Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)

On System Identification Based on Online Least Squares Support Vector Machine

Authors
Bin Liu1, Zhiping Wang
1Department of Computer, Shaanxi University of Science and Technology
Corresponding Author
Bin Liu
Available Online October 2007.
DOI
10.2991/iske.2007.184How to use a DOI?
Keywords
System identification, Online learning, Least squares support vector machine
Abstract

System identification is a fundamental topic of control theory, and LS-SVM has been applied to system identification. An online training algorithm of LS-SVM for system identi cation is presented, which is suitable for the data set supplied in sequence rather than in batch. The online algorithm avoids computing large-scale matrix inverse when the number of support vectors changes, thus the computation time is reduced. In order to validate the performance of the online algorithm, the system identification experiments are considered. The simulation results show that the online training algorithm is suitable for the online system identification.

Copyright
© 2007, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
Series
Advances in Intelligent Systems Research
Publication Date
October 2007
ISBN
978-90-78677-04-8
ISSN
1951-6851
DOI
10.2991/iske.2007.184How to use a DOI?
Copyright
© 2007, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Bin Liu
AU  - Zhiping Wang
PY  - 2007/10
DA  - 2007/10
TI  - On System Identification Based on Online Least Squares Support Vector Machine
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 1084
EP  - 1087
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.184
DO  - 10.2991/iske.2007.184
ID  - Liu2007/10
ER  -