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In this paper we present a method for improving the generalization performance of a radial basis function (RBF) neural network. The method uses a statistical linear regression technique which is based on the orthogonal least squares (OLS) algorithm. We first discuss a modified way to determine the center and width of the hidden layer neurons. Then, substituting a QR algorithm for the traditional Gram-Schmidt algorithm, we find the connected weight of the hidden layer neurons. Cross-validationdoi:10.1016/j.eswa.2009.03.012 fatcat:5v72qrljtzcsxfnzepugtwxygi