• DocumentCode
    1009058
  • Title

    Drift chamber tracking with neural networks

  • Author

    Lindsey, Clark S. ; Denby, Bruce ; Haggerty, Herman

  • Author_Institution
    Fermi Nat. Accel. Lab., Batavia, IL, USA
  • Volume
    40
  • Issue
    4
  • fYear
    1993
  • fDate
    8/1/1993 12:00:00 AM
  • Firstpage
    607
  • Lastpage
    614
  • Abstract
    Drift chamber tracking with a commercial analog VLSI neural network chip is discussed. Voltages proportional to the drift time in a four-layer drift chamber are presented to the Intel Electrically Trained Analog Neural Network chip. The network is trained to provide the intercept and slope of straight tracks traversing the chamber. The outputs are recorded and compared offline to conventional track fits. Two types of network architectures are studied. Application of neural network tracking to high energy physics detector triggers is discussed
  • Keywords
    computerised instrumentation; neural chips; neural nets; physics computing; position sensitive particle detectors; proportional counters; Intel Electrically Trained Analog Neural Network chip; commercial analog VLSI neural network chip; four-layer drift chamber; high energy physics detector triggers; network architectures; Detectors; Feedforward neural networks; Feedforward systems; Mesons; Neural network hardware; Neural networks; Neurons; Pattern recognition; Very large scale integration; Voltage;
  • fLanguage
    English
  • Journal_Title
    Nuclear Science, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9499
  • Type

    jour

  • DOI
    10.1109/23.256626
  • Filename
    256626