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Gradient-Type Algorithms for Partial Singular Value Decomposition
January 1987 (vol. 9 no. 1)
pp. 137-142
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.
Arnon Cohen, Department of Electrical and Computer Engineering and the Center for Biomedical Engineering, Ben-Gurion University, Beer-Sheva, 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.
Citation:
Raziel Haimi-Cohen, Arnon Cohen, "Gradient-Type Algorithms for Partial Singular Value Decomposition," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 9, no. 1, pp. 137-142, Jan. 1987, doi:10.1109/TPAMI.1987.4767879
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