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Detection and clustering of light charged particles via system‐identification techniques
Author(s) -
Previdi F.,
Savaresi Sergio M.,
Guazzoni P.,
Zetta L.
Publication year - 2007
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.927
Subject(s) - detector , impulse response , impulse (physics) , cascade , particle identification , cluster analysis , parametric statistics , physics , system identification , computer science , algorithm , artificial intelligence , mathematics , optics , engineering , data modeling , mathematical analysis , statistics , quantum mechanics , database , chemical engineering
The problem considered in this work is the classification of the particles produced by the collision of a heavy ion beam on a target. Each particle is captured by a detector and results in a signal (which is the impulse response of a dynamic linear system), which is measured by a digital acquisition system. The assumption made herein is that the shape of the impulse‐response contains complete information on the particle, and the classification can be done by pulse‐shape, analysis. In this work, a complete procedure for the particle identification is proposed. The main idea is to use the cascade of a state‐space identification algorithm and a parametric non‐linear map using the model parameters as input regressors. The algorithm has been tested on a large set of impulse‐responses and provides a fully automatic accurate classification of the isotopes. This work focuses on isotopic identification of the most energetic light charged particles (LCP). All the experiments are made with the large detector array CHIMERA (Charge Heavy Ions Mass and Energy Resolving Array). Copyright © 2006 John Wiley & Sons, Ltd.