Reproducing wavelet kernel method in nonlinear system identification |
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Authors: | WEN Xiang-jun XU Xiao-ming CAI Yun-ze |
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Affiliation: | 1. Dept.of Automation, Shanghai Jiaotong University, Shanghai 200240, China;NNPSB of Guangxi Power Grid Corp. , Nanning 530031 , China 2. Dept.of Automation, Shanghai Jiaotong University, Shanghai 200240, China |
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Abstract: | By combining the wavelet decomposition with kernel method, a practical approach of universal multi-scale wavelet kernels constructed in reproducing kernel Hilbert space (RKHS) is discussed, and an identifica-tion scheme using wavelet support vector machines ( WSVM ) estimator is proposed for nonlinear dynamic sys-tems. The good approximating properties of wavelet kernel function enhance the generalization ability of the pro-posed method, and the comparison of some numerical experimental results between the novel approach and some existing methods is encouraging. |
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Keywords: | wavelet kernels support vector machine ( SVM ) reproducing kernel Hilbert space (RKHS) nonlinear system identification |
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