Trimmed multilevel fast multipole algorithm for D-type volume ıntegral equations

buir.contributor.authorTopözlü, Halil
buir.contributor.authorErtük, Vakur Behçet
buir.contributor.orcidErtük, Vakur Behçet|0000-0003-0780-5015
dc.citation.epage1937en_US
dc.citation.spage1936en_US
dc.contributor.authorTopözlü, Halil
dc.contributor.authorKaraosmanoğlu, B.
dc.contributor.authorErtük, Vakur Behçet
dc.coverage.spatialDenver, CO, USAen_US
dc.date.accessioned2023-02-28T14:11:44Z
dc.date.available2023-02-28T14:11:44Z
dc.date.issued2022-09-21
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionConference Name: Antennas and Propagation Society International Symposiumen_US
dc.descriptionDate of Conference: 10-15 July 2022en_US
dc.description.abstractIn this work, we present a trimming scheme for the multilevel tree structure of multilevel fast multipole algorithm (MLFMA), which is applied on D-type volume integral equations. With this approach, the number of iterations and the durations of matrix-vector multiplications are significantly reduced for the solution of multi-scale volumetric problems. The trimming operation is performed on rows and columns of the impedance matrix. In order to eliminate the matrix columns, the current coefficients are estimated via machine learning techniques. The implementation particularly provides significant acceleration for the iterative solutions of electrically large volumetric problems.en_US
dc.identifier.doi10.1109/AP-S/USNC-URSI47032.2022.9886528en_US
dc.identifier.urihttp://hdl.handle.net/11693/111964
dc.language.isoEnglishen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofhttps://doi.org/10.1109/AP-S/USNC-URSI47032.2022.9886528en_US
dc.source.titleAntennas and Propagation Society International Symposiumen_US
dc.subjectMLFMAen_US
dc.subjectVolume integral equationsen_US
dc.subjectMachine learningen_US
dc.titleTrimmed multilevel fast multipole algorithm for D-type volume ıntegral equationsen_US
dc.typeConference Paperen_US

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