1 MatrixXf m
= MatrixXf::Random(3,2);
2 cout
<< "Here is the matrix m:" << endl
<< m
<< endl
;
3 JacobiSVD
<MatrixXf
> svd(m
, ComputeThinU
| ComputeThinV
);
4 cout
<< "Its singular values are:" << endl
<< svd
.singularValues() << endl
;
5 cout
<< "Its left singular vectors are the columns of the thin U matrix:" << endl
<< svd
.matrixU() << endl
;
6 cout
<< "Its right singular vectors are the columns of the thin V matrix:" << endl
<< svd
.matrixV() << endl
;
8 cout
<< "Now consider this rhs vector:" << endl
<< rhs
<< endl
;
9 cout
<< "A least-squares solution of m*x = rhs is:" << endl
<< svd
.solve(rhs
) << endl
;