A modified orthogonal forward regression least-squares algorithm for system modelling from noisy regressors

DOI10.1080/00207170600891941zbMath1120.93018OpenAlexW2151618694MaRDI QIDQ3447415

Lingzhong Guo, Stephen A. Billings

Publication date: 19 June 2007

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: http://eprints.whiterose.ac.uk/74554/1/911.pdf

zbMATH Keywords

system identificationorthogonal forward regression least-squares algorithmunbiased estimates of error reduction ratios

Mathematics Subject Classification ID

Related Items (1)

Parameter consistency and quadratically constrained errors-in-variables least-squares identification

Cites Work

• Correlation based model validity tests for non-linear models
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• Identification of non-linear output-affine systems using an orthogonal least-squares algorithm
• Orthogonal least squares methods and their application to non-linear system identification
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• Algorithms for minimal model structure detection in nonlinear dynamic system identification
• RETRIEVING DYNAMICAL INVARIANTS FROM CHAOTIC DATA USING NARMAX MODELS
• Term and variable selection for non-linear system identification
• Identification of coupled map lattice models of stochastic spatio-temporal dynamics using wavelets
• Improved structure selection for nonlinear models based on term clustering
• Identification of coupled map lattice models of complex spatio-temporal patterns

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