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Prof. Heidi Krömker


Telefon +49 3677 69-2890

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Ihre Position


ADSP / Digital Signal Procesing 2

Professors responsible for teaching: Prof. Dr.-Ing Gerald Schuller



  • Sampling, principles:
    • AD/DA conversion (Mic, Speaker)
    • Sampling rates
    • Aliasing
    • Sampling rate conversion
  • Z transform: theory and properties
  • Filtering:
    • FIR
    • IIR
    • design methods
    • optimization
  • Complex signals and filters, analytical signal, hilbert transform 
  • Complex filter banks
  • Wiener filter
  • Prediction 
    • Wiener-Hopf-Equations
    • LMS
  • Filter banks, wavelets, QMF, lifting, intMDCT



Installation of Python:

For the installation of Python in Windows, Mac or Ubuntu Linux you can find a description in It is easiest for Ubuntu Linux (just one click in the Ubuntu Software Center).


For Windows:

Go to Download PythonXXX.exe and execute it for installation. For our course you need extra Python libraries (e.g. numpy, scipy, matplotlib, etc.). In order to install extra libraries you can use pip installer program. You can find more full description of pip usage here

One more way to install full Python with all basic libraries in Windows is to install Python(x,y). Python(x,y) is a free scientific and engineering development software for numerical computations, data analysis and data visualization based on Python programming language, Qt graphical user interfaces and Spyder interactive scientific development environment. Full description of Python(x,y) and installation file can be found here


For Ubuntu:

Ubuntu comes with pre-installed Python. However, extra libraries have to be installed separately. It can be done using pip installer. 

To install something in Ubuntu command sudo apt-get install pkg_name can be used. 


- to install pip installer:

sudo apt-get install python-pip

 - to install numpy, scipy and matplotlib using pip:

sudo pip install numpy scipy matplotlib

- to install numpy, scipy and matplotlib using apt-get:

sudo apt-get install python-numpy python-scipy python-matplotlib


The Python Tutorial can be found here or use google and Stackoverflow.


[1] Alan V. Oppenheim, Ronald W. Schafer, with John R. Buck:    “Dicrete-Time Signal Processing” ; Pearson 2010, 3rd Edition, ISBN:0-13-206709-9;  (UB Ilmenau ELT ZN 6040 O62-A(3))

[2] John G. Proakis; Maoud Salehi:    “Digital Communications”; McGraw-Hill 2008, ISBN 978-0-07-295716-7;  (UB Ilmenau 79 ELT ZN6040 P962)

[3] N.J. Fliege : „Multirate Digital Signal Processing“; John Wiley and Sons , Ltd. 1996 and 2005

[4] Khalid Sayood: " Introduction to Data Compression"; Morgan Kaufman 2005 (UB Ilmenau : INF ST 265 S275(4))

[5] Monson H. Hayes: " Statistical Digital Signal Processing and Modelling"; Wiley, 1996 ISBN:0471594318

[6] Alan V. Oppenheim, Alan S. Willsky with S. Hamid Nawab:    “Signals and Systems” ; Prentice-Hall 1996, 2nd Edition, ISBN:0-13-814757-4

Other references:

[7] W. Zühlke:     Script of Lectures “Digitale Signalverarbeitung und Automatische Spracherkennung” in the years up to 2004

[8] P. S. R. Diniz, E.A.B. da Silva, S. L. Netto: Digital Signal Processing - System Analysis and Design 2. ed.  Cambridge Univ. Press 2010; ISBN 978-0-521-88775-5

[9] I.C. Ifeachor, B.W. Jervis: Digital Signal Processing A Practical Approach; Pearson Education Ldt 2002, 2. ed.; ISBN 0-201-59619-9


There are homework assignments every second week and quizzes every week. They account for 30% of the final grade. The exam accounts for the other 70%.

Please sign in at moodle (Fakultät EI --> Institut für Medientechnik --> FG Angewandte Mediensysteme -->  AVS / ADSP / DSP II) for further information and material.

You may form small groups (2-3 people) to solve the homework and deliver a single solution for the whole group. Please present your homework in a digital form (prefered laptop with octave or matlab running. Otherwise, code on a flash storage device).

The bonus points earned by solving the homework assignments and passing the quizzes will only be added after passing the exam. When a student fails the exam the points stay valid until the lecture is held again and there are new homework assignments (in the following winter semester).


Organization WS 2014/15:

Seminars start after the first lecture.

Quizzes will start after the second lecture.

Instructor: Oleg Golokolenko







Seminar and Lecture slides for WS 2016/2017:

The new slides will be available on moodle after each lecture. You need to log in with your university account



  • Lecture: 1 Organisation,  A/D conversion, Quantization [pdf]
  • Lecture: 2 Quantization, SNR [pdf]
  • Lecture: 3 SNR, non-uniform Quantisation [pdf]
  • Lecture: 4 Lloyd-Max Quantizer, LBG [pdf]
  • Lecture: 5 Vector Quantizer, LBG [pdf]
  • Lecture: 6 Sampling, z-Transform [pdf]
  • Lecture: 7 z-Transform, Filters [pdf]
  • Lecture: 8 Noble Identities, Filters [pdf]
  • Lecture: 9 Allpass Filters [pdf]
  • Lecture: 10 Frequency Warping, Example [pdf]
  • Lecture: 11 Complex Signals and Filters, Hilbert Transform [pdf]
  • Lecture: 12 Wiener and Matched Filter, Prediction [pdf]
  • Lecture: 13 Matched Filters [pdf]
  • Lecture: 14 Prediction [pdf]
  • Lecture: 15 Summary using Examples [pdf]



  • Lectures WS 2015/16 [zip]


Additional Information:

  • Python programs for the ADSP, together with python notebook files: Examples




Tuesday, 09:00-10:30am (Kirchhoff-Hörsaal 1)

Seminars (choose one):

  • Wednesday (even weeks), 13:00-14:30pm (HU 210)
  • Thursday (odd weeks) 09:00-10:30am (K 2002A)

To sign in for one of the seminars, follow the link



Prof. Schuller, Mondays at 14-15pm

O. Golokolenko, date and time are arranged per e-mail

Office: K3013



Calculators (also programmable ones) are allowed. No other material is allowed.