Digital Signal Processing (advanced)

Lecturer: A. Dekorsy, C. Bockelmann
Tutor: L. Zhu
Lecture: Monday 10:00 - 13:00
Exercise: Monday 10:00 - 13:00
VAK: 01-15-03-ADSP-V

Digital Signal Processing in general:
Kammeyer, Kroschel, "Digitale Signalverarbeitung", Springer Vieweg (in German)
Proakis, Manolakis, "Digital Signal Processing", Prentice Hall (in English)
Oppenheim, Schafer, "Discrete-Time Signal Processing", Prentice Hall (in English)

For the section on Linear Estimation:
Sayed, "Adaptive Filters", Wiley
Sayed, "Fundamentals of Adaptive Filtering", Wiley
Kailath, Sayed, Hassibi, "Linear Estimation", Prentice Hall
Haykin, "Adaptive Filter Theory", Prentice Hall
van Trees, "Detection, Estimation and Modulation Theory", Wiley

For the section on Compressed Sensing:
Eldar, Kutyniok, "Compressed Sensing: Theory and Applications", Cambridge University Press
Foucart, Rauhut, "A Mathematical Introduction to Compressive Sensing", Birkhäuser
Kammeyer, Dekorsy, "Nachrichtenübertragung", Springer Vieweg (in German)

Mailing List:

DSP Maillist

This lecture is now managed in Stud.IP Logo (GIF). All details will be found in Stud.IP.

This course follows the course Digital Signal Processing and covers advanced topics in digital signal processing as the discrete Fourier transform (DFT), its applications, linear estimation and spectrum estimation. 

Recommended background: digital signal processing, signal and system theory

The exam will be oral and around 15-20 minutes. There will be no Matlab exercise for the exam on DSP Advanced.

Last change on 21.01.2022 by S. Wang
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