Robust functional principal components: A projection-pursuit approach
  In many situations, data are recorded over a period of time and may be regarded as realizations of a stochastic process. In this paper, robust estimators for the principal components are considered by adapting the projection pursuit approach to the functional data setting. Our approach combines robust projection-pursuit with different smoothing methods. Consistency of the estimators are shown under mild assumptions. The performance of the classical and robust procedures are compared in a simulation study under different contamination schemes. 
Juan Lucas Bali, Graciela Boente, David E. Tyler, Jane-Ling Wang
math.ST stat.TH