A radial basis function network (RBFN) for function approximation

dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorLucks, M. B.
dc.creatorOki, N.
dc.creatorRamirezAngulo, J.
dc.date2014-05-20T13:29:00Z
dc.date2016-10-25T21:21:32Z
dc.date2014-05-20T13:29:00Z
dc.date2016-10-25T21:21:32Z
dc.date1999-01-01
dc.date.accessioned2017-04-06T09:23:15Z
dc.date.available2017-04-06T09:23:15Z
dc.identifier42nd Midwest Symposium on Circuits and Systems, Proceedings, Vols 1 and 2. New York: IEEE, p. 1099-1101, 1999.
dc.identifierhttp://hdl.handle.net/11449/130589
dc.identifierhttp://acervodigital.unesp.br/handle/11449/130589
dc.identifier10.1109/MWSCAS.1999.867828
dc.identifierWOS:000089525800262
dc.identifier2-s2.0-0033292531
dc.identifierhttp://dx.doi.org/10.1109/MWSCAS.1999.867828
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/941132
dc.descriptionA radial basis function network (RBFN) circuit for function approximation is presented. Simulation and experimental results show that the network has good approximation capabilities. The RBFN was a squared hyperbolic secant with three adjustable parameters amplitude, width and center. To test the network a sinusoidal and sine function,vas approximated.
dc.languageeng
dc.publisherIEEE
dc.relation42nd Midwest Symposium on Circuits and Systems, Proceedings, Vols 1 and 2
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectApproximation theory
dc.subjectBipolar transistors
dc.subjectComputer simulation
dc.subjectElectric network analysis
dc.subjectFunction evaluation
dc.subjectNeural networks
dc.subjectSimulated annealing
dc.subjectFunction approximation
dc.subjectRadial basis function network
dc.subjectSinc function
dc.subjectSinusoidal function
dc.subjectIntegrated circuit testing
dc.titleA radial basis function network (RBFN) for function approximation
dc.typeOtro


Este ítem pertenece a la siguiente institución