A Fast Adaptive Algorithm for the Generalized Symmetric Eigenvalue Problem
Samir Attallah, Karim Abed‐Meraim · IEEE Signal Processing Letters · 2008
In this letter, we propose a new adaptive algorithm for the generalized symmetric eigenvalue problem, which can extract the principal and minor generalized eigenvectors, as well as their corresponding subspaces, at a low computational cost. A comparison with other adaptive algorithms from the literature, including the batch generalized singular value decomposition (GSVD) technique, is also given to show the superiority of the proposed algorithm in terms of convergence performance and computational complexity.