Asymptotic performance analysis of PCA algorithms based on the weighted subspace criterion

摘要

This paper studies the asymptotic distribution of the eigenvectors estimated by some PCA algorithms based on the weighted subspace criterion. This enables us to analyse how the choice of the weighting matrix affects the algorithm's performance, an issue previously overlooked.