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Convex Optimization in Communications and Signal Processing (ConvOpt)5 ECTS (englische Bezeichnung: Convex Optimization in Communications and Signal Processing)
Modulverantwortliche/r: Wolfgang Gerstacker Lehrende:
Wolfgang Gerstacker
Startsemester: |
WS 2020/2021 | Dauer: |
1 Semester | Turnus: |
jährlich (WS) |
Präsenzzeit: |
60 Std. | Eigenstudium: |
90 Std. | Sprache: |
Englisch |
Lehrveranstaltungen:
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Convex Optimization in Communications and Signal Processing
(Vorlesung, 3 SWS, Wolfgang Gerstacker, Di, 12:15 - 13:45, Zoom-Meeting; Fr, 14:15 - 15:45, Zoom-Meeting; Details on StudOn: https://www.studon.fau.de/crs3252792.html)
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Tutorial for Convex Optimization in Communications and Signal Processing
(Übung, 1 SWS, Adela Vagollari, Zeit n.V., Zoom-Meeting; Details on StudOn: https://www.studon.fau.de/crs3252792.html)
Empfohlene Voraussetzungen:
Signals and Systems, Communications
Inhalt:
Convex optimization problems are a special class of mathematical problems which arise in a variety of practical applications. In this course we focus on the theory of convex optimization, corresponding algorithms, and applications in communications and signal processing (e.g. statistical estimation, allocation of resources in communications networks, and filter design). Special attention is paid to recognizing and formulating convex optimization problems and their efficient solution.
The course is based on the textbook "Convex Optimization" by Boyd and Vandenberghe and includes a tutorial in which many examples and exercises are discussed.
Lernziele und Kompetenzen:
Students
characterize convex sets and functions,
recognize, describe and classify convex optimization problems,
determine the solution of convex optimization problems via the dual function and the KKT conditions,
apply numerical algorithms in order to solve convex optimization problems,
apply methods of convex optimization to different problems in communications and signal processing
Literatur:
Boyd, Steven ; Vandenberghe, Lieven: Convex Optimization. Cambridge, UK : Cambridge University Press, 2004
Weitere Informationen:
Schlüsselwörter: ASC
Studien-/Prüfungsleistungen:
Convex Optimization in Communications and Signal Processing (Prüfungsnummer: 68501)
(englischer Titel: Convex Optimization in Communications and Signal Processing)
- Prüfungsleistung, Klausur, Dauer (in Minuten): 90, benotet, 5 ECTS
- Anteil an der Berechnung der Modulnote: 100.0 %
- Erstablegung: WS 2020/2021, 1. Wdh.: SS 2021
1. Prüfer: | Wolfgang Gerstacker |
- Termin: 01.04.2021, 08:00 Uhr, Ort: H 7 TechF
Termin: 11.10.2021, 08:00 Uhr, Ort: H 16
Termin: 14.04.2022, 11:00 Uhr, Ort: H 8 TechF
Termin: 10.10.2022
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