Machine Learning in Communications (MLC)5 ECTS (englische Bezeichnung: Machine Learning in Communications)
Modulverantwortliche/r: Laura Cottatellucci Lehrende:
Laura Cottatellucci
Start semester: |
WS 2020/2021 | Duration: |
1 semester | Cycle: |
jährlich (WS) |
Präsenzzeit: |
60 Std. | Eigenstudium: |
90 Std. | Language: |
Englisch |
Lectures:
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Machine Learning in Communications
(Vorlesung, 3 SWS, Laura Cottatellucci, Wed, Thu, 10:15 - 11:45, 01.021)
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Tutorial for Machine Learning in Communications
(Übung, 1 SWS, Nikita Shanin, Zeit n.V., Zoom-Meeting; For details see https://www.studon.fau.de/crs3252846.html)
Inhalt:
Recently, in many areas of wireless communications such as wireless sensor networks (WSNs), heterogeneous networks and complex ad hoc networks, distributed graph algorithms and machine learning on graphs are gaining relevance as fundamental tools in network analysis and information processing.
This motivates to deliver a general introduction to fundamentals of machine learning such as detection of clusters on graphs. The introduction is followed by the application of machine learning to the design of physical and data layer techniques in wireless communications and in the optimization of mobile networks.
Lernziele und Kompetenzen:
The students
know and explain the fundamentals of machine learning with special attention to machine learning over graphs.
apply these principles in the design and optimisation of wireless communications systems and mobile networks.
Studien-/Prüfungsleistungen:
Machine Learning in Communications (Prüfungsnummer: 668129)
(englischer Titel: Machine Learning in Communications)
- Prüfungsleistung, mündliche Prüfung, Dauer (in Minuten): 30, benotet, 5.0 ECTS
- Anteil an der Berechnung der Modulnote: 100.0 %
- Prüfungssprache: Englisch
- Erstablegung: WS 2020/2021, 1. Wdh.: SS 2021
1. Prüfer: | Laura Cottatellucci |
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