Abstract
Given a square matrix A, a decomposition A = QR, where Q is unitary and R is upper triangular, is said to be the QR decomposition of A. In contrast to the LU decomposition, one does not fear a growth of entries in the case of the QR decomposition. (Why?)
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References
W. Hoffmann. Iterative algorithms for Gram-Schmidt orthogonalization. Computing 41: 335–348 (1989).
A. Bjorck and C. C. Paige. Loss and recapture of orthogonality in the modified Gram-Schmidt algorithm. SIAM J. Matrix Anal. Appl. 13(1): 176–190 (1992).
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Tyrtyshnikov, E.E. (1997). Lecture 8. In: A Brief Introduction to Numerical Analysis. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-0-8176-8136-4_8
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DOI: https://doi.org/10.1007/978-0-8176-8136-4_8
Publisher Name: Birkhäuser, Boston, MA
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