Community Research and Development Information Service - CORDIS

Abstract

Neural networks provide a new tool for the fast solution of non-linear curve fitting problems. In this paper it is shown how such networks can be used for fitting functional forms to experimental data. The neural network algorithm is typically much faster than conventional iterative approaches. In addition, further substantial improvements in speed can be obtained by using special purpose hardware implementations of the network, thus making the technique suitable for use in fast real-time applications. The basic concepts are illustrated using a simple example from fusion research, involving the determination of spectral line parameters from measurements of Boron IV impurity radiation in the COMPASS-C tokamak.

Additional information

Authors: BISHOP C M, AEA Technology, Harwell Laboratory, Didcot, Oxon. (GB);ROACH C M, AEA Technology, Culham Laboratory, Abingdon, Oxon. (GB)
Bibliographic Reference: Report: AEA FUS 162 EN (1991) 12 pp.
Availability: Available from AEA Techology Information Service, 465 Harwell, Didcot, Oxon. OX11 0RA (GB)
Record Number: 199210395 / Last updated on: 1994-12-02
Category: PUBLICATION
Original language: en
Available languages: en