Nadia Souilem, Ilyes Elaissi, Okba Taouali, Hassani Messeouad, "New Online RKPCA-RN Kernel Method Applied to Tennessee Eastman Process," WSEAS Transactions on Systems, vol. 12, pp. -, 2013, DOI:
Nadia Souilem, Ilyes Elaissi, Okba Taouali, Hassani Messeouad. New Online RKPCA-RN Kernel Method Applied to Tennessee Eastman Process.
WSEAS Transactions on Systems. 2013;12:-.
WSEAS Transactions on Systems
Print ISSN: 1109-2777, E-ISSN: 2224-2678
Volume 12, 2013
New Online RKPCA-RN Kernel Method Applied to Tennessee Eastman Process
Authors: , , ,
Abstract: This paper proposes a new method for online identification of a nonlinear system using RKHS models. The RKHS model is a linear combination of kernel functions applied to the used training set observations. For large datasets, this kernel based to severs computational problems and makes identification techniques unsuitable to the online case. For instance, in the KPCA scheme the Gram matrix order grows with the number of training observations and its eigen decomposition. The proposed method is based on Reduced Kernel Principal Component Analysis technique (RKPCA), to extract the principal component will be time consuming.
Pages: - WSEAS Transactions on Systems, ISSN / E-ISSN: 1109-2777 / 2224-2678, Volume 12, 2013DOI: *As the DOI is a unique identifier, it is already available in the pdf version.
**The DOI link will be activated in the first midst of January 2026.
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