DocumentCode
1157428
Title
Real-time applications of neural nets
Author
Spencer, J.E.
Author_Institution
Stanford Univ., CA, USA
Volume
36
Issue
5
fYear
1989
fDate
10/1/1989 12:00:00 AM
Firstpage
1485
Lastpage
1489
Abstract
The formidable real-time control problem posed by producing, accelerating, and colliding very-high-power, low-emittance beams for long periods of time is addressed. It is shown how neural nets suggest ways to circumvent the limitations encountered by such large, complex systems. It is argued that they are logically equivalent to multiloop feedback/forward control of faulty systems and mesh nicely with characteristics desired for real-time systems. Examples are given, and the potential of the approach is discussed
Keywords
beam handling techniques; data acquisition; neural nets; nuclear electronics; physics computing; real-time systems; low-emittance beams; multiloop feedback/forward control; neural nets; real-time control problem; Acceleration; Artificial intelligence; Computer aided instruction; Control systems; Electrons; Integrated circuit reliability; Neural networks; Optical computing; Real time systems; Slag;
fLanguage
English
Journal_Title
Nuclear Science, IEEE Transactions on
Publisher
ieee
ISSN
0018-9499
Type
jour
DOI
10.1109/23.41088
Filename
41088
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