Application Of generalized purcell method for real eigenvalue problems

Basit Öğe Kaydı
dc.contributor.authorRahmani, M.
dc.contributor.authorMomeni-Masuleh, S. H.
dc.date.accessioned2024-07-12T20:50:19Z
dc.date.available2024-07-12T20:50:19Z
dc.date.issued2009en_US
dc.departmentFakülteler, İnsan ve Toplum Bilimleri Fakültesi, Matematik Bölümüen_US
dc.description.abstractIn numerical linear algebra, the singular value decomposition (SVD) is an important factorization of a rectangular real or complex matrix, with several applications in signal and image processing, image compression and statistics. A new method based on generalized Purcell method for real eigenvalue problem and QR decomposition of an arbitrary matrix is proposed. The method in comparison to the inverse power method generates better results and has less computational cost. In addition, the method obtains directly the rank of a matrix and gives linearlly independent eigenvectors corresponding to an eigenvalue.en_US
dc.identifier.citationRahmani, M. ve Momeni-Masuleh, S. H. (2009). Application Of generalized purcell method for real eigenvalue problems. Maltepe Üniversitesi. s. 252.en_US
dc.identifier.endpage253en_US
dc.identifier.isbn9.78605E+12
dc.identifier.startpage252en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12415/2310
dc.language.isoenen_US
dc.publisherMaltepe Üniversitesien_US
dc.relation.ispartofInternational Conference of Mathematical Sciencesen_US
dc.relation.publicationcategoryUluslararası Konferans Öğesi - Başka Kurum Yazarıen_US
dc.rightsCC0 1.0 Universal*
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.snmzKY07637
dc.titleApplication Of generalized purcell method for real eigenvalue problemsen_US
dc.typeConference Object
dspace.entity.typePublication

Dosyalar

Koleksiyon

İnsan ve Toplum Bilimleri Fakültesi Koleksiyonu