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Proceedings Paper

Easily updatable approximate generalized singular value decomposition
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Paper Abstract

Despite its important signal processing applications, the generalized singular value decomposition (GSVD) is under-utilized due to the high updating cost. In this paper, we consider the noise subspace problem and introduce a new approximate GSVD that is easily amenable to updating.

Paper Details

Date Published: 1 November 1993
PDF: 7 pages
Proc. SPIE 2027, Advanced Signal Processing Algorithms, Architectures, and Implementations IV, (1 November 1993); doi: 10.1117/12.160457
Show Author Affiliations
Franklin T. Luk, Rensselaer Polytechnic Institute (Hong Kong)
Sanzheng Qiao, McMaster Univ. (Canada)


Published in SPIE Proceedings Vol. 2027:
Advanced Signal Processing Algorithms, Architectures, and Implementations IV
Franklin T. Luk, Editor(s)

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