NEURAL NETWORKS IN EXPERIMENTAL HIGH-ENERGY PHYSICS

C. Bortolotto, A. de Angelis, N. de Groot and J. Seixas
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C. Bortolotto: Istituto di Fisica dell’Universita’ di Udine, Via Fagagna 208, I-33100 Udine, Italy
A. de Angelis: Istituto di Fisica dell’Universita’ di Udine, Via Fagagna 208, I-33100 Udine, Italy
N. de Groot: NIKHEF, Amsterdam NL-1009, The Netherlands
J. Seixas: CERN, Geneva CH-1211, Switzerland

International Journal of Modern Physics C (IJMPC), 1992, vol. 03, issue 04, 733-771

Abstract: During the last years, the possibility to use Artificial Neural Networks in experimental High Energy Physics has been widely studied. In particular, applications to pattern recognition and pattern classification problems have been investigated. The purpose of this article is to review the status of such investigations and the techniques established.

Keywords: Neural Networks; Classification Problems; Optimization Problems; Taxonomy; Nonlinear Separators (search for similar items in EconPapers)
Date: 1992
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DOI: 10.1142/S0129183192000452

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