Nonlinear black-box modeling in system identification: a unified overview
Automatica (Journal of IFAC) - Special issue on trends in system identification
Matrix computations (3rd ed.)
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
On the eigenspectrum of the gram matrix and the generalization error of kernel-PCA
IEEE Transactions on Information Theory
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The application of kernel method to petrochemical industry is explored in this paper. A nonlinear soft analyzer for the flashpoint measurement of Dearomatization process is developed by using kernel principal component regression (KPCR) method. To trace the time varying dynamics and reject disturbances, a novel online eigenspace decomposing algorithm is proposed to update that of the Kernel Matrix, which is much faster than direct decomposition and meanwhile has stable numerical performance. Simulation results indicate the developed soft analyzer has satisfying prediction precision under both nominal and faulty operating conditions.