Generalized Radial Basis Functions were used to construct networks
that learn input-output mappings from given data. They are
developed out of a theoretical framework for approximation based
on regularization techniques and represent a class of three-layer
networks similar to backpropagation networks with one hidden
layer.
A network using Gaussian base...