A New Estimation Method for Radial Basis Function-based Models

Abstract

A structured nonlinear parameter optimization method (SNPOM) used to RBF network and RBF-ARX model parameter estimation is presented. This is an off-line nonlinear model parameter optimization method, which is developed based on the Levenberg-Marquardt method (LMM) for nonlinear parameter optimization and the Least Squares method (LSM) for linear parameter estimation. The SNPOM can accelerate the computational convergence of parameter optimization search process of the RBF-based models comparing with other algorithms. Some applications illustrate the usefulness.