svd( A, U, S, V)  computes the Singular Value Decomposition of A and returns
	the rank of A.  For an m-by-n matrix A, U*S*V' = A, where U is m-by-m
	orthogonal, S is m-by-n diagonal containing the singular values in
	decreasing order, and V is n-by-n orthogonal.