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  Statistische Signalverarbeitung (STASIP)

Lecturer
Prof. Dr.-Ing. Walter Kellermann

Details
Vorlesung
3 cred.h, ECTS studies, ECTS credits: 5
nur Fachstudium, Sprache Englisch
Time and place: Tue 12:15 - 13:45, 0.154-115; Wed 10:15 - 11:45, 0.154-115

Fields of study
WPF MT-MA-BDV 1-2
WF WING-BA-IKS 6
WF WING-MA 1-4
WPF SIM-MA 1-4
WF IuK-BA 6
WPF IuK-MA-KN-EEI 1-3
WPF IuK-MA-ÜTMK-EEI 1-3
WPF IuK-MA-MMS-EEI 1-3
WPF IuK-MA-ES-EEI 1-4
WF CE-MA-TA-IT ab 1
WPF EEI-BA-INT 5-6
WPF EEI-MA-INT 1-4
PF CME-MA 2
WF CE-BA-TW 6
WPF SIM-DH 6-8
WPF WING-DH 6-8
WPF MT-MA-MEL 2-3

Contents
Die Vorlesung behandelt grundlegende Verfahren der statistischen Signalverarbeitung und deren Anwendung auf reale Probleme.
Die Themengebiete im Einzelnen sind:
• Zeitdiskrete Zufallsprozesse im Zeit- und Frequenzbereich
• Schätztheorie
• Nichtparametrische und parametrische Signalmodelle (Pol-/Nullstellenmodelle, ARMA-Modelle)
• Lineare Optimalfilter (z.B. zur Prädiktion, Entzerrung), Eigenfilter, Kalman-Filter
• Algorithmen zur Identifikation linearer Optimalfilter (adaptive Filter)

Recommended literature
• A. Papoulis, S. Pillai: Probability, Random Variables and Stochastic Processes; McGraw-Hill, 2002 (englisch)
• D. Manolakis, V. Ingle, S. Kogon: Statistical and Adaptive Signal Processing; McGraw-Hill, 2005 (englisch)

ECTS information:
Credits: 5

Contents
The course concentrates on fundamental methods of statistical signal processing and their applications. The main topics are:
• Discrete-time stochastic processes in the time and frequency domain
• Estimation theory
• Non-parametric and parametric signal models (pole/zero models, ARMA models)
• Optimum linear filters (e.g. for prediction), eigenfilters, Kalman filters
• Algorithms for optimum linear filter identification (adaptive filters)

Literature
• A. Papoulis, S. Pillai: Probability, Random Variables and Stochastic Processes; McGraw-Hill, 2002 (english)
• D. Manolakis, V. Ingle, S. Kogon: Statistical and Adaptive Signal Processing; McGraw-Hill, 2005 (english)

Additional information
Expected participants: 44

Assigned lectures
UE: Übung zur statistischen Signalverarbeitung
Lecturer: M.Sc. Roland Maas
Time and place: Mon 18:15 - 19:45, H15

Verwendung in folgenden UnivIS-Modulen
Startsemester SS 2014:
Statistische Signalverarbeitung (STASIP)

Department: Chair of Multimedia Communications and Signal Processing (Prof. Dr. Kaup)
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