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Lindblad, Thomas
Publications (2 of 2) Show all publications
Shelton, R. O., Hultberg, S. & Lindblad, T. (2021). A neural network VME-module for recognizing AC current demand signatures in space shuttle telemetry data. In: World Congress on Neural Networks: (pp. II.631-II.640). Taylor & Francis, 2
Open this publication in new window or tab >>A neural network VME-module for recognizing AC current demand signatures in space shuttle telemetry data
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

Available from: 2022-08-24 Created: 2022-08-24 Last updated: 2022-08-24Bibliographically approved
Eide, Ä., Lindblad, T. & Paillet, G. (2011). Radial-Basis-Function Networks. In: The Industrial Electronics Handbook - Five Volume Set: (pp. 7-1-7-12). CRC Press
Open this publication in new window or tab >>Radial-Basis-Function Networks
2011 (English)In: The Industrial Electronics Handbook - Five Volume Set, CRC Press , 2011, p. 7-1-7-12Chapter in book (Other academic)
Place, publisher, year, edition, pages
CRC Press, 2011
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-324585 (URN)2-s2.0-85131467723 (Scopus ID)
Note

Part of book: ISBN 978-143980290-8, QC 20230307

Available from: 2023-03-07 Created: 2023-03-07 Last updated: 2023-03-07Bibliographically approved
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