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.