论文信息 - Adaptive nonlinear filtering with the support vector method

Adaptive nonlinear filtering with the support vector method

The recently introduced Support Vector Method (SVM) is one of the most powerful methods for training a Radial Basis Function (RBF) filter in a batch mode. This paper proposes a modification of this method for on-line adaptation of the filter parameters on a block-by-block basis. The proposed method requires a limited number of computations and compares well with other adaptive RBF filters.

Simon Haykin | Francesco Palmieri | Davide Mattera

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