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Proceedings Paper

Updating rate of Jacobi singular value decomposition (SVD) arrays and data nonstationarity
Author(s): Flavio Lorenzelli; Kung Yao
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Paper Abstract

An effective updating algorithm for singular value decomposition, based on Jacobi rotations, has recently been proposed. This algorithm is composed of two basic steps: QR updating and rediagonalization. By proper interleaving these two operations, parallel implementations with very high updating rates are possible. In this paper, we are concerned with the behavior of this algorithm for nonstationary data, and the effect of the pipeline rate on tracking accuracy. In order to overcome the trade-off between accuracy and updating rate intrinsic in the original algorithm, we proposed two schemes which improve the overall performance when the rate of change of the data is high. In the `variable rotational rate' scheme, the number of Jacobi rotations per update is dynamically determined. The alternative approach is to make the forgetting factor variable and data-dependent. Behavior and performance of both schemes are discussed and compared.

Paper Details

Date Published: 28 October 1994
PDF: 12 pages
Proc. SPIE 2296, Advanced Signal Processing: Algorithms, Architectures, and Implementations V, (28 October 1994); doi: 10.1117/12.190853
Show Author Affiliations
Flavio Lorenzelli, Univ. of California/Los Angeles (United States)
Kung Yao, Univ. of California/Los Angeles (United States)


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

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