Time series forecasting using recurrent neural networks and wavelet reconstructed signals

Abstract

In this paper a novel neural network architecture for medium-term time series forecasting is presented. The proposed model, inspired on the Hybrid Complex Neural Network (HCNN) model, takes advantage of information obtained by wavelet decomposition and of the oscillatory abilities of recurrent neural networks (RNN). The prediction accuracy of the proposed… (More)
DOI: 10.1109/CONIELECOMP.2010.5440775

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