Referenced Items are not available for this document.
Training problem of least squares support vector machine (LS-SVM) is solved by finding a solution to a set of linear equations. This makes online adaptive implementation of the algorithm feasible. In this paper, an adaptive algorithm for the purpose of nonlinear system identification is proposed. Using this training algorithm, a variant of support vector machine has been developed called adaptive LS-SVM. The adaptive LS-SVM is especially useful on online system identification. Several pertinent numerical simulations have shown the validity of the proposed method
Published in:
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
(Volume:1
)
Date of Conference: 0-0 0
- Page(s):
- 1897 - 1900
- Print ISBN:
- 1-4244-0332-4
- INSPEC Accession Number:
- 9187637
- Conference Location :
- Dalian
- Digital Object Identifier :
- 10.1109/WCICA.2006.1712685
- Product Type:
- Conference Publications
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