Technical Report announcement

[Jeff Elman]

The following  abstract  describes  a  paper  which  can  be
obtained  from Hal White, Dept. of Economics D-008, Univ. of
Calif., San Diego, La Jolla, CA 92093.


Multi-layer feedforward networks are universal approximators
                             by
    Kurt Hornik, Maxwell Stinchcombe, and Halbert White

This paper rigorously establishes that standard  multi-layer
feedforward  networks  with as few as one hidden layer using
arbitrary squashing functions (not  necessarily  continuous)
at  the  hidden  layer(s)  are  capable of approximating any
Borel  measurable  function  from  one  Euclidean  space  to
another  to  any desired degree of accuracy, provided suffi-
ciently many hidden units are  available.   In  this  sense,
multi-layer  feedforward  networks  are a class of universal
approximators.