DocumentCode :
821564
Title :
Fast triggering in high-energy physics experiments using hardware neural networks
Author :
Denby, Bruce ; Garda, Patrick ; Granado, Bertrand ; Kiesling, Christian ; Prévotet, Jean-Christophe ; Wassatsch, Andreas
Author_Institution :
Lab. des Instrum. et Syst. d´´Ile de France, Univ. Pierre et Marie Curie, Paris, France
Volume :
14
Issue :
5
fYear :
2003
Firstpage :
1010
Lastpage :
1027
Abstract :
High-energy physics experiments require high-speed triggering systems capable of performing complex pattern recognition at rates of Megahertz to Gigahertz. Neural networks implemented in hardware have been the solution of choice for certain experiments. The neural triggering problem is presented here via a detailed look at the H1 level 2 trigger at the HERA accelerator, Hamburg, Germany, followed by a section on the importance of hardware preprocessing for such systems, and finally some new architectural ideas for using field programmable gate arrays in very high-speed neural-network triggers at upcoming experiments.
Keywords :
field programmable gate arrays; high energy physics instrumentation computing; neural nets; nuclear electronics; particle accelerators; pattern recognition; storage rings; trigger circuits; FPGA; Germany; H1 level 2 trigger; HERA accelerator; Hamburg; architectural ideas; fast triggering; field programmable gate arrays; hardware neural networks; hardware preprocessing; high-energy physics experiments; high-speed triggering systems; pattern recognition; very high-speed neural-network triggers; Data mining; Detectors; Instruments; Intelligent networks; Neural network hardware; Neural networks; Particle accelerators; Pattern recognition; Physics; Timing;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/TNN.2003.816903
Filename :
1243706
Link To Document :
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