Neural modeling and space mapping: two approaches to circuit design

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dc.contributor.authorBandler, John W.
dc.contributor.authorRayas-Sánchez, José E.
dc.contributor.authorZhang, Qi J.
dc.date.accessioned2014-08-25T18:58:08Z
dc.date.available2014-08-25T18:58:08Z
dc.date.issued1999-08
dc.descriptionThe drive in the microwave industry for manufacturability-driven design and time-to-market demands powerful and efficient computer-aided design tools. The need for statistical analysis and yield optimization coupled with the desire to use accurate physics-based and EM-based models leads to tasks that are computationally intensive using conventional approaches. We present two recent advances in the microwave CAD area, Artificial Neural Network (ANN) based modeling and Space Mapping (SM) based modeling for fast and accurate design of microwave components and circuits.es
dc.description.sponsorshipConsejo Nacional de Ciencia y Tecnologíaes
dc.description.sponsorshipCarleton Universityes
dc.identifier.citationBandler, J.W; Rayas-Sánchez, J.E. and Zhang, Q.J. (1999) “Neural modeling and space mapping: two approaches to circuit design,” in XXVI URSI General Assembly, Toronto, ON, Aug., p. 246.es
dc.identifier.urihttp://hdl.handle.net/11117/1410
dc.language.isoenges
dc.publisherXXVI URSI General Assemblyes
dc.relation.ispartofseriesXXVI URSI General Assembly;
dc.rights.urihttp://quijote.biblio.iteso.mx/licencias/CC-BY-NC-ND-2.5-MX.pdfes
dc.subjectMicrowave Modelinges
dc.subjectNeural Networkses
dc.subjectSpace Mappinges
dc.subjectCADes
dc.titleNeural modeling and space mapping: two approaches to circuit designes
dc.typeinfo:eu-repo/semantics/conferencePaperes
rei.peerreviewedYeses
rei.revisorXXVI URSI General Assembly

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