Title :
Gradient-Type Algorithms for Partial Singular Value Decomposition
Author :
Haimi-Cohen, Raziel ; Cohen, Arnon
Author_Institution :
Department of Electrical and Computer Engineering, Ben-Gurion University, Beer-Sheva, Israel; Tadiran, Inc., Telecommunication Divison, P. O. B. 500, Petah Tikva 49104, Israel.
Abstract :
It is often desirable to calculate only a few terms of the SVD expansion of a matrix, corresponding to the largest or smallest singular values. Two algorithms, based on gradient and conjugate gradient search, are proposed for this purpose. SVD is computed term by term in a decreasing or increasing order of singular values. The algorithms are simple to implement and are especially advantageous with large matrices.
Keywords :
Biomedical signal processing; Councils; Covariance matrix; Eigenvalues and eigenfunctions; Matrix decomposition; Pattern analysis; Psychology; Signal processing algorithms; Singular value decomposition; Symmetric matrices; Conjugate gradient; Rayleigh quotient; gradient search; partial singular value decomposition;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1987.4767879
