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Proceedings Paper

Neural nets with varying topology for high-energy particle recognition: an outlook of computational dynamics
Author(s): Antonio Luigi Perrone; Roberto Messi; Enrico Pasqualucci; Gianfranco Basti
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Paper Abstract

With respect to Rosenblatt linear perceptron, a classical limitation theorem demonstrated by M. Minsky and S. Papert is discussed. This theorem, '$PSIOne-in-a-box', ultimately concern the intrinsic limitations of parallel calculations in pattern calculations in pattern recognition problems. We demonstrate a possible solution of this limitation problem by substituting the static definition of characteristic functions and of their domains in the 'geometrical' perceptron, with their dynamic definition. This dynamics consists in the mutual redefinition of the characteristic function and of its domain depending on the matching with the input. We show an application of this 'dynamic' perceptron scheme in particle tracks recognition in high energy physics. Actually, this algorithm is being used for real time automatic triggering of ADONE e+e- storage ring (Frascati, Rome) to evaluate the neutron time-like electromagnetic form factor in the context of 'Fenice' collaboration by Italian Institute of Nuclear Physics (INFN).

Paper Details

Date Published: 2 September 1993
PDF: 10 pages
Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); doi: 10.1117/12.152532
Show Author Affiliations
Antonio Luigi Perrone, INFN/Univ. of Rome Tor Vergata (Italy)
Roberto Messi, INFN/Univ. of Rome Tor Vergata (Italy)
Enrico Pasqualucci, INFN/Univ. of Rome Tor Vergata (Italy)
Gianfranco Basti, INFN/Univ. of Rome Tor Vergata and Pontifical Gregorian Univ. (Italy)

Published in SPIE Proceedings Vol. 1965:
Applications of Artificial Neural Networks IV
Steven K. Rogers, Editor(s)

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