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

✍ Scribed by Marc Van Barel; Yvette Vanberghen; Paul Van Dooren

Publisher: Elsevier Science
Year: 2010
Tongue: English
Weight: 364 KB
Volume: 234
Category: Article
ISSN: 0377-0427
DOI: 10.1016/j.cam.2010.02.007

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✦ Synopsis

In this work we reduce the computation of the singular values of a general product/quotient of matrices to the computation of the singular values of an upper triangular semiseparable matrix. Compared to the reduction into a bidiagonal matrix the reduction into semiseparable form exhibits a nested subspace iteration. Hence, when there are large gaps between the singular values, these gaps manifest themselves already during the reduction algorithm in contrast to the bidiagonal case.

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