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Evaluation of 5G and Fixed-Satellite Service Earth Station (FSS-ES) Downlink Interference Based on Artificial Neural Network Learning Models (ANN-LMS).
Al-Jumaily, Abdulmajeed; Sali, Aduwati; Jiménez, Víctor P Gil; Lagunas, Eva; Natrah, Fatin Mohd Ikhsan; Fontán, Fernando Pérez; Hussein, Yaseein Soubhi; Singh, Mandeep Jit; Samat, Fazdliana; Aljumaily, Harith; Al-Jumeily, Dhiya.
Afiliação
  • Al-Jumaily A; Wireless and Photonic Networks Research Centre of Excellence (WiPNET), Department of Computer and Communication Systems Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia.
  • Sali A; Department of Signal Theory and Communications, Universidad Carlos III de Madrid, 28911 Madrid, Spain.
  • Jiménez VPG; Wireless and Photonic Networks Research Centre of Excellence (WiPNET), Department of Computer and Communication Systems Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia.
  • Lagunas E; Department of Signal Theory and Communications, Universidad Carlos III de Madrid, 28911 Madrid, Spain.
  • Natrah FMI; Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, L-1855 Luxembourg, Luxembourg.
  • Fontán FP; Faculty of Agriculture, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia.
  • Hussein YS; Department of Signal Theory and Communications, Universidad de Vigo, 36310 Vigo, Spain.
  • Singh MJ; Department of Information Systems and Computer Science, Ahmed Bin Mohammed Military College (ABMMC), Doha P.O. Box 22988, Qatar.
  • Samat F; Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.
  • Aljumaily H; Pusat Sains Angkasa Institut Perubahan Iklim, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.
  • Al-Jumeily D; Department of Computer Science and Engineering, Universidad Carlos III de Madrid, 28912 Madrid, Spain.
Sensors (Basel) ; 23(13)2023 Jul 05.
Article em En | MEDLINE | ID: mdl-37448024
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Aprendizagem Tipo de estudo: Evaluation_studies / Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article
Texto completo
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XML
PubMed Links
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Aprendizagem Tipo de estudo: Evaluation_studies / Prognostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article