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On the use of KPCA pre-filtering for KCCA method

On the use of KPCA pre-filtering for KCCA method 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The International Journal of Advanced Manufacturing Technology Springer Journals

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References (24)

Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer-Verlag London
Subject
Engineering; Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design
ISSN
0268-3768
eISSN
1433-3015
DOI
10.1007/s00170-017-0094-7
Publisher site
See Article on Publisher Site

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.

Journal

The International Journal of Advanced Manufacturing TechnologySpringer Journals

Published: Feb 13, 2017

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