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Orthogonal least squares methods and their application to non-linear system identification

Orthogonal least squares methods and their application to non-linear system identification
Orthogonal least squares methods and their application to non-linear system identification
Identification algorithms based on the well-known linear least squares methods of
gaussian elimination, Cholesky decomposition, classical Gram-Schmidt, modified
Gram-Schmidt, Householder transformation, Givens method, and singular value
decomposition are reviewed. The classical Gram-Schmidt, modified Gram-Schmidt,
and Householder transformation algorithms are then extended to combine
structure determination, or which terms to include in the model, and parameter
estimation in a very simple and efficient manner for a class of multivariable
discrete-time non-linear stochastic systems which are linear in the parameters.
0020-3270
1873-1896
Billings, S. A.
8e258823-ff22-4f19-a457-18479caa30c5
Luo, W.
a24a610b-a0be-428b-9190-32501d62f1e3
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Billings, S. A.
8e258823-ff22-4f19-a457-18479caa30c5
Luo, W.
a24a610b-a0be-428b-9190-32501d62f1e3
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80

Billings, S. A., Luo, W. and Chen, Sheng (1989) Orthogonal least squares methods and their application to non-linear system identification. International Journal of Control, 50 (5), 1873-1896.

Record type: Article

Abstract

Identification algorithms based on the well-known linear least squares methods of
gaussian elimination, Cholesky decomposition, classical Gram-Schmidt, modified
Gram-Schmidt, Householder transformation, Givens method, and singular value
decomposition are reviewed. The classical Gram-Schmidt, modified Gram-Schmidt,
and Householder transformation algorithms are then extended to combine
structure determination, or which terms to include in the model, and parameter
estimation in a very simple and efficient manner for a class of multivariable
discrete-time non-linear stochastic systems which are linear in the parameters.

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More information

Published date: 1 November 1989
Additional Information: Address: London
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 251147
URI: http://eprints.soton.ac.uk/id/eprint/251147
ISSN: 0020-3270
PURE UUID: 7f8df69f-8e94-488e-a11d-e97440dfe52e

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Date deposited: 12 Oct 1999
Last modified: 06 Sep 2021 16:32

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Contributors

Author: S. A. Billings
Author: W. Luo
Author: Sheng Chen

University divisions

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