Convergence Analysis of Möller Algorithm for Estimating Minor Component

摘要

The minor component analysis (MCA) deals with the recovery of the eigenvector associated with the smallest eigenvalue of the autocorrelation matrix of the input data, and Möller algorithm is a famous self-stability MCA method. In this paper, we present a convergence analysis of Möller algorithm for estimating minor component of an input signal via a deterministic discrete time method. Some sufficient conditions are obtained to guarantee the convergence of Möller algorithm. Simulations are carried out to further illustrate the theoretical results achieved.