Course code CTU15
Course title Digital Signal and Image Processing with Applications
Institution Czech Technical University in Prague
Course address Institute of Chemical Technology, Faculty of Chemical Engineering, Technicka 5, CZ-166 28 Prague 6, Czech Republic
City Prague
Minimum year of study 3rd year
Minimum level of English None
Minimum level of French None
Key words Signal analysis, discrete Fourier transform, Wavelet transform, signal and image processing, digital filters, biomedical signals, environmental signals, energy consumption signals, Matlab environment
Language English
Professor responsible Ales PROCHAZKA
Telephone 420 220 444 198
Fax 420 220 445 053
Participating professors
Number of places Minimum: 8, Maximum: 15, Reserved for local students: 0
Objectives The main goal of the course is to:
1. present selected mathematical and algorithmic structures in MATLAB
environment used for signal analysis and processing
2. study fundamentals of discrete Fourier transform and its properties in connection with signal and image analysis and discretization
3. analyse principles if digital filtering in the time (FIR, IIR) and
frequency domains for signal de-noising and image enhancement
4. discuss selected mathematical methods of signal analysis and to
present fundamentals of wavelet transform in signal decomposition,
modification and reconstruction with applications
5. summarize basic principles of signal modelling in its prediction using
both linear and nonlinear methods including neural networks
6. present selected applications of signal processing in environmental
engineering, biomedical signal and image processsing and energy
consumption data prediction

It is supposed that course participants will be able to use the MATLAB environment to solve selected problems of the interdisciplinary area of signal and image processing, to use its visualization tools, and to study selected applications of digital signal processing methods.
Programme to be followed Five 3-hour lectures:
1. Algorithmization in the MATLAB environment, visualization, programming tools, data processing.
2. Principles of the discrete Fourier transform, properties, applications
3. Digital filtering using difference equations. Frequency domain filters
4. Approximation of functions. Discrete Wavelet transform, basic
definitions, signal decomposition, de-noising, reconstruction
5. Signal prediction, linear models, neural networks, optimization

Three 1 hour case studies:
1. Two-dimensional modelling of air pollution data
2. Energy consumption data analysis
3. EEG signal de-noising

Four 2-hour seminar work:
1. Programming in MATLAB, structured data, computer graphics
2. Signal acquisition, visualization, analysis
3. Digital filters, graphical user interphase
4. Discussion of results

One 4-hour excursion:
Biomedical signal and image acquisition
Prerequisites Basic knowledge of numerical mathematics.
Course exam Continuous evaluation through laboratory exercises and an evaluation test at the end of the course.