Nonlinear time series modelling and predictionusing Gaussian RBF networks with enhancedclustering and RLS learning

An improved clustering and recursive least squares (RLS) learning algorithm for Gaussian radial basis function (RBF) networks is described for modelling and predicting nonlinear time series. Significant performance gain can be achieved with a much smaller network compared with the usual clustering and RLS method.