Title :
Drift chamber tracking with neural networks
Author :
Lindsey, Clark S. ; Denby, Bruce ; Haggerty, Herman
Author_Institution :
Fermi Nat. Accel. Lab., Batavia, IL, USA
Abstract :
Drift chamber tracking with a commercial analog VLSI neural network chip is considered. Voltages proportional to the drift times in a four-layer drift chamber were presented to the Intel ETANN (Electrically Trained Analog Neural Network) chip. The network was trained to provide the intercept and slope of straight tracks traversing the chamber. The outputs were recorded and later compared off-line to conventional track fits. Two types of network architectures were studied
Keywords :
neural nets; physics computing; position sensitive particle detectors; proportional counters; Electrically Trained Analog Neural Network; Intel ETANN; commercial analog VLSI neural network chip; drift chamber tracking; drift times; four-layer drift chamber; network architectures; neural networks; track fits; Detectors; Emulation; Laboratories; Large Hadron Collider; Mesons; Neural networks; Neurons; Very large scale integration; Voltage; Wire;
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference, 1992., Conference Record of the 1992 IEEE
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-0884-0
DOI :
10.1109/NSSMIC.1992.301444
