On neuro-wavelet modeling

Fionn Murtagh; Jean Luc Starck; Olivier Renuad

doi:10.1016/S0167-9236(03)00092-7

On neuro-wavelet modeling

Fionn Murtagh, Jean Luc Starck, Olivier Renuad

Research output: Contribution to journal › Review article

100 Citations (Scopus)

Abstract

We survey a number of applications of the wavelet transform in time series prediction. The Haar à trous wavelet transform is proposed as a means of handling time series data when future data is unknown. Results are exemplified on financial futures and S&P500 data. Nonlinear and linear multiresolution autoregressionmodels are studied. Experimentally, we show that multiresolution approaches can outperform the traditional single resolution approach to modeling and prediction.

Original language	English
Pages (from-to)	475-484
Number of pages	10
Journal	Decision Support Systems
Volume	37
Issue number	4
Early online date	3 Jul 2003
DOIs	https://doi.org/10.1016/S0167-9236(03)00092-7
Publication status	Published - 1 Sep 2004
Externally published	Yes

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Murtagh, F., Starck, J. L., & Renuad, O. (2004). On neuro-wavelet modeling. Decision Support Systems, 37(4), 475-484. https://doi.org/10.1016/S0167-9236(03)00092-7

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