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Bayesian inversion for electromyography using low-rank tensor formats

; ; ;

Umfang26 Seiten

Online
DOI: 10.48550/arXiv.2009.02772


Einrichtungen

  1. Lehr- und Forschungsgebiet Numerische Analysis (111620)
  2. Fachgruppe Mathematik (110000)
  3. Institut für Geometrie und Praktische Mathematik (111400)


Inhaltliche Beschreibung (Schlagwörter)
EMG (frei) ; Metropolis-Hastings algorithm (frei) ; hierarchical Tucker format (frei) ; inverse problem (frei) ; parameter-dependent problem (frei)

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Dokumenttyp
Preprint

Format
online

Sprache
English

Externe Identnummern
arXiv: arXiv:2009.02772

Interne Identnummern
RWTH-2020-12355
Datensatz-ID: 808864

Beteiligte Länder
Germany

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Related:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article  ;  ;  ;
Bayesian inversion for electromyography using low-rank tensor formats
Inverse problems 37(5), 055003 () [10.1088/1361-6420/abd85a]  GO BibTeX | EndNote: XML, Text | RIS

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 Record created 2020-12-16, last modified 2025-03-25
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