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Proceedings Paper

Computing low-dimensional signal subspaces
Author(s): Ricardo D. Fierro; Per Christian Hansen
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Paper Abstract

A two-sided (or complete) orthogonal decomposition of an m X n matrix A is a product of an orthogonal matrix, a triangular matrix, and another orthogonal matrix. Two examples are the URV and ULV decompositions. In this paper we present and analyze URV and ULV algorithms that are efficient whenever the numerical rank k of the matrix is much less than min(m,n). We also prove that good estimates of the singular vectors, needed in the algorithms, lead to good approximations of the singular subspaces of A.

Paper Details

Date Published: 28 October 1994
PDF: 11 pages
Proc. SPIE 2296, Advanced Signal Processing: Algorithms, Architectures, and Implementations V, (28 October 1994); doi: 10.1117/12.190894
Show Author Affiliations
Ricardo D. Fierro, California State Univ./San Marcos (United States)
Per Christian Hansen, Technical Univ. of Denmark (Denmark)

Published in SPIE Proceedings Vol. 2296:
Advanced Signal Processing: Algorithms, Architectures, and Implementations V
Franklin T. Luk, Editor(s)

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