Recommended prerequisite for participation in the module

Content, progress and pedagogy of the module

Learning objectives

Knowledge

Students who complete the module:

• Have knowledge about different tools for joint-time-frequency analysis
• Demonstrate understanding of the trade-off between time and frequency resolution in the analysis of a non-stationary signal
• Can explain the relationships between time-frequency and wavelet analysis
• Have knowledge about adaptive filtering and multivariate signal processing
• Can identify different nonlinear tools that can be applied to analyze biomedical signals
• Have knowledge about methods for estimation of features from biomedical signals

Skills

• Can reflect on the choice of appropriate time-frequency distributions suitable to different biomedical problems
• Can design wavelets for multi-resolution analysis of signals with specific biomedical applications such as filtering
• Can evaluate appropriate adaptive filters suitable for the problem to solve
• Can apply multivariate tools for classification and feature space reduction
• Can analyze and describe nonlinear analysis methods
• Can analyze and describe the frequency content of a biomedical signal with respect to time
• Can handle de-noising of biomedical signals using various techniques such as wavelet and adaptive filters

Type of instruction

Lectures and exercises.

Exam

Exams

Additional information

Please contact the   programme student counsellors if you consider applying to the education and you have questions.

Please consult the Moodle page for your semester and contact the semester coordinator if you have academic questions, or the study secretary if you have administrative questions.

All other enquiries may be directed to Malene Møller Knudsen, secretary of the Study Board.