Mostrar el registro sencillo del ítem

dc.contributor.authorRayas-Sánchez, José E.
dc.date.accessioned2019-07-23T15:23:11Z
dc.date.accessioned2023-03-21T20:43:02Z
dc.date.available2023-03-21T20:43:02Z
dc.date.issued2013-06
dc.identifier.citationJ. E. Rayas-Sánchez, “Artificial neural networks and space mapping for EM-based modeling and design of microwave circuits,” in Surrogate-Based Modeling and Optimization: Applications in Engineering, S. Koziel and L. Leifsson, Ed., New York, NY: Springer, 2013, ch. 7, pp. 147-169.es
dc.identifier.isbn978-1-4614-7550-7
dc.identifier.urihttps://hdl.handle.net/20.500.12032/75056
dc.descriptionThis chapter reviews the intersection of two major CAD technologies for modeling and design of RF and microwave circuits: artificial neural networks (ANNs) and space mapping (SM). A brief introduction to artificial neural networks is first pre-sented, starting from elementary concepts associated to biological neurons. Elec-tromagnetics (EM)-based modeling and design optimization of microwave circuits using artificial neural networks is addressed. The conventional and most widely used neural network approach for RF and microwave design optimization is ex-plained, followed by brief descriptions of typical enhancing techniques, such as decomposition, design of experiments, clusterization and adaptive data sampling. More advanced approaches for ANN-based design exploiting microwave knowledge are briefly reviewed, including the hybrid EM-ANN approach, the pri-or-knowledge input method, and knowledge-based neural networks. Computa-tionally efficient neural space mapping methods for highly accurate EM-based design optimization are surveyed, contrasting different strategies for developing suitable (input and output) neural mappings. A high-level perspective is kept throughout the chapter, emphasizing the main ideas associated with these innova-tive techniques. A tutorial example using commercially available CAD tools is fi-nally presented to illustrate the efficiency of the neural space mapping methods.es
dc.language.isoenges
dc.publisherSpringeres
dc.rights.urihttp://quijote.biblio.iteso.mx/licencias/TodosLosDerechosReservados.pdfes
dc.subjectComputer-aided Design (CAD)es
dc.subjectDesign Automationes
dc.subjectRF and Microwave Modelinges
dc.subjectEM-based Design Optimizationes
dc.subjectArtificial Neural Networks (ANN)es
dc.subjectSpace Mapping (SM)es
dc.subjectNowledge-based Neural Networks (KBNN)es
dc.subjectNeural Space Mappinges
dc.titleArtificial neural networks and space mapping for EM-based modeling and design of microwave circuitses
dc.typeinfo:eu-repo/semantics/bookPartes


Ficheros en el ítem

FicherosTamañoFormatoVer
Rayas-Sanchez_v10.pdf355.2Kbapplication/pdfVer/

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem


© AUSJAL 2022

Asociación de Universidades Confiadas a la Compañía de Jesús en América Latina, AUSJAL
Av. Santa Teresa de Jesús Edif. Cerpe, Piso 2, Oficina AUSJAL Urb.
La Castellana, Chacao (1060) Caracas - Venezuela
Tel/Fax (+58-212)-266-13-41 /(+58-212)-266-85-62

Nuestras redes sociales

facebook Facebook

twitter Twitter

youtube Youtube

Asociaciones Jesuitas en el mundo
Ausjal en el mundo AJCU AUSJAL JESAM JCEP JCS JCAP