Feature selection for high-order neural unit based identification

dc.contributor.authorPawlik, V.
dc.contributor.authorSteinbauer, P.
dc.contributor.authorBukovský, I.
dc.contributor.editorAdámek, Vítězslav
dc.contributor.editorJonášová, Alena
dc.contributor.editorPlánička, Stanislav
dc.date.accessioned2023-12-09T10:25:18Z
dc.date.available2023-12-09T10:25:18Z
dc.date.issued2023
dc.description.sponsorshipThe work has been supported by the project SGS22/150/OHK2/3T/12 “Mechatronics and adaptronics 2022” of Czech Technical University in Pragueen
dc.format4 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.citationComputational mechanics 2023: book of extended abstracts: 38th conference with international participation, p. 159-162.en
dc.identifier.isbn978-80-261-1177-1
dc.identifier.urihttp://hdl.handle.net/11025/54951
dc.language.isoenen
dc.publisherUniversity of West Bohemiaen
dc.rights© 2023 University of West Bohemia, Plzeň, Czech Republicen
dc.rights.accessopenAccessen
dc.subjectBorutacs
dc.subjectidentifikacecs
dc.subjectneuronová jednotka vysokého řáducs
dc.subject.translatedBoruta packageen
dc.subject.translatedidentificationen
dc.subject.translatedhigh-order neural uniten
dc.titleFeature selection for high-order neural unit based identificationen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen

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