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The routine computes the minimum norm solution to a real linear least squares problem: minimize ||b - A*x|| using the singular value decomposition (SVD) of a rectangular matrix A, which may be rank-deficient.
Several right-hand side vectors b and solution vectors x can be handled in a single call; they are stored as the columns of the right-hand side matrix B and the solution matrix X.
The effective rank of A equals the number of the singular values, which are greater than rcond multiplied by the largest singular value.
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