CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 1987 vol.9 Issue No.01 - January
Issue No.01 - January (1987 vol.9)
Raziel 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.
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.
Raziel Haimi-Cohen, "Gradient-Type Algorithms for Partial Singular Value Decomposition", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.9, no. 1, pp. 137-142, January 1987, doi:10.1109/TPAMI.1987.4767879