Some Fortran subroutines for Computing the Singular Value Decomposition of a real Matrix

In this paper we specify the calling sequences of several FORTRAN programs for computing the singular value decomposition (SVD) of a matrix and computing the solution of the linear least squares problem using the SVD of the coefficient matrix. The SVD of a matrix is helpful in indicating the condition of a matrix, i.e. how close a matrix is to a singular matrix or to one of lower rank. The SVD of a matrix has been useful in least squares problems, as well as in solving integral equations and in digital image processing.