a matrix \(A\) by a trial
vector \(v_1^{(k)}\) converges to the value of the eigenvector,
$$v_1^{(k+1)} = A v_1^{(k)} / \vert\vert A v_1^{(k)} \vert\vert $$
The corresponding eigenvalue is then found as
$$\lambda_1 = \frac{v_1^T A v_1}{v_1^T  v_1}$$</p>
<p>In pre-computer days, this method could be extended to find subsequent eigenvalue - eigenvector
pairs by "deflation", i.e., by applying the method again to the new matrix.
\(A - \lambda_1 v_1 v_1^{T} \).</p>
<p>This method is still used in some computer-i