Gradient-type algorithms for partial singular value decomposition.

R Haimi-Cohen, A Cohen
Author Information
  1. R Haimi-Cohen: 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.

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