Computing singular value decompositions of parameterized matrices with total nonpositivity to high relative accuracy
type: Item
instance of: scholarly article
title: Computing singular value decompositions of parameterized matrices with total nonpositivity to high relative accuracy
zbMATH Open document ID: 1387.65035
author: Rong Huang
author: Delin Chu
published in: Journal of Scientific Computing
publication date: 2018-03-13T00:00:00Z
review text: The authors are concerned with accurately computing singular value decompositions (SVDs) of matrices. They present a new algorithm to compute SVDs of nonsingular totally nonpositive matrices to high relative accuracy. The new algorithm is developed by taking into account the property that there are \(n\times n\) independent parameters for any nonsingular totally nonpositive matrix of order \(n\) which determine all its singular values and singular vectors to high relative accuracy. Numerical results are presented to demonstrate the high relative accuracy of the proposed algorithm.
Mathematics Subject Classification ID: 65F15
Mathematics Subject Classification ID: 65F20
Mathematics Subject Classification ID: 15A18
zbMATH DE Number: 6849487
zbMATH Keywords: nonsingular totally nonpositive matrices
zbMATH Keywords: singular value decomposition
zbMATH Keywords: high relative accuracy computation
reviewed by: Liu Xinguo
MaRDI profile type: Publication
full work available at URL: s10915-016-0315-5
OpenAlex ID: W2552864248
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DOI: 10.1007/S10915-016-0315-5
description: scientific article; zbMATH DE number 6849487