On the Relationship between LS-SVM, MSA, and LSA
نویسندگان
چکیده
A common task in signal processing is to approximate adequately a signal. It is crucial to understand various methods to this task. In this paper we survey three different approximation methods: least squares support vector machine (LS-SVM), multiresolution signal approximation (MSA), and least squares approximation (LSA) to highlight their mathematical relationship. Based on the theoretical analysis, we prove that LS-SVM is identical to the LSA with the minimum norm solution, and MSA is identical to the LSA with the least squares solution. Therefore, both LS-SVM and MSA can be derived as specific instances of LSA.
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