Abstract
Singular value decomposition (SVD) is a factorization of a real or complex matrix in the form A = USV*, where U and V are unitary and S is diagonal. SVD exists for every matrix A. This factorization is useful in many cases, such as minimum squares calculation and approximation of A with low rank matrixes. This last technique is largely employed in large-scale matrix processing. Classic me…