Using reservoir computing in a decomposition approach for time series prediction
Francis wyffels, Benjamin Schrauwen, Dirk Stroobandt · Ghent University Academic Bibliography (Ghent University) · 2008
In this paper we combine wavelet decomposition and recurrent neural networks to provide fast and accurate time series predictions. The original time series is decomposed by means of wavelet decomposition into a hierarchy of time series which are easier to predict. The prediction core of our solution is given by reservoir computing, which is a recently developed technique for the very fast training of recurrent neural networks. The three time series of the ESTSP 2008 competition will be used as an illustration for our method.