Anomaly detection for atomic clocks using unsupervised machine learning algorithms

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Veröffentlicht in:Metrologia Jg. 61; H. 5
Hauptverfasser: Chen, Edwin, Charbonneau, André, Gertsvolf, Marina, Wang, Yunli
Format: Journal Article
Sprache:Englisch
Veröffentlicht: IOP Publishing 01.10.2024
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ISSN:0026-1394, 1681-7575
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Author Chen, Edwin
Gertsvolf, Marina
Charbonneau, André
Wang, Yunli
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  organization: University of Toronto , Toronto, ON M5S 1A1, Canada
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  surname: Charbonneau
  fullname: Charbonneau, André
  organization: National Research Council Canada , Ottawa, ON K1A 0R6, Canada
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  givenname: Marina
  orcidid: 0000-0002-1188-2104
  surname: Gertsvolf
  fullname: Gertsvolf, Marina
  organization: National Research Council Canada , Ottawa, ON K1A 0R6, Canada
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  givenname: Yunli
  orcidid: 0000-0002-2320-954X
  surname: Wang
  fullname: Wang, Yunli
  organization: National Research Council Canada , Ottawa, ON K1A 0R6, Canada
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SubjectTerms anomaly detection
atomic clock
change point detection
frequency jumps
machine learning
phase jumps
Title Anomaly detection for atomic clocks using unsupervised machine learning algorithms
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