Additionally, advancements in parallel computing frameworks have invigorated classical matrix iteration methods, providing robust solutions for large, sparse generalised eigenvalue problems.

These methods are based on the transformation of A to quasi-stochastic form by diagonal matrices where, in contrast to other classes of methods, the whole diagonal consists of numbers different from 1 ...

The QR algorithm is currently the most popular method for finding all eigenvalues of a full matrix. While QR is now well understood by specialists in eigenvalue computations, this understanding is not ...