Use the svd function to perform SVD factorization of matrices. This is useful in solving linear systems. The algorithms underlying these functions are also used in lsolve.
1. Input a real matrix M (not necessarily square).
2. Use the svd function to perform SVD decomposition of matrix M. Uncollapse the nested matrices to view their content.
3. Show that the svds function returns a vector of singular values of matrix M, and that it is identical to the first nested array of the results returned by the svd function.
4. Set variables s, U and V to be element 0, 1 and 2, respectively of matrix S.
5. Use the diag function to create a matrix whose diagonal elements are the elements of s.
6. Show that the product of U, D and V returns input matrix M.