Clustering based on the geodesic distance on Gaussian manifolds for the automatic classification of disruptions

by A. Murari, P. Boutot, J. Vega, M. Gelfusa, R. Moreno, G. Verdoolaege, P. C. de Vries, JET-EFDA Contributors
Reference:
Clustering based on the geodesic distance on Gaussian manifolds for the automatic classification of disruptions (A. Murari, P. Boutot, J. Vega, M. Gelfusa, R. Moreno, G. Verdoolaege, P. C. de Vries, JET-EFDA Contributors), In NUCLEAR FUSION, volume 53, 2013.
Bibtex Entry:
@article{ ISI:000315417000006,
Author = {Murari, A. and Boutot, P. and Vega, J. and Gelfusa, M. and Moreno, R.
   and Verdoolaege, G. and de Vries, P. C. and JET-EFDA Contributors},
Title = {{Clustering based on the geodesic distance on Gaussian manifolds for the
   automatic classification of disruptions}},
Journal = {{NUCLEAR FUSION}},
Year = {{2013}},
Volume = {{53}},
Number = {{3}},
Month = {{MAR}},
DOI = {{10.1088/0029-5515/53/3/033006}},
Article-Number = {{033006}},
ISSN = {{0029-5515}},
EISSN = {{1741-4326}},
ResearcherID-Numbers = {{Gelfusa, Michela/C-4979-2014
   Verdoolaege, Geert/I-4655-2012
   }},
ORCID-Numbers = {{Gelfusa, Michela/0000-0001-5158-7292
   Verdoolaege, Geert/0000-0002-2640-4527
   Vega, Jesus/0000-0002-1622-3984
   Moreno Salinas, Raul/0000-0001-6964-2333}},
Unique-ID = {{ISI:000315417000006}},
}