In this paper a neural network for approximating function is described. The activation functions of the hidden nodes are the Radial Basis Functions (RBF) whose parameters are learnt by a two-stage gradient descent strategy. A new growing radial basis functions-node insertion strategy with different radial basis functions is used in order to improve the net performances. The learning strategy is...

A connectionist model made up of a combination of RBF networks is proposed the model decomposes multivalued dependencies into local single valued functions theory and applications are presented

On page 8 of the paper (page 3209 of the volume), in the seventh line of the second-to-last paragraph of section 5.

Motivated by 5] we describe a method related to scattered Hermite interpolation for which the solution of elliptic partial diierential equations by collocation is well-posed. We compare the method of 5] with our method. x1. Introduction In this paper we discuss the numerical solution of elliptic partial diierential equations using a collocation approach based on radial basis functions. To make ...