Fast orthogonal identification of nonlinear stochastic models and radial basis function neural networks

DOI10.1080/00207179608921662zbMath0858.93069OpenAlexW2043313903MaRDI QIDQ4894040

Quanmin Zhu, Stephen A. Billings

Publication date: 25 March 1997

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

Full work available at URL: http://eprints.whiterose.ac.uk/79798/1/acse%20research%20report%20526.pdf

zbMATH Keywords

identificationnonlinearautoregressive moving averageradial basis functions neural networks

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Nonlinear systems in control theory (93C10) Identification in stochastic control theory (93E12)

Related Items (13)

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Cites Work

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• Interpolation of scattered data: distance matrices and conditionally positive definite functions
• Rational model identification using an extended least-squares algorithm
• Non-linear systems identification using radial basis functions
• Model selection and validation methods for non-linear systems
• Orthogonal parameter estimation algorithm for non-linear stochastic systems
• Identification of non-linear output-affine systems using an orthogonal least-squares algorithm
• Extended model set, global data and threshold model identification of severely non-linear systems
• Orthogonal least squares methods and their application to non-linear system identification

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