Publicação
Training multilayer perceptrons for control systems applications - a comparison of different approaches
| dc.contributor.author | Ruano, Antonio | |
| dc.date.accessioned | 2013-02-13T09:53:42Z | |
| dc.date.available | 2013-02-13T09:53:42Z | |
| dc.date.issued | 1996 | |
| dc.date.updated | 2013-01-28T15:53:30Z | |
| dc.description.abstract | Multilayer 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.citation | Ruano, 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.other | AUT: ARU00698; | |
| dc.identifier.uri | http://hdl.handle.net/10400.1/2334 | |
| dc.language.iso | eng | por |
| dc.peerreviewed | yes | por |
| dc.title | Training multilayer perceptrons for control systems applications - a comparison of different approaches | por |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | London | por |
| oaire.citation.endPage | 10 | por |
| oaire.citation.startPage | 1 | por |
| oaire.citation.title | Int. Conf. on Engineering Applications of Neural Networks (EANN’96), In Int. Conf. on Engineering Applications of Neural Networks (EANN’96) | por |
| person.familyName | Ruano | |
| person.givenName | Antonio | |
| person.identifier.orcid | 0000-0002-6308-8666 | |
| person.identifier.rid | B-4135-2008 | |
| person.identifier.scopus-author-id | 7004284159 | |
| rcaap.rights | restrictedAccess | por |
| rcaap.type | conferenceObject | por |
| relation.isAuthorOfPublication | 13813664-b68b-40aa-97a9-91481a31ebf2 | |
| relation.isAuthorOfPublication.latestForDiscovery | 13813664-b68b-40aa-97a9-91481a31ebf2 |