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dc.contributor.authorKuriyama, Kentaen
dc.contributor.authorMifune, Takeshien
dc.contributor.authorMatsuo, Tetsujien
dc.contributor.alternative栗山, 健太ja
dc.contributor.alternative美舩, 健ja
dc.contributor.alternative松尾, 哲司ja
dc.date.accessioned2022-05-13T09:38:43Z-
dc.date.available2022-05-13T09:38:43Z-
dc.date.issued2021-06-
dc.identifier.urihttp://hdl.handle.net/2433/270018-
dc.description.abstractMultiple expansion points are introduced to the multiport Cauer ladder network method to realize an efficient model order reduction of an eddy-current field. The proposed method can set multiple target frequencies to cover a wide frequency range with a small number of multiport electric network elements. A time-dependent response to pulsewidth-modulation (PWM) excitation is accurately reconstructed by setting the target frequencies at both fundamental and carrier frequencies.en
dc.language.isoeng-
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.rights© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.rightsThis is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。en
dc.subjectArtificial neural networksen
dc.subjectFinite element analysisen
dc.subjectConductivityen
dc.subjectTime-frequency analysisen
dc.subjectImpedanceen
dc.subjectElectric potentialen
dc.subjectTransformer coresen
dc.subjectCauer ladder network (CLN)en
dc.subjectexpansion pointen
dc.subjectmodel order reduction (MOR)en
dc.subjectmultiple portsen
dc.titleMultiport Model Order Reduction With Multiple Expansion Pointsen
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.jtitleIEEE Transactions on Magneticsen
dc.identifier.volume57-
dc.identifier.issue6-
dc.relation.doi10.1109/tmag.2021.3065024-
dc.textversionauthor-
dc.identifier.artnum6301505-
dcterms.accessRightsopen access-
datacite.awardNumber20K04443-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-20K04443/-
dc.identifier.pissn0018-9464-
dc.identifier.eissn1941-0069-
jpcoar.funderName日本学術振興会ja
jpcoar.awardTitleマルチスケール・マルチフィジクスモデル縮約による高精度モータシミュレーターの開発ja
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