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Proceedings Paper

Neural nets with varying topology for high-energy particle recognition: theory and applications
Author(s): Antonio Luigi Perrone; Gianfranco Basti; Roberto Messi; Luciano Paoluzi; Piergiorgio Picozza
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Paper Abstract

In this paper we start from a critical analysis of the fundamental problems of the parallel calculus in linear structures and of their extension to the partial solutions obtained with non- linear architectures. Then, we briefly present a new dynamic architecture able to solve the limitations of the previous architectures through an automatic redefinition of the topology. This architecture is applied to real time recognition of particle tracks in high energy accelerators and in astrophysics experiments.

Paper Details

Date Published: 6 April 1995
PDF: 9 pages
Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); doi: 10.1117/12.205106
Show Author Affiliations
Antonio Luigi Perrone, Univ. di Roma Tor Vergata (Italy)
Gianfranco Basti, Univ. di Roma Tor Vergata (Italy)
Roberto Messi, Univ. di Roma Tor Vergata (Italy)
Luciano Paoluzi, Univ. di Roma Tor Vergata (Italy)
Piergiorgio Picozza, Univ. di Roma Tor Vergata (Italy)

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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