Basic knowledge of numerical mathematics. 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.

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, pattern recognition and computational intelligence 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

Five 3-hour lectures:
1. Signal and system modelling, algorithmization in the MATLAB environment, visualization, programming tools
2. Principles of the discrete Fourier transform, properties, applications
3. Digital filtering using difference equations and frequency domain analysis
4. Approximation of functions, discrete wavelet transform, basic
definitions, signal decomposition, de-noising, reconstruction
5. Computational intelligence, neural networkds, pattern recognition

 
Three 1 hour case studies:
1. DSP in environmental engineering (air pollution data modelling)

2. DSP in prediction (modelling of energy consumption data)
3. DSP in biomedical signal and image processing

Four 2-hour seminar work:
1. Programming in MATLAB, structured data, computer graphics
2. Application of DSP and optimization in pattern recognition
3. Application of DSP in sleep, breathing and motion analysis
4. Colloquium with presentation of selected case studies

Excursions:
Czech Institute of Informatics, Robotics and Cybernetics, Digital Signal Processing Laboratory, Technical Museum

Continuous evaluation through laboratory exercises and an evaluation during the final colloquium.

Saturday, November 14, 16:00 – 18:00 Welcome meeting
Sunday, November 15, 15:00 –  18:00 Prague Discovery Game, 18:00 - 21:00 Dinner party
Friday, November 20, 17:00 – 19:00 – Farewell Party