Open this publication in new window or tab >>2021 (English)In: World Congress on Neural Networks, Taylor & Francis, 2021, Vol. 2, p. II.631-II.640Chapter in book (Other academic)
Abstract [en]
An implementation of an analog neural network trained to identify signatures from the AC electrical power system on the Space Shuttle Orbiter is described. This demonstration project shows that a small stand alone system in the form of a VME-module can be designed, constructed and tested within days, provided a proper set of training vectors are available.
Place, publisher, year, edition, pages
Taylor & Francis, 2021
National Category
Physical Sciences
Identifiers
urn:nbn:se:kth:diva-316144 (URN)2-s2.0-84914888299 (Scopus ID)
Note
QC 20220824
Chapter in book: ISBN 978-131578407-6, 978-080581745-4
2022-08-242022-08-242022-08-24Bibliographically approved