Fast parametric models for EM design using neural networks and space mapping

dc.contributor.author	Rayas-Sánchez, José E.
dc.contributor.author	Zhang, Qi J.
dc.date.accessioned	2013-05-21T17:57:02Z
dc.date.available	2013-05-21T17:57:02Z
dc.date.issued	2008-06
dc.description	- Brief introduction to ANNs - EM-based statistical analysis - Input Space Mapping - Linear-Input Neural-Output Space Mapping (LINO-SM) - LINO-SM approach to yield estimation - Constrained Broyden-Based Space Mapping - Training the Output Neuromapping - Example - Conclusions	es
dc.description.sponsorship	ITESO, A.C.	es
dc.identifier.uri	http://hdl.handle.net/11117/600
dc.language.iso	eng	es
dc.publisher	IEEE MTT-S Int. Microwave Symp. Workshop Notes and Short Courses	es
dc.relation.ispartofseries	IEEE MTT-S Int. Microwave Symp. Workshop Notes and Short Courses;2008
dc.rights.uri	http://quijote.biblio.iteso.mx/licencias/CC-BY-NC-ND-2.5-MX.pdf	es
dc.subject	Linear-Input Neural-Output Space Mapping (LINO-SM)	es
dc.subject	Electromagnetic Based Design	es
dc.subject	Neural Networks	es
dc.subject	Space Mapping	es
dc.title	Fast parametric models for EM design using neural networks and space mapping	es
dc.type	info:eu-repo/semantics/conferencePaper	es
rei.peerreviewed	Yes	es
rei.revisor	IEEE MTT-S International Microwave Symposium

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