Abstract
In many applications of the Singular Value Decomposition (SVD) it is desirable to calculate only a few terms of the expansion, corresponding to the greatest or smallest eigenvalues. An algorithm, based on a gradient search approach is proposed for SVD computation, one eigenvector at a time, in decreasing or increasing order of eigenvalues. Analytical as well as experimental examinations show that when the dimension is large, the proposed new method is superior to existing ones.
Original language | English |
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Title of host publication | Unknown Host Publication Title |
Editors | Vito Cappellini, A.G. Constantinides |
Publisher | North-Holland |
Pages | 382-385 |
Number of pages | 4 |
ISBN (Print) | 0444875832 |
State | Published - 1 Dec 1984 |
ASJC Scopus subject areas
- General Engineering