English version below.
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GOALS:
The students have a basic knowledge of MATLAB and are also proficient in specific aspects of MATLAB programming. MATLAB is a widely used programming language from The MathWorks, Inc. It is used extensively to solve technical and scientific problems in both research and industry. The students have become familiar with the essential functions and properties of MATLAB in the context of interesting applications. They understand the differences between programming in MATLAB and other common programming languages, such as working with vectors and matrices and the straightforward implementation of graphical user interfaces. At the same time, they possess an in-depth understanding of applications in communications engineering and audio signal processing.
CONTENTS:
In this practical course, students will be gradually introduced to the specific features of the MATLAB programming environment. The main topics covered in the course are:
- Generation and use of vectors, matrices and operators
- Memory- and runtime-efficient programming
- Simple data input and output, graphical representation of one-dimensional signals
- Design of digital filters, calculation of frequency response, spectral analysis
- Implementation of simple graphical user interfaces
- The Signal Processing Toolbox and the DSP Systems Toolbox
- Using Cell Arrays
- Debugging MATLAB code
Programming methods are learned using applications from communication technology and communication acoustics, e.g.
- LTI Systems (Digital Filters)
- Compression (Huffman Code)
- BPSK Modulation/Demodulation (Baseband Transmission)
- Channel coding (repeat codes,...)
- MISO broadcast channel (beamforming vs. TDMA)
- Audio signal equalizer
- Auditory filter bank
- Feature extraction for audio classification
- Gaussian mixture models for classification
- Flexible multi-channel filtering using cell arrays
- Real-time source tracking with DSP Systems Toolbox and Kinect
MISCELLANEOUS:
The experiments are carried out in groups of two.
documentation
http://www.mathworks.de/products/matlab/
It is recommended to attend the lecture "System Theory 1" concurrently.
TEST:
Internship, registration at the chair
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GOALS:
The students attain basic knowledge about Matlab and further they learn the specified aspects of programming with Matlab. Matlab is a widely applied programming language developed by MathWorks. This programming language is commonly used for solving the scientific and engineering problems in both research and industrial projects. In this course, the students learn the scientific functionalities and specifications of Matlab in connection with interesting practical applications. Furthermore, they achieve a general overview about the differences between programming in Matlab and other common programming languages. Some examples for these differences are array and matrix operations and visualization capabilities offered by Matlab. Furthermore, the students acquire deep understanding about applications of Matlab in communications technology and audio signal processing.
CONTENT:
In each laboratory session different features of Matlab programming will be discussed. The content of the laboratory is given as follows:
- Generating vectors, matrices and their related operations
- Memory and time efficient programming
- Input and output data, graphical illustration of one-dimensional signals
- Implementation of digital filters, calculating the frequency response, spectral analysis
- Implementation of simple graphical user interface (GUI)
- Signal processing toolbox and DSP system toolbox
- Applications of cell array
- Debugging a Matlab program
The programming methods are presented with the aid of following applications in domains communications technology and audio signal processing.
- LTI systems (digital filter)
- Compression (Huffman Code)
- BPSK modulation/demodulation (baseband transmission)
- Channel coding (repetition code)
- MISO broadcast channel (beam forming vs. TDMA)
- Audio signal equalization
- Auditory filter banks
- Feature extraction for sound classification
- Gaussian mixture model based classification
- Flexible multichannel filtering by applying cell arrays
- Real time source tracing with DSP system toolbox and kinect
MISCELLANEOUS:
The experiments are performed in groups of two students. Documentation: http://www.mathworks.de/products/matlab/ Registration: The registration takes place via
https://moodle.ruhr-uni-bochum.de/ , course number: 142222
We recommend taking the lecture System Theory 1 in parallel.
EXAM:
Practical courses, registration: with the lecturer
- Kursleiter/in: Akshay Dodwadmath
- Kursleiter/in: Mohammad Khosravi
- Kursleiter/in: Setareh Maghsudi
- Kursleiter/in: Klara Leoni Wallbaum