Interpolation networks

This paper introduces a new type of network based on local response units, the `interpolation networks´ (INs). Under certain conditions this network is an interpolator. Its formulation allows a type of initialisation by prototypes that will set the net in a good initial starting point for the subsequent supervised learning process. These networks can be seen as a type of radial basis functions network (RBFN). However, their basis functions are essentially inverse squared distances instead of Gaussian functions. A brief description of the origin and motivation of INs is made in the first section, followed by the description of the first experiments with these networks