COMPUTATIONAL INTELLIGENCE AND DIGITAL SIGNAL PROCESSING RESEARCH GROUP
Panorama
S4
COMPUTATIONAL INTELLIGENCE AND
DIGITAL SIGNAL AND IMAGE PROCESSING
WITH APPLICATIONS

*** Czech Technical University ***
Czech Institute of Informatics, Robotics and Cybernetics
Supported by EU Socrates Programme
*** University of Chemistry and Technology ***
Department of Computing and Control Engineering
Computational Intelligence and Digital Signal and Image Processing Research Group
Prof. Ing. Aleš Procházka, CSc
S5

S5

ATHENS

COURSE TOPICS


BLOCK SECTION
1		 SECTION
2		 SECTION
3		 Text Case studies
A Numerical Methods: Introduction to signal processing, MATLAB programming, visualization, programming tools, structured arrays, selected methods of data processing, linear algebra, the least square method, approximation and interpolation Signal and System Modelling:
Z-transform, difference equations, system description 		Case Study 1: DSP in environmental engineering: Spatial modelling of air pollution data Matlab
MATLAB
B Spectral Analysis: Discrete Fourier transform, properties, frequency components detection, short time Fourier transform, window functions, applications Digital Filters:
Digital filtering using difference equations, FIR and IIR filters, frequency domain filtering
Case Study 2: DSP in prediction of energy consumption DSP
DSP 		Project MME
PROJECTenNN
C Time-scale Analysis:
Discrete Wavelet transform, basic definitions, signal decomposition, de-noising, reconstruction
Applications: DSP in signal and image processing
Case Study 3: DSP in biomedical signal and image processing Project DSP
PROJECTenNN
D Neural Networks:
Computational intelligence, artificial neural networks, mathematical description, error surface, optimization, adaptive linear element, signal denoising
Classification: Feature extraction, classification, nearest neighbour method, Kohonen learning, deep learning
Case Study 4:
Classification of EEG segments 		Project NN
PROJECTenNN
F Signal Prediction:
Neural networks in signal prediction. recurrent systems, applications of data processing in physiological signal processing, robotic systems and computer vision

Conclusion: History and interdisciplinary applications of digital signal and image processing
COLLOQUIUM
ATHENS_EXAM 		TOPICS
ATHENS_EXAM

DATA FILES Real Data Files: Biomedical Signals (EEG, MRI, motion data), Environmental Signals (Air Pollution), Energy Data (Gas consumption, photovoltaics), ... DATA

CS1 CS2 CS3

INFORMATIONS COURSE OVERVIEW:      PRESENTATION REFERENCES:      REFERENCES