Symbolbild
Ein Symbolbild, das die AG repräsentiert
Login |
 
 

Digital Signal Processing

Tutor

Dr. Maciej Gratkowski

Schedule

Lecture Mo. 10:00 - 11:30 Z 613
  Thu. 11:45 - 13:15 Z 613
Lab Session

Tu.

11:45 - 13:15

Z 613
       
Exam, Term1 Mo.

17.02.2014, 10:00

A 702
Exam, Term2 Tu.

22.04.2014, 10:00

Z 613

Target Audience

The course belongs to the topic areas Foundations of Computer Science and Applied Computer Science and is for students of the following degree programs

  • Information Engineering und Computer Science, both for Bachelor Advanced Studies and Master
  • Mathematics
  • Physics


Preknowledge in analysis and stochastics is required.

Prerequisites

None, if taken as a master course. If taken as an advanced course in the bachelor program:

  • basic math courses offered in our bachelor programs
  • algorithms and data structures
  • introduction to computer science including programming

Course works and credits

The course ends with a final exam (either oral or written, depending on the number of course participants). 50 % of the marks for homework assignments is required for the admission to this final exam. If you earn at least 70 % of the marks for homework assignments, the final grade is 1/3 of a grade better than the exam grade. If you earn at least 90 %, the bonus is 2/3 of a grade.

Lab Sheets

  Date Due
Lab Sheet 1 28.10.2013 No Submission
Lab Sheet 2 28.10.2013 04.11.2013 9 am
Lab Sheet 3 04.11.2013 11.11.2013 9 am
Lab Sheet 4 11.11.2013 18.11.2013 9 am
Lab Sheet 5 18.11.2013 25.11.2013 9 am

Lab Sheet 6

handwriting.png

25.11.2013 02.12.2013 9 am

Lab Sheet 7

02.12.2013 09.12.2013 9 am

Lab Sheet 8

09.12.2013 16.12.2013 9 am

Lab Sheet 9

16.12.2013 23.12.2013

Bonus Lab Sheet:

Christmas Exercise

speech.mat

20.12.2013

Submission

not compulsory!

07.01.2014 9 am

Lab Sheet 10

07.01.2014

14.01.2014 9 am

Lab Sheet 11

13.01.2014 20.01.2014 9 am

Lab Sheet 12

20.01.2014 27.01.2014 9 am

Lab Sheet 13

27.01.2014 03.02.2014 9 am

Lab Sheet 14

03.02.2014 10.02.2014 9 am

Please submit your solutions as Latex-generated PDFs (first 4 Lab Sheets can be handwritten and scanned) per e-mail to maciej.gratkowski@uni-konstanz.de.

Matlab Access

Matlab will be used extensively during the course and is installed locally on every computer in Z 613. For completing assignments you can use the computer pool in V 304. Remote access from home might be slow. Matlab is installed on a server:

  • for Linux: /net/lin_local/matlab/bin/matlab
  • for Windows: \\titan01\lin_local\matlab\win\bin\matlab.bat

Literature / Weblinks

  • Alan Oppenheim, Ronald Schafer, John Buck, Discrete-time Signal Processing, Prentice-Hall, 2010.
  • Alan Oppenheim, Ronald Schafer, John Buck, Zeitdiskrete Signalverarbeitung, 2. Auflage, Pearson Studium, 2004.
  • Vinay Ingke, John Proakis, Digital Signal Processing using MATLAB, Third Edition, Cengage Learning, 2012.

Reading on Complex Calculus

An Introduction to Complex Analysis for Engineers

DSP Book References

Digital Signal Processing Using MATLAB

This supplement to any standard DSP text is one of the first books to successfully integrate the use of MATLAB in the study of DSP concepts. In this book, MATLAB is used as a computing tool to explore traditional DSP topics, and solve problems to gain insight. This greatly expands the range and complexity of problems that students can effectively study in the course. Since DSP applications are primarily algorithms implemented on a DSP processor or software, a fair amount of programming is required. Using interactive software such as MATLAB makes it possible to place more emphasis on learning new and difficult concepts than on programming algorithms. Interesting practical examples are discussed and useful problems are explored. This updated second edition includes new homework problems and revises the scripts in the book, available functions, and m-files to MATLAB V7.

This hands on, multi-media package provides a motivating introduction to fundamental concepts, specifically discrete-time systems, for beginning engineering readers. Designed and written by experienced and well- respected authors, this class-tested learning package can also be used as a self-teaching tool for anyone eager to discover more about DSP applications, multi-media signals, and MATLAB. Unique features, such as visual learning demonstrations, MATLAB laboratories and a bank of solved home-work problems are just a few things that make this an essential learning tool for mastering fundamental concepts in today's electrical and computer engineering institutions.

This text is derived from DSP First: A Multimedia Approach, published in 1997, which filled an emerging need for a new entry-level course not centered on analog circuits in the ECE curriculum. It was also successfully used in 80 universities as a core text for linear systems and beginning signal processing courses. This derivative product, Signal Processing First [SPF] contains similar content and presentation style, but focuses on analog signal processing.

Online Version

This is the standard text for introductory advanced undergraduate and first-year graduate level courses in signal processing. The text gives a coherent and exhaustive treatment of discrete-time linear systems, sampling, filtering and filter design, reconstruction, the discrete-time Fourier and z-transforms, Fourier analysis of signals, the fast Fourier transform, and spectral estimation. The author develops the basic theory independently for each of the transform domains and provides illustrative examples throughout to aid the reader. Discussions of applications in the areas of speech processing, consumer electronics, acoustics, radar, geophysical signal processing, and remote sensing help to place the theory in context. The text assumes a background in advanced calculus, including an introduction to complex variables and a basic familiarity with signals and linear systems theory. If you have this background, the book forms an up-to-date and self-contained introduction to discrete-time signal processing that is appropriate for students and researchers.

DSP in Matlab

DSP Video Lectures

Interactive Online Applets