The nature of statistical learning theory
The nature of statistical learning theory
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Kernel Eigenfaces vs. Kernel Fisherfaces: Face Recognition Using Kernel Methods
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Incremental Kernel SVD for Face Recognition with Image Sets
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Online kernel PCA with entropic matrix updates
Proceedings of the 24th international conference on Machine learning
Fast Iterative Kernel Principal Component Analysis
The Journal of Machine Learning Research
Online prediction model based on support vector machine
Neurocomputing
Leading strategies in competitive on-line prediction
Theoretical Computer Science
Induction machine fault detection using support vector machine based classifier
WSEAS TRANSACTIONS on SYSTEMS
Online prediction of time series data with kernels
IEEE Transactions on Signal Processing
Online identification of nonlinear system using reduced kernel principal component analysis
Neural Computing and Applications
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This paper proposes the design and a comparative study of two proposed online kernel methods identification in the reproducing kernel Hilbert space and other two kernel method existing in the literature. The two proposed methods, titled SVD-KPCA, online RKPCA. The two other techniques named Sliding Window Kernel Recursive Least Square and the Kernel Recursive Least Square. The considered performances are the Normalized Means Square Error, the consumed time and the numerical complexity. All methods are evaluated by handling a chemical process known as the Continuous Stirred Tank Reactor and Wiener-Hammerstein benchmark.