Determining 1D fast-ion velocity distribution functions from ion cyclotron emission data using deep neural networks.

Schmidt, B S; Salewski, M; Reman, B; Dendy, R O; Moseev, D; Ochoukov, R; Fasoli, A; Baquero-Ruiz, M; Järleblad, H

Schmidt, B S; Salewski, M; Reman, B; Dendy, R O; Moseev, D; Ochoukov, R; Fasoli, A; Baquero-Ruiz, M; Järleblad, H.

Afiliación

Schmidt BS; Department of Physics, Technical University of Denmark, Kgs. Lyngby, Denmark.
Salewski M; Department of Physics, Technical University of Denmark, Kgs. Lyngby, Denmark.
Reman B; Laboratoire Plasma et Conversion d'Energie, Université Toulouse, Toulouse, France.
Dendy RO; Centre for Fusion, Space and Astrophysics, University of Warwick, Coventry, United Kingdom.
Moseev D; Max-Planck-Institut für Plasmaphysik, Greifswald, Garching, Germany.
Ochoukov R; Max-Planck-Institut für Plasmaphysik, Greifswald, Garching, Germany.
Fasoli A; École Polytechnique Fédérale de Lausanne, Swiss Plasma Center, Lausanne, Switzerland.
Baquero-Ruiz M; École Polytechnique Fédérale de Lausanne, Swiss Plasma Center, Lausanne, Switzerland.
Järleblad H; Department of Physics, Technical University of Denmark, Kgs. Lyngby, Denmark.

Rev Sci Instrum ; 92(5): 053528, 2021 May 01.

Article en En | MEDLINE | ID: mdl-34243325

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: Rev Sci Instrum Año: 2021 Tipo del documento: Article País de afiliación: Dinamarca Pais de publicación: Estados Unidos

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