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dc.contributor.authorSmid, P.
dc.contributor.authorRaida, Zbyněk
dc.date.accessioned2016-04-22T06:16:01Z
dc.date.available2016-04-22T06:16:01Z
dc.date.issued2006-12cs
dc.identifier.citationRadioengineering. 2006, vol. 15, č. 4, s. 71-75. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/57977
dc.description.abstractThe paper describes the methodology of the automated creation of neural models of microwave structures. During the creation process, artificial neural networks are trained using the combination of the particle swarm optimization and the quasi-Newton method to avoid critical training problems of the conventional neural nets. In the paper, neural networks are used to approximate the behavior of a planar microwave filter (moment method, Zeland IE3D). In order to evaluate the efficiency of neural modeling, global optimizations are performed using numerical models and neural ones. Both approaches are compared from the viewpoint of CPU-time demands and the accuracy. Considering conclusions, methodological recommendations for including neural networks to the microwave design are formulated.en
dc.formattextcs
dc.format.extent71-75cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/2006/06_04_71_75.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectFeed-forward neural networken
dc.subjectrecurrent neural networken
dc.subjectparticle swarm optimizationen
dc.titleAutomated Modeling of Microwave Structures by Enhanced Neural Networksen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue4cs
dc.coverage.volume15cs
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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