New Method for Filtered ICA Signals Applied To Volatile Time Series.

Authors:
J.M. Górriz;Carlos G. Puntonet;Moisés Salmerón;Julio Ortega
Affiliations:
Dpto. Ingeniería de Sistemas y Automática, Tec. Electrónica y Electrónica, Universidad de Cádiz, Spain and Dpto. Arquitectura y Tecnología de Computadores, Universida ...;Dpto. Ingeniería de Sistemas y Automática, Tec. Electrónica y Electrónica, Universidad de Cádiz, Spain and Dpto. Arquitectura y Tecnología de Computadores, Universida ...;Dpto. Ingeniería de Sistemas y Automática, Tec. Electrónica y Electrónica, Universidad de Cádiz, Spain and Dpto. Arquitectura y Tecnología de Computadores, Universida ...;Dpto. Ingeniería de Sistemas y Automática, Tec. Electrónica y Electrónica, Universidad de Cádiz, Spain and Dpto. Arquitectura y Tecnología de Computadores, Universida ...
Venue:
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
Year:
2009

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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.