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Random Matrices in Communications and Signal Processing (RM-CSP)
- Dozent/in
- Prof. Dr.-Ing. Ralf Müller
- Angaben
- Vorlesung
2 SWS, ECTS-Studium, ECTS-Credits: 5, Sprache Englisch
Zeit und Ort: Mi 8:15 - 9:45, 01.021; Fr 10:15 - 11:45, 01.021
- Studienfächer / Studienrichtungen
- WF ASC-MA ab 1 (ECTS-Credits: 5)
WF CME-MA ab 2 (ECTS-Credits: 5)
WF EEI-MA-INT ab 2 (ECTS-Credits: 5)
WF ICT-MA ab 2 (ECTS-Credits: 5)
WF CE-MA-TA-IT ab 2 (ECTS-Credits: 5)
- Voraussetzungen / Organisatorisches
- Recommended: Good skills in linear algebra, probability theory and complex analysis
- Inhalt
- Dual antenna arrays, compressive sensing, Wishart distribution, factor iid model, Kronecker model, convergence of random variables, semi-circle law, quarter circle law, full circle law, Haar distribution, Marchenko-Pastur distribution, Stieltjes transform, Girko’s law, unitary invariance, freeness, free convolution, R-transform, free central limit theorem, free Poisson limit theorem, subordination, S-transform, R-diagonal random matrices, R-diagonal free convolution, Haagerup-Larsen law, operator-valued freeness, linearization of noncommutative polynomials, free Fourier transform, self-averaging properties, microscopic vs. macroscopic random variables, quenched random variable, a statistical physics point of view of digital systems, spin glasses, frozen disorder, replica method, replica continuity, replica symmetry, replica symmetry breaking, approximate message passing, classification of np-complete problems
- Empfohlene Literatur
- Mingo, J., Speicher, R.: Free Probability and Random Matrices, Springer, 2017
Couillet, R., Debbah, M.: Random Matrix Methods for Wireless Communications, Cambridge Univ. Press, Cambridge, 2011.
Mezard, M., Montanari, A.: Information, Physics, and Computation, Oxford Graduate Texts, 2009.
- ECTS-Informationen:
- Credits: 5
- Zusätzliche Informationen
- Erwartete Teilnehmerzahl: 20
www: https://www.studon.fau.de/crs3253173.html Für diese Lehrveranstaltung ist eine Anmeldung erforderlich. Die Anmeldung erfolgt über: StudOn
- Zugeordnete Lehrveranstaltungen
- UE: Tutorial for Random Matrices in Communications and Signal Processing
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Dozent/in: Mostafa Mohammadkarimi, Ph.D.
Zeit und Ort: n.V. www: https://www.studon.fau.de/crs3253173.html
- Verwendung in folgenden UnivIS-Modulen
- Startsemester WS 2020/2021:
- Random Matrices in Communications and Signal Processing (RM-CSP)
- Institution: Institute for Digital Communications (IDC) (Prof. Dr. Schober)
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