Abstract
An admissible support vector (SV) kernel (the wavelet kernel), by which we can construct a wavelet support vector machine (SVM), is presented. The wavelet kernel is a kind of multidimensional wavelet function that can approximate arbitrary nonlinear functions. The existence of wavelet kernels is proven by results of theoretic analysis. Computer simulations show the feasibility and validity of wavelet support vector machines (WSVMs) in regression and pattern recognition.
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CITATION STYLE
Zhang, L., Zhou, W., & Jiao, L. (2004). Wavelet Support Vector Machine. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 34(1), 34–39. https://doi.org/10.1109/TSMCB.2003.811113
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