- #1
dirk_mec1
- 761
- 13
Homework Statement
Let A be a symmetric n x n - matrix with eigenvalues and orthonormal eigenvectors [tex](\lambda_k, \xi_k)[/tex] assume ordening: [tex] \lambda_1 \leq...\leq \lambda_n [/tex]
We define the rayleigh coefficient as:
[tex]
R(x) = \frac{(Ax)^T x}{x^T x}
[/tex]Show that the following constrained problem produces the second eigenvalue and its eigenvector:
[tex]
min \left( R(X)| x \neq 0, x \bullet \xi_1 = 0 \right)
[/tex]
The Attempt at a Solution
In the first part of the exercise I was asked to proof that (without that inproduct being zero) the minimalisation produces the first eigenvalue. The idea was to use lagrange multipliers but I don't how to use it here.
Do I need to use Lagrange multipliers?
Last edited: