A feedforward neural net with d input neurons and with a single hidden
layer of n neurons is given by [GRAPHICS] where a(j), theta(j), w(ji)
is an element of R. In this paper we study the approximation of arbit
rary functions f: R-d --> R by a neural net in an L-p(mu) norm for som
e finite measure mu on R-d. We prove that under natural moment conditi
ons, a neural net with non-polynomial function can approximate any giv
en function. (C) 1998 Elsevier Science Ltd. All rights reserved.