Optimal Radial Basis Function Nets with Applications to Nonlinear Function Learning and Classification

摘要

Single layer radial basis function (RBF) networks in nonlinear functional estimation and classification are considered. Analytical expressions the optimal radial functions are given and the optimal rates of convergence in the class of smooth functions are derived.