title: A parameter optimization method for radial basis function type models.
abstract: This paper considers the nonlinear systems modeling problem for control. A structured nonlinear parameter optimization method (SNPOM) adapted to radial basis function (RBF) networks and an RBF network-style coefficients autoregressive model with exogenous variable model parameter estimation is presented. This is an off-line nonlinear model parameter optimization method, depending partly on the Levenberg-Marquardt method for nonlinear parameter optimization and partly on the least-squares method using singular value decomposition for linear parameter estimation. When compared with some other algorithms, the SNPOM accelerates the computational convergence of the parameter optimization search process of RBF-type models. The usefulness of this approach is illustrated by means of several examples.
authors.affiliation: Coll. of Inf. Sci. and Eng., Central South Univ., China.
authors.forename: Hui
authors.initials: H
authors.lastname: Peng
authors.forename: T
authors.initials: T
authors.lastname: Ozaki
authors.forename: V
authors.initials: V
authors.lastname: Haggan-Ozaki
authors.forename: Y
authors.initials: Y
authors.lastname: Toyoda