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Proceedings Paper

Artificial neural networks for data recovery in a Shashlik calorimeter
Author(s): M. Bonesini; M. Paganoni; F. Terranova; S. Gumenyuk; L. Petrovyk
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Paper Abstract

Artificial Neural Networks (ANN) are a powerful tool widely used in High Energy Physics to solve track finding and particle identification problems. A entirely new class of application is related to the problem of recovering the information lost during data taking or signal transmission. Good performance can be reached by ANN when the events are described by quite regular patterns. Such a method was used for the DELPHI luminosity monitor to recover calorimeter dead channels. A comparison with more traditional techniques is also given.

Paper Details

Date Published: 22 March 1996
PDF: 12 pages
Proc. SPIE 2760, Applications and Science of Artificial Neural Networks II, (22 March 1996); doi: 10.1117/12.235978
Show Author Affiliations
M. Bonesini, Univ. of Milan (Italy)
INFN (Italy)
M. Paganoni, Univ. of Milan (Italy)
INFN (Italy)
F. Terranova, Univ. of Milan (Italy)
INFN (Italy)
S. Gumenyuk, INFN (Italy)
IHEP (Russia)
L. Petrovyk, INFN (Italy)
IHEP (Russia)

Published in SPIE Proceedings Vol. 2760:
Applications and Science of Artificial Neural Networks II
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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