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Training multilayer perceptrons for control systems applications - a comparison of different approaches

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dc.contributor.authorRuano, Antonio
dc.date.accessioned2013-02-13T09:53:42Z
dc.date.available2013-02-13T09:53:42Z
dc.date.issued1996
dc.date.updated2013-01-28T15:53:30Z
dc.description.abstractMultilayer perceptrons (MLPs) (1) are the most common artificial neural networks employed in a large field of applications. In control and signal processing applications, MLPs are mainly used as nonlinear mapping approximators. The most common training algorithm used with MLPs is the error back-propagation (BP) alg. (1).pt_PT
dc.identifier.citationRuano, A. E. Training multilayer perceptrons for control systems applications - a comparison of different approaches, Trabalho apresentado em Int. Conf. on Engineering Applications of Neural Networks (EANN’96), In Int. Conf. on Engineering Applications of Neural Networks (EANN’96), London, 1996.por
dc.identifier.otherAUT: ARU00698;
dc.identifier.urihttp://hdl.handle.net/10400.1/2334
dc.language.isoengpor
dc.peerreviewedyespor
dc.titleTraining multilayer perceptrons for control systems applications - a comparison of different approachespor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceLondonpor
oaire.citation.endPage10por
oaire.citation.startPage1por
oaire.citation.titleInt. Conf. on Engineering Applications of Neural Networks (EANN’96), In Int. Conf. on Engineering Applications of Neural Networks (EANN’96)por
person.familyNameRuano
person.givenNameAntonio
person.identifier.orcid0000-0002-6308-8666
person.identifier.ridB-4135-2008
person.identifier.scopus-author-id7004284159
rcaap.rightsrestrictedAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication13813664-b68b-40aa-97a9-91481a31ebf2
relation.isAuthorOfPublication.latestForDiscovery13813664-b68b-40aa-97a9-91481a31ebf2

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