Study and optimization of a neural network with fuzzy logic preprocessing for particle identification on a cosmic ray detector

Marco Casolino; M. Candusso; M. P. DePascale; Aldo Morselli; Piergiorgio Picozza; M. Ricci

doi:10.1117/12.211797

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13 June 1995 Study and optimization of a neural network with fuzzy logic preprocessing for particle identification on a cosmic ray detector

Marco Casolino, M. Candusso, M. P. DePascale, Aldo Morselli, Piergiorgio Picozza, M. Ricci

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Proceedings Volume 2493, Applications of Fuzzy Logic Technology II; (1995) https://doi.org/10.1117/12.211797
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

A fuzzy logic preprocessing is used in connection with a back propagation neural network in particle recognition. As application on 4 GeV CERN experimental and Monte Carlo data of e^- and (pi) (superscript -, taken with the prototype of the silicon Tungsten calorimeter of the Wizard collaboration, is shown. This preprocessing consists in giving as input to the net the membership value, for a given discriminating parameter value, to belong to a given particle class. In this way the input layer receives a normalized input. The net can then exploit the correlations between different parameters, resulting in an increased convergence speed and recognition capability of the net. Other advantages of this approach are its noise robustness and the simple generalization of other particle classes or energies.

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Marco Casolino, M. Candusso, M. P. DePascale, Aldo Morselli, Piergiorgio Picozza, and M. Ricci "Study and optimization of a neural network with fuzzy logic preprocessing for particle identification on a cosmic ray detector", Proc. SPIE 2493, Applications of Fuzzy Logic Technology II, (13 June 1995); https://doi.org/10.1117/12.211797

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