Share Email Print
cover

Proceedings Paper

Easily updatable approximate generalized singular value decomposition
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

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)

© SPIE. Terms of Use
Back to Top