• 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