New method for filtered ICA signals applied to volatile time series

Abstract

In this paper we propose a new method for volatile time series forecasting using techniques like Independent Component Analysis (ICA) or Savitzky-Golay filtering as preprocessing tools. The preprocessed data will be introduce in a based radial basis functions (RBF) Artificial Neural Network (ANN) and the prediction result will be compared with the one we get without these preprocessing tools or the classical Principal Component Analysis (PCA) tool. © Springer-Verlag Berlin Heidelberg 2003.