used to obtain optimum network conﬁgurations. The proposed solution is applied to estimate the processing eﬃciency of diﬀerent networks. Based on the results we develop a new performance metric to calibrate the processing capacity of SNNs.
dc.format	application/pdf
dc.relation.isformatof	https://doi.org/10.1587/elex.5.921
dc.relation.ispartof	Ieice Electronics Express, 2008, vol. 5, num. 22, p. 921-926
dc.rights	, 2008
dc.subject.classification	Enginyeria
dc.subject.other	Engineering
dc.title	Self-configuring spiking neural networks
dc.type	info:eu-repo/semantics/article
dc.date.updated	2024-01-17T07:22:23Z
dc.rights.accessRights	info:eu-repo/semantics/openAccess
dc.identifier.doi	https://doi.org/10.1587/elex.5.921