An efficient algorithm for rank and subspace tracking
Yükleniyor...
Tarih
2006
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Pergamon-Elsevier Science Ltd
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Traditionally, the singular value decomposition (SVD) has been used in rank and subspace tracking methods. However, the SVD is computationally costly, especially when the problem is recursive in nature and the size of the matrix is large. The truncated ULV decomposition (TULV) is an alternative to the SVD. It provides a good approximation to subspaces for the data matrix and can be modified quickly to reflect changes in the data. It also reveals the rank of the matrix. This paper presents a TULV updating algorithm. The algorithm is most efficient when the matrix is of low rank. Numerical results are presented that illustrate the accuracy of the algorithm. (c) 2006 Elsevier Ltd. All rights reserved.
Açıklama
Erbay, Hasan/0000-0002-7555-541X
Anahtar Kelimeler
singular value decomposition, modifying decompositions, subspace tracking, rank estimation, ULV decomposition
Kaynak
Mathematical And Computer Modelling
WoS Q Değeri
Q4
Scopus Q Değeri
N/A
Cilt
44
Sayı
7-8
Künye
Erbay, H. (2006). An efficient algorithm for rank and subspace tracking. Mathematical and Computer Modelling, 44(7–8), 742–748. https://doi.org/10.1016/j.mcm.2006.02.011
