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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/68592
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dc.contributor.authorBrinhole, E. R.-
dc.contributor.authorDestro, J. F. Z.-
dc.contributor.authorFreitas, A. A. C. de-
dc.contributor.authorAlcantara, N. P. de-
dc.date.accessioned2014-05-27T11:21:43Z-
dc.date.accessioned2016-10-25T18:21:33Z-
dc.date.available2014-05-27T11:21:43Z-
dc.date.available2016-10-25T18:21:33Z-
dc.date.issued2005-12-01-
dc.identifierhttp://dx.doi.org/10.2529/PIERS041210091305-
dc.identifier.citationPIERS 2005 - Progress in Electromagnetics Research Symposium, Proceedings, p. 579-582.-
dc.identifier.urihttp://hdl.handle.net/11449/68592-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/68592-
dc.description.abstractThis paper presents models that can be used in the design of microstrip antennas for mobile communications. The antennas can be triangular or rectangular. The presented models are compared with deterministic and empirical models based on artificial neural networks (ANN) presented in the literature. The models are based on Perceptron Multilayer (PML) and Radial Basis Function (RBF) ANN. RBF based models presented the best results. Also, the models can be embedded in CAD systems, in order to design microstrip antennas for mobile communications.en
dc.format.extent579-582-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectAntennas-
dc.subjectBackpropagation-
dc.subjectComputer aided design-
dc.subjectEmbedded systems-
dc.subjectFeedforward neural networks-
dc.subjectMicrostrip antennas-
dc.subjectMicrowave antennas-
dc.subjectMobile telecommunication systems-
dc.subjectNatural frequencies-
dc.subjectNeural networks-
dc.subjectPiers-
dc.subjectRadial basis function networks-
dc.subjectWireless networks-
dc.subjectArtificial neural networks-
dc.subjectCad systems-
dc.subjectEmpirical models-
dc.subjectMobile communications-
dc.subjectPerceptron-
dc.subjectRadial basis functions-
dc.subjectResonant frequencies-
dc.subjectMobile antennas-
dc.titleDetermination of resonant frequencies of triangular and rectangular microstrip antennas, using artificial neural networksen
dc.typeoutro-
dc.contributor.institutionFaculdade Metropolitana Londrinense (UMP)-
dc.contributor.institutionCentro Federal de Educação Tecnológica (CEFET)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationLondrinense Metropolitan Faculty-UMP-
dc.description.affiliationCEFET at Cornélio Procópio-
dc.description.affiliationSão Paulo State University-Unesp-
dc.description.affiliationUnespSão Paulo State University-Unesp-
dc.identifier.doi10.2529/PIERS041210091305-
dc.rights.accessRightsAcesso aberto-
dc.relation.ispartofPIERS 2005 - Progress in Electromagnetics Research Symposium, Proceedings-
dc.identifier.scopus2-s2.0-55749095422-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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