Rational Parametrizations of Neural Networks

Part of Advances in Neural Information Processing Systems 5 (NIPS 1992)

Bibtex Metadata Paper

Authors

Uwe Helmke, Robert C. Williamson

Abstract

A connection is drawn between rational functions, the realization theory of dynamical systems, and feedforward neural networks. This allows us to parametrize single hidden layer scalar neural networks with (almost) arbitrary analytic activation functions in terms of strictly proper rational functions. Hence, we can solve the uniqueness of parametrization problem for such networks.