Course detail
Advanced Analysis of Biological Signals
FEKT-FACSAcad. year: 2011/2012
The course is oriented to multirate signal processing, wavelet transforms, parametric methods for power spectrum estimation, Karhunen-Loeve transform (KLT) and principal component analysis (PCA).
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Learning outcomes of the course unit
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Course curriculum
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Proakis,J.G., Manolakis,D.G.: Digital Signal Processing. Principles, Algorithms and Applications. Macmillan, 1992 (EN)
Recommended reading
Classification of course in study plans
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
Design of multirate filters
Time-frequency analysis, continuous-time wavelet transform (CTWT)
Discrete-time wavelet transform (DTWT), dyadic and packet DTWT
Use of CTWT in analysis of biosignals
Lossy compression of biosignals
Use of DTWT in compression of biosignals
Redundant DTWT for filtering and analysis of biosignals
Spectral analysis of biosignals and parametric methods for power spectrum estimation
Linear prediction and Burg method for power spectrum estimation
Karhunen-Loeve transform (KLT) and principal component analysis (PCA)
Multivariate signal analysis
Applications of KLT and PCA for analysis of biosignals
Exercise in computer lab
Teacher / Lecturer
Syllabus
Implementations of multirate filters
CTWT with Wavelet toolbox for Matlab
Applications of CTWT
DTWT with Wavelet toolbox for Matlab
Applications of DTWT
Realization of DTWT without the Wavelet toolbox
Redundant DTWT and wavelet filtering
Packet DTWT
Parametric methods for power spectrum estimation
Realization of Karhunen-Loeve transform, principal component analysis
Applications of KLT and PCA for analysis of biosignals
Presentations of projects