Using semiseparable matrices to compute the SVD of a general matrix product/quotient

Journal of Computational and Applied Mathematics

Volumn 234, Issue 11, 2010, Pages 3175-3180

  Van Barel, Marc ^a   Vanberghen, Yvette ^a   Van Dooren, Paul ^b  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

BIDIAGONAL; MATRIX; REDUCTION ALGORITHMS; SEMISEPARABLE MATRICES; SINGULAR VALUES; SUBSPACE ITERATIONS;

MATRIX ALGEBRA;

EID: 77955275313     PISSN: 03770427     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cam.2010.02.007     Document Type: Conference Paper

References (6)

1. G.H. Golub, and W. Kahan Calculating the singular values and pseudo-inverse of a matrix SIAM Journal on Numerical Analysis 2 1965 205 224
2. R. Vandebril, M. Van Barel, and N. Mastronardi A QR -method for computing the singular values via semiseparable matrices Numerische Mathematik 99 2004 163 195
3. M.T. Heath, A.J. Laub, C.C. Paige, and R.C. Ward Computing the singular value decomposition of a product of two matrices SIAM Journal on Scientific and Statistical Computation 7 4 1986 1147 1159
4. A.W. Bojanczyk, M. Ewerbring, F.T. Luk, and P. Van Dooren An accurate product SVD algorithm Signal Processing 25 2 1991 189 201
5. G.H. Golub, K. Sølna, and P. Van Dooren Computing the SVD of a general matrix product/quotient SIAM Journal on Matrix Analysis and its Applications 22 1 2000 1 19
6. B.L.R. De Moor, and P. Van Dooren Generalizations of the singular value and QR decompositions SIAM Journal on Matrix Analysis and its Applications 13 4 1992 993 1014