Enhancing the Accuracy of Microwave Element Models by Artificial Neural Networks

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dc.contributor.authorDobes, Josef
dc.contributor.authorPospisil, Ladislav
dc.coverage.issue3cs
dc.coverage.volume13cs
dc.date.accessioned2016-04-26T11:04:11Z
dc.date.available2016-04-26T11:04:11Z
dc.date.issued2004-09cs
dc.description.abstractIn the recent PSpice programs, five types of the GaAs FET model have been implemented. However, some of them are too sophisticated and therefore very difficult to measure and identify afterwards, especially the realistic model of Parker and Skellern. In the paper, simple enhancements of one of the classical models are proposed first. The resulting modification is usable for the accurate modeling of both GaAs FETs and pHEMTs. Moreover, its updated capacitance function can serve as an accurate representation of microwave varactors, which is also important. The precision of the updated models can be strongly enhanced using the artificial neural networks. In the paper, both using an exclusive neural network without an analytic model and cooperating a corrective neural network with the updated analytic model will be discussed. The accuracy of the analytic models, the models based on the exclusive neural network, and the models created as a combination of the updated analytic model and the corrective neural network will be compared.en
dc.formattextcs
dc.format.extent7-12cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 2004, vol. 13, č. 3, s. 7-12. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/58052
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/2004/04_03_07_12.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectGaAs FETen
dc.subjectpHEMTen
dc.subjectmicrowave varactoren
dc.subjectparameters extractionen
dc.subjectCADen
dc.subjectartificial neural networken
dc.titleEnhancing the Accuracy of Microwave Element Models by Artificial Neural Networksen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
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