ON THE COMPUTATION OF THE PARTIAL SINGULAR VALUE DECOMPOSITION.

Raziel Haimi-Cohen; Arnon Cohen

ON THE COMPUTATION OF THE PARTIAL SINGULAR VALUE DECOMPOSITION.

Raziel Haimi-Cohen
, Arnon Cohen

Department of Electrical & Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

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
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

Cite this

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title = "ON THE COMPUTATION OF THE PARTIAL SINGULAR VALUE DECOMPOSITION.",

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.",

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T1 - ON THE COMPUTATION OF THE PARTIAL SINGULAR VALUE DECOMPOSITION.

AU - Haimi-Cohen, Raziel

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N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/0021555084

M3 - Conference contribution

AN - SCOPUS:0021555084

SN - 0444875832

SP - 382

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BT - Unknown Host Publication Title

A2 - Cappellini, Vito

A2 - Constantinides, A.G.

PB - North-Holland

ER -

ON THE COMPUTATION OF THE PARTIAL SINGULAR VALUE DECOMPOSITION.

Abstract

ASJC Scopus subject areas

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