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Proceedings Paper

Alternative To The SVD: Rank Revealing QR-Factorizations
Author(s): Tony F. Chan
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Paper Abstract

Both the singular value decomposition (SVD) and the QR factorization play central roles in signal processing algorithms. The usual tradeoff is that the SVD is more expensive but can reveal rank more reliably. In this paper, we show how to construct a QR factorization which can also reveal the rank reliably. For matrices with low rank deficiency, the overhead over the usual QR procedures is negligible. It also appears possible to implement the new procedure in systolic arrays.

Paper Details

Date Published: 4 April 1986
PDF: 8 pages
Proc. SPIE 0696, Advanced Algorithms and Architectures for Signal Processing I, (4 April 1986); doi: 10.1117/12.936872
Show Author Affiliations
Tony F. Chan, UCLA (United States)

Published in SPIE Proceedings Vol. 0696:
Advanced Algorithms and Architectures for Signal Processing I
Jeffrey M. Speiser, Editor(s)

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