Adaptive orthogonal least squares learning algorithm for the radial basis function network

This paper presents an algorithm to select the parameters of a radial basis function network based on the orthogonal least squares (OLS) learning algorithm. To improve the OLS learning process, an additional procedure to modify the selected node´s parameter during training is introduced. Using simulation results, we show that significant improvement to the selected model´s performance can be achieved by the proposed algorithm