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dc.contributor.authorRayas-Sánchez, José E.
dc.contributor.authorZhang, Qi J.
dc.date.accessioned2013-05-21T19:14:54Z
dc.date.accessioned2023-03-10T16:54:40Z
dc.date.available2013-05-21T19:14:54Z
dc.date.available2023-03-10T16:54:40Z
dc.date.issued2012-06
dc.identifier.citationJ. E. Rayas-Sánchez and Q. J. Zhang, “On knowledge-based neural networks and neuro-space mapping,” in IEEE MTT-S Int. Microwave Symp. Dig., Montreal, Canada, Jun. 2012, pp. 1-3. (ISSN: 0149-645X; E-ISBN: 978-1-4673-1086-4; P-ISBN: 978-1-4673-1085-7; DOI: 10.1109/MWSYM.2011.5972954)es
dc.identifier.urihttps://hdl.handle.net/20.500.12032/69580
dc.descriptionThis article reviews the most significant milestones in CAD methodologies for intelligent EM-based modeling and design optimization using artificial neural networks and space mapping. We consider knowledge-based and automatic neural network model generation based on advanced data sampling algorithms. Computationally efficient neural space mapping methods for highly accurate EM-based modeling, statistical analysis and yield estimation are described. We briefly compare different strategies for developing suitable (input and output) neuro-mappings. Inverse modeling exploiting neural networks is addressed, including neural inverse space mapping optimization. Embedded passives, microstrip filters, active devices and waveguide structures illustrate the techniques.es
dc.description.sponsorshipITESO, A.C.es
dc.language.isoenges
dc.publisherIEEE MTT-S International Microwave Symposiumes
dc.relation.ispartofseriesIEEE MTT-S International Microwave Symposium;2012
dc.rights.urihttp://quijote.biblio.iteso.mx/licencias/CC-BY-NC-ND-2.5-MX.pdfes
dc.subjectSpace Mappinges
dc.subjectElectromagnetic Based Optimizationes
dc.subjectNeural Networkses
dc.subjectKnowledge Based Techniqueses
dc.titleOn knowledge-based neural networks and neuro-space mappinges
dc.typeinfo:eu-repo/semantics/articlees


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