Modelling dynamic processes with clustered time-delay neurons

Neumerkel, D., Murray-Smith, R. and Gollee, H. (1993) Modelling dynamic processes with clustered time-delay neurons. In: IJCNN '93: Proceedings of the International Joint Conference on Neural Networks, 25-29 October 1993, Nagoya, Japan. IEEE Computer Society: Piscataway, N.J., USA, pp. 1765-1768. ISBN 9780780314221 (doi: 10.1109/IJCNN.1993.716995)

Abstract

This paper investigates the modelling capabilities of neural nets for a dynamic nonlinear process. Different neural structures are compared: multilayer perceptron (MLP) and radial basis function network (RBF) with an external tapped delay line, and modifications of both network types using internal delays, called time-delay MLP (TDMLP) and time-delay RBF (TDRBF). The nonlinear process to be modelled is a drive system including some nonlinearities, e.g. saturation effects. A special clustering procedure is introduced in order to increase the modelling accuracy, reduce computation and provide better generalisation.

• Item Type: Book Sections
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Murray-Smith, Professor Roderick and Gollee, Dr Henrik
• Authors: Neumerkel, D., Murray-Smith, R., and Gollee, H.
• Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
• College/School: College of Science and Engineering > School of Computing Science; College of Science and Engineering > School of Engineering > Biomedical Engineering
• Publisher: IEEE Computer Society
• ISBN: 9780780314221