Linear programming support vector regression with wavelet kernel: A new approach to nonlinear dynamical systems identification

DOI10.1016/j.matcom.2008.10.011zbMath1161.65313OpenAlexW2009984955MaRDI QIDQ1013139

Kenneth R. Butts, Zhao Lu, Jing Sun

Publication date: 17 April 2009

Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.matcom.2008.10.011

zbMATH Keywords

linear programminglearning algorithmssupport vector regressionwavelet kernelnonlinear systems identification

Mathematics Subject Classification ID

Related Items (3)

Use of support vector regression in structural optimization: application to vehicle crashworthiness design ⋮ Local Quadratic Model Tree with Orthogonal Matching Pursuit (LOQUMOTOMP) Method for Nonlinear System Identification ⋮ A pruning method of refining recursive reduced least squares support vector regression

Cites Work

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• Time series prediction using support vector machines, the orthogonal and the regularized orthogonal least-squares algorithms
• Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel
• Wavelet Reconstruction of Nonlinear Dynamics
• A new method for sparsity control in support vector classification and regression

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