Abstract
In this chapter we discuss reduction of matrices to the canonical form by use of orthogonal transformations in the spaces of images and preimages. Such canonical form is called the singular value decomposition. In what follows we will use the well-known polar decomposition, which is recalled in Section 1 in course of discussion of singular value decomposition of square matrices.
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© 1993 Springer Science+Business Media Dordrecht
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Godunov, S.K., Antonov, A.G., Kiriljuk, O.P., Kostin, V.I. (1993). Singular Value Decomposition. In: Guaranteed Accuracy in Numerical Linear Algebra. Mathematics and Its Applications, vol 252. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-1952-8_1
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DOI: https://doi.org/10.1007/978-94-011-1952-8_1
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-4863-7
Online ISBN: 978-94-011-1952-8
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