Neural network classification of gamma-ray bursts

Balastegui, A. and Ruiz-Lapuente, P. and Canal, R. (2005) Neural network classification of gamma-ray bursts. Il nuovo cimento C, 28 (4\5). pp. 801-804. ISSN 1826-9885

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From a cluster analysis it appeared that a three-class classification of GRBs could be preferable to just the classic separation of short/hard and long/soft GRBs (Balastegui A., Ruiz-Lapuente P. and Canal R. MNRAS 328 (2001) 283). A new classification of GRBs obtained via a neural network is presented, with a short/hard class, an intermediate-duration/soft class, and a long/soft class, the latter being a brighter and more inhomogenous class than the intermediate duration one. A possible physical meaning of this new classification is also outlined.

Item Type: Article
Additional Information: Paper presented at the “4th Workshop on Gamma-Ray Burst in the Afterglow Era”, Rome, October 18-22, 2004.
Uncontrolled Keywords: γ-ray sources; γ-ray bursts ; Multivariate Analysis ; Neural networks, fuzzy logic, artificial intelligence in physics
Subjects: 500 Scienze naturali e Matematica > 520 Astronomia e scienze connesse
Depositing User: Marina Spanti
Date Deposited: 17 Mar 2020 17:56
Last Modified: 17 Mar 2020 17:56

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