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
Link To Document :
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