Computation of Optimal Backward Perturbation Bounds for Large Sparse Linear Least Squares Problems |
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Authors: | A. Malyshev M. Sadkane |
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Affiliation: | (1) Department of Informatics, University of Bergen, N-5020 Bergen, Norway;(2) Department of Mathematics, Université de Bretagne Occidentale, 6, Av. Le Gorgeu, BP 809, F-29285 Brest Cedex, France |
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Abstract: | In this note we propose an algorithm based on the Lanczos bidiagonalization to approximate the backward perturbation bound for the large sparse linear squares problem. The algorithm requires ((m + n)l) operations where m and n are the size of the matrix under consideration and l <#60;<#60; min(m,n). The import of the proposed algorithm is illustrated by some examples coming from the Harwell-Boeing collection of test matrices.This revised version was published online in October 2005 with corrections to the Cover Date. |
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Keywords: | linear least squares backward perturbation Lanczos bidiagonalization bisection sparse matrix |
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