Fast RLS-Like Algorithm for Generalized Eigendecomposition and its Applications

Generalized eigendecomposition (GED) plays a vital role in many signal-processing applications. In this paper, we will propose a new method for computing the generalized eigenvectors, which is on-line and resembles the RLS algorithm for Wiener filtering. We further present a proof to show convergence to the exact solution and simulations have shown that the algorithm is faster than most of the traditional methods. This algorithm belongs to the class of fixed-point algorithms and hence does not require any external step-size parameters like the gradient-based methods. Simulations are performed on synthetic data and compared with other algorithms found in literature. Finally we will demonstrate the application of GED in the design of a CDMA receiver for direct-sequence spread spectrum signals.