Robust structure selection of radial basis function networks for nonlinear system identification

This paper proposed a robust structure selection method of radial basis function (RBF) networks for nonlinear system identification problems. A greedy algorithm is first employed by combining information criteria with the forward stepwise selection to choose the RBF network structures. Then, a robust selection procedure, which can select a concise and generalized network structure, is developed based on the forward stepwise selection and the subsampling method. Finally, a numerical example is given to illustrate the effectiveness of the proposed method by using the disturbance storm time index data.