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Proceedings Paper

Numerically stable Jacobi array for parallel singular value decomposition (SVD) updating
Author(s): Filiep J. Vanpoucke; Marc Moonen; Ed F. A. Deprettere
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Paper Abstract

A novel algorithm is presented for updating the singular value decomposition in parallel. It is an improvement upon an earlier developed Jacobi-type SVD updating algorithm, where now the exact orthogonality of a certain matrix is guaranteed by means of a minimal factorization in terms of angles. Its orthogonality is known to be crucial for the numerical stability of the overall algorithm. The factored approach leads to a triangular array of rotation cells, implementing an orthogonal matrix-vector multiplication, and a novel array for SVD updating. Both arrays can be built up of CORDIC processors since the algorithms make exclusive use of orthogonal planar transformations.

Paper Details

Date Published: 28 October 1994
PDF: 10 pages
Proc. SPIE 2296, Advanced Signal Processing: Algorithms, Architectures, and Implementations V, (28 October 1994); doi: 10.1117/12.190852
Show Author Affiliations
Filiep J. Vanpoucke, Katholieke Univ. Leuven (Belgium)
Marc Moonen, Katholieke Univ. Leuven (Belgium)
Ed F. A. Deprettere, Delft Univ. of Technology (Netherlands)

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

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