Abstract
In the last years, much effort has been devoted to high relative accuracy algorithms for the singular value problem. However, such algorithms have been constructed only for a few classes of matrices with certain structure or properties. In this paper, we study a different class of matrices--parameterized matrices with total nonpositivity. We develop a new algorithm to compute singular value decompositions of such matrices to high relative accuracy. Our numerical results confirm the high relative accuracy of our algorithm.
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