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dc.contributor.authorPomenka, P.
dc.contributor.authorRaida, Zbyněk
dc.date.accessioned2016-04-22T06:14:51Z
dc.date.available2016-04-22T06:14:51Z
dc.date.issued2006-06cs
dc.identifier.citationRadioengineering. 2006, vol. 15, č. 2, s. 12-17. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/57949
dc.description.abstractIn the paper, an original methodology for the automatic creation of neural models of microwave structures is proposed and verified. Following the methodology, neural models of the prescribed accuracy are built within the minimum CPU time. Validity of the proposed methodology is verified by developing neural models of selected microwave structures. Functionality of neural models is verified in a design - a neural model is joined with a genetic algorithm to find a global minimum of a formulated objective function. The objective function is minimized using different versions of genetic algorithms, and their mutual combinations. The verified methodology of the automated creation of accurate neural models of microwave structures, and their association with global optimization routines are the most important original features of the paper.en
dc.formattextcs
dc.format.extent12-17cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/2006/06_02_12_17.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectArtificial neural networksen
dc.subjectgenetic algorithmsen
dc.subjectmetho-dology of developing neural models Bayesian regula-rizationen
dc.subjectLevenberg-Marquardt algorithmen
dc.titleMethodology of Neural Design: Applications in Microwave Engineeringen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue2cs
dc.coverage.volume15cs
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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