DocumentCode
2230017
Title
Segmented Independent Component Analysis for Online Filtering Using Highly Segmented Detectors
Author
Filho, Eduardo F Simas ; de Seixas, Jose Manoel ; Caloba, Luiz Pereira
Author_Institution
Fed. Univ. of Rio de Janeiro, Rio de Janeiro
fYear
2007
fDate
20-24 Oct. 2007
Firstpage
659
Lastpage
664
Abstract
An online particle discrimination system is proposed for the ATLAS particle detector, which will be placed at one of the collision points of LHC, the next generation particle collider experiment. segmented independent component analysis (SICA) is applied over a highly segmented calorimeter (energy measurement system) in order to cope with the different levels of granularity present at each segment of the detector. A discrimination efficiency of 97% was achieved for a false alarm probability of 4.8%.
Keywords
independent component analysis; particle detectors; ATLAS particle detector; Online filtering; Online particle discrimination system; energy measurement system; highly segmented detectors; large hadron collider; segmented independent component analysis; Background noise; Detectors; Electrons; Energy measurement; Event detection; Filtering; Independent component analysis; Intelligent systems; Large Hadron Collider; Mesons;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems Design and Applications, 2007. ISDA 2007. Seventh International Conference on
Conference_Location
Rio de Janeiro
Print_ISBN
978-0-7695-2976-9
Type
conf
DOI
10.1109/ISDA.2007.107
Filename
4389683
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