Identification of MIMO Hammerstein models using least squares support vector machines
作者： Ivan Goethals , Kristiaan Pelckmans , Johan A.K. Suykens , Bart De Moor
DOI: 10.1016/J.AUTOMATICA.2005.02.002
关键词:
摘要: This paper studies a method for the identification of Hammerstein models based on least squares support vector machines (LS-SVMs). The technique allows determination memoryless static nonlinearity as well estimation model parameters dynamic ARX part. is done by applying equivalent Bai's overparameterization systems in an LS-SVM context. SISO MIMO cases are elaborated. can lead to significant improvements with respect classical methods illustrated number examples. Another important advantage that no stringent assumptions nature need be imposed except certain degree smoothness.
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