Abstract

Networks can be considered as approximation schemes. Multilayer networks of the backpropagation type can approximate arbitrarily well continuous functions (Cybenko, 1989# Funahashi, 1989# Stinchcombe and White, 1989). Weprovethatnetworks derived from regularization theory and including Radial Basis Functions (Poggio and Girosi, 1989), have a similar property.From the point of view of approximation theory, however, the property of approximating continuous functions arbitrarily well is not sufficientforcharacterizing good approximation schemes. More critical is the property of best approximation. The main result of this paper is that multilayer networks, of the type used in backpropagation, are not best approximation. For regularization networks (in particular Radial Basis Function networks) we prove existence and uniqueness of best approximation.

Citations