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Proceedings Paper

Neural networks for offline analysis in high-energy physics
Author(s): Alessandro D. de Angelis
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Paper Abstract

Feed-forward neural networks are nowadays a standard tool in the toolbox of high energy physicists. This talk summarizes the fields of application in offline analysis, and discusses some open problems.

Paper Details

Date Published: 6 April 1995
PDF: 10 pages
Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); doi: 10.1117/12.205103
Show Author Affiliations
Alessandro D. de Angelis, Univ. di Udine (Italy) and CERN (Switzerland)


Published in SPIE Proceedings Vol. 2492:
Applications and Science of Artificial Neural Networks
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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