(Eigenvalue,eigenvector) pair approximation by linear least squares

eigenvalues-eigenvectorsleast squareslinear algebramatricessoft-question

The other day I thought about the problem

$$\min_{\bf a}\{\|{\bf Ma}-\lambda {\bf a}\|_2^2+\epsilon\|{\bf a-d}\|_2^2\}$$

For a known triplet ${\bf M}, \lambda, {\bf d \neq 0}$

Minimum would be $0$ if $\bf d=a$ is an eigenvector with eigenvalue $\lambda$.

Could this be a start for (eigenvalue,eigenvector) approximation or am I just extra christmas-time wishful?

Best Answer

We can indeed use the question as outline for an algorithm:

$${\bf a_i} = \min_{\bf a}\{\|{\bf Ma}-\lambda_i {\bf a}\|_2^2+\epsilon\|{\bf a-d}_i\|_2^2\}$$

Let us start with ${\bf d}_1, \lambda_1$ either random if we have no clue or as some first guess.

We can devise the following update:

$${\bf d_{i+1} }= {\bf d_{i}- a_{i}}\\\lambda_{i+1} = \delta \cdot \lambda_{i} + (1-\delta)\cdot \text{mean}\left(\frac{\bf Ma_i}{\bf a_i}\right)\\ s.t. \delta \in [0,1]$$ We use $\epsilon = 10^{-1}, \delta = 1/4$ in following experiment. Below is example log2 plot of error:

enter image description here

Merry Christmas!