Recent results on structural pattern recognition for Fusion massive databases

J. Vega, G. Rattá, A. Murari, P. Castro, S. Dormido-Canto, R. Dormido, G. Farias, A. Pereira, A. Portas, E. De La Luna, I. Pastor, J. Sánchez, N. Duro, R. Castro, M. Santos, H. Vargas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

Physics studies in fusion devices require statistical analyses of a large number of discharges. Given the complexity of the plasma and the non-linear interactions between the relevant parameters, connecting a physical phenomenon with the signal patterns that it generates can be quite demanding. Up to now, data retrieval has been typically accomplished by means of signal name and shot number. The search of the temporal segment to analyze has been carried out in a manual way. Manual searches in databases must be replaced by intelligent techniques to look for data in an automated way. Structural pattern recognition techniques have proven to be very efficient methods to index and retrieve data in JET and TJ-II databases. Waveforms and images can be accessed through several structural pattern recognition applications.

Original languageEnglish
Title of host publication2007 IEEE International Symposium on Intelligent Signal Processing, WISP
DOIs
StatePublished - 2007
Externally publishedYes
Event2007 IEEE International Symposium on Intelligent Signal Processing, WISP - Alcala de Henares, Spain
Duration: 3 Oct 20075 Oct 2007

Publication series

Name2007 IEEE International Symposium on Intelligent Signal Processing, WISP

Conference

Conference2007 IEEE International Symposium on Intelligent Signal Processing, WISP
Country/TerritorySpain
CityAlcala de Henares
Period3/10/075/10/07

Keywords

  • Data mining
  • Image processing
  • Information retrieval
  • Structural pattern recognition

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