Wavelet-based combined signal filtering and prediction

Olivier Renaud; Jean Luc Starck; Fionn Murtagh

doi:10.1109/TSMCB.2005.850182

Wavelet-based combined signal filtering and prediction

Olivier Renaud, Jean Luc Starck, Fionn Murtagh

Research output: Contribution to journal › Article

127 Citations (Scopus)

Abstract

We survey a number of applications of the wavelet transform in time series prediction. We show how multiresolution prediction can capture short-range and long-term dependencies with only a few parameters to be estimated. We then develop a new multiresolution methodology for combined noise filtering and prediction, based on an approach which is similar to the Kalman filter. Based on considerable experimental assessment, we demonstrate the powerfulness of this methodology.

Original language	English
Pages (from-to)	1241-1251
Number of pages	11
Journal	IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume	35
Issue number	6
Early online date	21 Nov 2005
DOIs	https://doi.org/10.1109/TSMCB.2005.850182
Publication status	Published - 1 Dec 2005
Externally published	Yes

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abstract = "We survey a number of applications of the wavelet transform in time series prediction. We show how multiresolution prediction can capture short-range and long-term dependencies with only a few parameters to be estimated. We then develop a new multiresolution methodology for combined noise filtering and prediction, based on an approach which is similar to the Kalman filter. Based on considerable experimental assessment, we demonstrate the powerfulness of this methodology.",

keywords = "Autoregression, Filtering, Forecasting, Kalman filter, Model, Resolution, Scale, Time series, Wavelet transform",

author = "Olivier Renaud and Starck, {Jean Luc} and Fionn Murtagh",

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AU - Starck, Jean Luc

AU - Murtagh, Fionn

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N2 - We survey a number of applications of the wavelet transform in time series prediction. We show how multiresolution prediction can capture short-range and long-term dependencies with only a few parameters to be estimated. We then develop a new multiresolution methodology for combined noise filtering and prediction, based on an approach which is similar to the Kalman filter. Based on considerable experimental assessment, we demonstrate the powerfulness of this methodology.

AB - We survey a number of applications of the wavelet transform in time series prediction. We show how multiresolution prediction can capture short-range and long-term dependencies with only a few parameters to be estimated. We then develop a new multiresolution methodology for combined noise filtering and prediction, based on an approach which is similar to the Kalman filter. Based on considerable experimental assessment, we demonstrate the powerfulness of this methodology.

KW - Autoregression

KW - Filtering

KW - Forecasting

KW - Kalman filter

KW - Model

KW - Resolution

KW - Scale

KW - Time series

KW - Wavelet transform

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M3 - Article

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AN - SCOPUS:29144431556

VL - 35

SP - 1241

EP - 1251

JO - IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

JF - IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

SN - 1083-4419

IS - 6

ER -

Wavelet-based combined signal filtering and prediction

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