title: Representations and rates of approximation of real-valued Boolean functions by neural networks.
abstract: We give upper bounds on rates of approximation of real-valued functions of d Boolean variables by one-hidden-layer perceptron networks. Our bounds are of the form c/n where c depends on certain norms of the function being approximated and n is the number of hidden units. We describe sets of functions where these norms grow either polynomially or exponentially with d.
authors.affiliation: Institute of Computer Science, Academy of Sciences of the Czech Republic, Pod vodárensku vezi; 2, P.O. Box 5 182 07, Prague, Czech Republic
authors.forename: V
authors.lastname: Kůrková
authors.forename: P
authors.initials: P
authors.lastname: Savický
authors.forename: K
authors.initials: K
authors.lastname: Hlavácková