Robust on-line Principal Component Analysis based on a fixed-point approach

Abstract

Principal Component Analysis (PCA) is a widely used statistical tool in many signal-processing applications. In this paper we will present a new on-line algorithm for computing the principal components. The new algorithm belongs to a class of fixed-point methods. We mathematically investigate the convergence properties of the method and also verify the robustness of the algorithm with simulations.