title: Synthesis of feedforward networks in supremum error bound.
abstract: The main result of this paper is a constructive proof of a formula for the upper bound of the approximation error in Linfinity (supremum norm) of multidimensional functions by feedforward networks with one hidden layer of sigmoidal units and a linear output. This result is applied to formulate a new method of neural-network synthesis. The result can also be used to estimate complexity of the maximum-error network and/or to initialize that network weights. An example of the network synthesis is given.
authors.affiliation: Department of Mathematics, West Virginia University, Morgantown, WV 26506, USA. K_cies@math.wvu.edu
authors.forename: K
authors.initials: K
authors.lastname: Ciesielski
authors.forename: J P
authors.initials: JP
authors.lastname: Sacha
authors.forename: K J
authors.initials: KJ
authors.lastname: Cios