Long term prediction of non-linear time series using multiresolution wavelet models
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Publication:5491402
DOI10.1080/00207170600621447zbMath1179.37111OpenAlexW2062336288MaRDI QIDQ5491402
Hua-Liang Wei, Stephen A. Billings
Publication date: 11 October 2006
Published in: International Journal of Control (Search for Journal in Brave)
Full work available at URL: http://eprints.whiterose.ac.uk/84820/1/acse%20research%20report%20882.pdf
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40) Time series analysis of dynamical systems (37M10) Application of orthogonal and other special functions (94A11)
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Cites Work
- A wavelet-based approach for model and parameter identification of non-linear systems
- Nonlinear prediction of chaotic time series
- Multivariate adaptive regression splines
- On the use of the wavelet decomposition for time series prediction
- Local averaging optimization for chaotic time series prediction
- Predicting chaotic time series with wavelet networks
- Towards long-term prediction
- Modelling and analysis of non-linear time series
- A theory for multiresolution signal decomposition: the wavelet representation
- Orthogonal parameter estimation algorithm for non-linear stochastic systems
- Identification of non-linear output-affine systems using an orthogonal least-squares algorithm
- Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
- Ten Lectures on Wavelets
- Orthogonal least squares methods and their application to non-linear system identification
- PREDICTION OF CHAOTIC TIME SERIES WITH NEURAL NETWORKS AND THE ISSUE OF DYNAMIC MODELING
- Continuous-Time System Identification for Linear and Nonlinear Systems Using Wavelet Decompositions
- A new direct approach of computing multi-step ahead predictions for non-linear models
- Wavelet-based system identification for nonlinear control
- DISCRETE WAVELET MODELS FOR IDENTIFICATION AND QUALITATIVE ANALYSIS OF CHAOTIC SYSTEMS
- Oscillation and Chaos in Physiological Control Systems
- The wavelet-NARMAX representation: A hybrid model structure combining polynomial models with multiresolution wavelet decompositions
- Term and variable selection for non-linear system identification
- Identification of time-varying systems using multiresolution wavelet models
- A unified wavelet-based modelling framework for non-linear system identification: the WANARX model structure
- Time-varying system identification and model validation using wavelets
- Wavelet Reconstruction of Nonlinear Dynamics