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Self-organizing networks for extracting jet features

Lönnblad, Leif LU orcid ; Peterson, Carsten LU ; Pi, Hong and Rögnvaldsson, Thorsteinn (1991) In Computer Physics Communications 67(2). p.193-209
Abstract

Self-organizing neural networks are briefly reviewed and compared with supervised learning algorithms like back-propagation. The power of self-organization networks is in their capability of displaying typical features in a transparent manner. This is successfully demonstrated with two applications from hadronic jet physics; hadronization model discrimination and separation of b, c and light quarks.

Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Computer Physics Communications
volume
67
issue
2
pages
17 pages
publisher
Elsevier
external identifiers
  • scopus:0026391884
ISSN
0010-4655
DOI
10.1016/0010-4655(91)90016-E
language
English
LU publication?
yes
id
99b6f3db-cf43-465d-b248-ce0db339d4d6
date added to LUP
2019-05-15 08:02:56
date last changed
2024-01-01 04:42:30
@article{99b6f3db-cf43-465d-b248-ce0db339d4d6,
  abstract     = {{<p>Self-organizing neural networks are briefly reviewed and compared with supervised learning algorithms like back-propagation. The power of self-organization networks is in their capability of displaying typical features in a transparent manner. This is successfully demonstrated with two applications from hadronic jet physics; hadronization model discrimination and separation of b, c and light quarks.</p>}},
  author       = {{Lönnblad, Leif and Peterson, Carsten and Pi, Hong and Rögnvaldsson, Thorsteinn}},
  issn         = {{0010-4655}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{193--209}},
  publisher    = {{Elsevier}},
  series       = {{Computer Physics Communications}},
  title        = {{Self-organizing networks for extracting jet features}},
  url          = {{http://dx.doi.org/10.1016/0010-4655(91)90016-E}},
  doi          = {{10.1016/0010-4655(91)90016-E}},
  volume       = {{67}},
  year         = {{1991}},
}