Application Of generalized purcell method for real eigenvalue problems
Küçük Resim Yok
Tarih
2009
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Maltepe Üniversitesi
Erişim Hakkı
CC0 1.0 Universal
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
Özet
In 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.
Açıklama
Anahtar Kelimeler
Kaynak
International Conference of Mathematical Sciences
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Rahmani, M. ve Momeni-Masuleh, S. H. (2009). Application Of generalized purcell method for real eigenvalue problems. Maltepe Üniversitesi. s. 252.
