1MatrixXf m = MatrixXf::Random(3,2); 2cout << "Here is the matrix m:" << endl << m << endl; 3JacobiSVD<MatrixXf> svd(m, ComputeThinU | ComputeThinV); 4cout << "Its singular values are:" << endl << svd.singularValues() << endl; 5cout << "Its left singular vectors are the columns of the thin U matrix:" << endl << svd.matrixU() << endl; 6cout << "Its right singular vectors are the columns of the thin V matrix:" << endl << svd.matrixV() << endl; 7Vector3f rhs(1, 0, 0); 8cout << "Now consider this rhs vector:" << endl << rhs << endl; 9cout << "A least-squares solution of m*x = rhs is:" << endl << svd.solve(rhs) << endl; 10