SingularValueDecomposition
For an m-by-n matrix A with m >= n, the singular value decomposition is
an m-by-n orthogonal matrix U, an n-by-n diagonal matrix S, and
an n-by-n orthogonal matrix V so that A = U*S*V'.
//secondary diagonal - the diagonal of a square matrix running from the lower left entry to the upper right entry
to implement it use ....
1. first element is 0 and col
2. second element is (0+1)or1 and col-1
3. third element is (1+1)or2 and col-2
4. and so on till rows() and 0 is reached ..