Generalized eigendecomposition with an on-line local algorithm

Abstract

This article presents a novel, on-line, local learning algorithm to obtain generalized eigenvalues and their corresponding eigenvectors in descending order with a linear adaptive filter. The filter is composed of a set of forward linear projections constrained by lateral inhibitions. Equilibrium points of the adaptation process and their stability are briefly analyzed. Simulations and experimental comparisons are given to verify the validity and effectiveness of the proposed algorithm.