Time series prediction using a rational fraction neural networks
K. Lee, Young-Ro Lee, Cris W. Barnes, Chris Aldrich, J. Kindel · University of North Texas Digital Library (University of North Texas) · 1988
An efficient neural network based on a rational fraction representation has been trained to perform time series prediction. The network is a generalization of the Volterra-Wiener network while still retaining the computational efficiency of the latter. Because of the second order convergent nature of the learning algorithm, the rational net is computationally far more efficient than multilayer networks. The rational fractional representation is, however, more restrictive than the multilayer networks.