FUNCTION ESTIMATION WITH NEURAL NETS

We report on the use of multilayer networks as 'estimators' of functio ns, or their application to problems of nonlinear regression. A set of target functions with adjustable complexity is used. The results of e mpirical investigation into the extent to which function estimation is possible, and the relationship between the network parameters, are pr esented. This could provide the designer of a neural-based system with some intuition about the design choices to be made.