Abstract
In this paper, we propose a kernel method to build RKHS models of nonlinear system. This method entitled prefiltered kernel canonical correlation analysis (PKCCA) performs a prefiltering prior to the use of KCCA in order to avoid low variances between canonical coefficients and the learning data set observations. The prefilter phase is based on KPCA. The method is used to identify a benchmark nonlinear system and is compared to KCCA and SVM.
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