Drift chamber tracking with neural networks

Author

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

Author_Institution

Fermi Nat. Accel. Lab., Batavia, IL, USA

fYear

1992

fDate

25-31 Oct 1992

Firstpage

835

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/NSSMIC.1992.301444

Filename

301444

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1932040