Selection of hadronic W-decays in DELPHI with feed forward neural networks - An update

Since 1998 feed forward neural networks have been successfully applied to select candidates of hadronic W-decays measured at different center of mass-energies by the DELPHI collaboration at the Large Electron Positron collider at CERN. To prepare the final publication, the neural network was adapted...

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Detalles Bibliográficos
Autores principales: Becks, K H, Drees, J, Müller, U, Wahlen, H
Lenguaje:eng
Publicado: 2003
Materias:
Detectors and Experimental Techniques
Acceso en línea:https://dx.doi.org/10.1016/S0168-9002(03)00476-5
http://cds.cern.ch/record/624972
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author Becks, K H
Drees, J
Müller, U
Wahlen, H
author_facet Becks, K H
Drees, J
Müller, U
Wahlen, H
author_sort Becks, K H
collection CERN
description Since 1998 feed forward neural networks have been successfully applied to select candidates of hadronic W-decays measured at different center of mass-energies by the DELPHI collaboration at the Large Electron Positron collider at CERN. To prepare the final publication, the neural network was adapted to all center of mass- energies. Detailed studies were performed concerning the level of preselection, the choice of network parameters and especially of the network architecture. The number of hidden nodes was optimized by testing different pruning methods. All studies and results will be discussed.
id cern-624972
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2003
record_format invenio
spelling cern-6249722019-09-30T06:29:59Zdoi:10.1016/S0168-9002(03)00476-5http://cds.cern.ch/record/624972engBecks, K HDrees, JMüller, UWahlen, HSelection of hadronic W-decays in DELPHI with feed forward neural networks - An updateDetectors and Experimental TechniquesSince 1998 feed forward neural networks have been successfully applied to select candidates of hadronic W-decays measured at different center of mass-energies by the DELPHI collaboration at the Large Electron Positron collider at CERN. To prepare the final publication, the neural network was adapted to all center of mass- energies. Detailed studies were performed concerning the level of preselection, the choice of network parameters and especially of the network architecture. The number of hidden nodes was optimized by testing different pruning methods. All studies and results will be discussed.oai:cds.cern.ch:6249722003
spellingShingle Detectors and Experimental Techniques
Becks, K H
Drees, J
Müller, U
Wahlen, H
Selection of hadronic W-decays in DELPHI with feed forward neural networks - An update
title Selection of hadronic W-decays in DELPHI with feed forward neural networks - An update
title_full Selection of hadronic W-decays in DELPHI with feed forward neural networks - An update
title_fullStr Selection of hadronic W-decays in DELPHI with feed forward neural networks - An update
title_full_unstemmed Selection of hadronic W-decays in DELPHI with feed forward neural networks - An update
title_short Selection of hadronic W-decays in DELPHI with feed forward neural networks - An update
title_sort selection of hadronic w-decays in delphi with feed forward neural networks - an update
topic Detectors and Experimental Techniques
url https://dx.doi.org/10.1016/S0168-9002(03)00476-5
http://cds.cern.ch/record/624972
work_keys_str_mv AT beckskh selectionofhadronicwdecaysindelphiwithfeedforwardneuralnetworksanupdate
AT dreesj selectionofhadronicwdecaysindelphiwithfeedforwardneuralnetworksanupdate
AT mulleru selectionofhadronicwdecaysindelphiwithfeedforwardneuralnetworksanupdate
AT wahlenh selectionofhadronicwdecaysindelphiwithfeedforwardneuralnetworksanupdate

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