Numerically stable Jacobi array for parallel singular value decomposition (SVD) updating

Filiep J. Vanpoucke; Marc Moonen; Ed F. A. Deprettere

doi:10.1117/12.190852

28 October 1994 Numerically stable Jacobi array for parallel singular value decomposition (SVD) updating

Filiep J. Vanpoucke, Marc Moonen, Ed F. A. Deprettere

Proceedings Volume 2296, Advanced Signal Processing: Algorithms, Architectures, and Implementations V; (1994) https://doi.org/10.1117/12.190852
Event: SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, 1994, San Diego, CA, United States

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.

Citation Download Citation

Filiep J. Vanpoucke, Marc Moonen, and Ed F. A. Deprettere "Numerically stable Jacobi array for parallel singular value decomposition (SVD) updating", Proc. SPIE 2296, Advanced Signal Processing: Algorithms, Architectures, and Implementations V, (28 October 1994); https://doi.org/10.1117/12.190852

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