On the use of KPCA pre-filtering for KCCA method

被引：2
|
作者：
Nadia Souilem
Ilyes Elaissi
Hassani Messaoud
机构：
[1] University of Monastir,Laboratory of Automatic Signal and Image Processing, National School of Engineers of Monastir
来源：
The International Journal of Advanced Manufacturing Technology | 2017年 / 91卷
关键词：
Kernel method; KCCA; PKCCA; KPCA; SVM; Wiener-Hammerstein benchmark;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
引用
收藏
页码：4331 / 4340
页数：9
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