# Singular Value Decomposition and Generalized Inverse

The SVD of an m by n matrix A is a matrix decomposition, A = USVT. With q = min(m, n), the factors Um x q and Vn x q are orthogonal matrices, and Sq x q is a nonnegative diagonal matrix with nonincreasing diagonal terms. The IMSL_SVDCOMP function computes the singular values of A by default. By using keywords, you can also obtain part or all of the U and V matrices, an estimate of the rank of A, and the generalized inverse of A.