[Forside] [Hovedområder] [Perioder] [Udannelser] [Alle kurser på en side]
The aim of the course is to give participants insight into methods for Nonlinear Signal Processing and Pattern Recognition of real world signals such as music, images/video or physiological signal from the human body. Participants will gain experience with nonlinear models of such signals, where techniques from estimation/detection theory and machine learning will be used for identification of suitable models and further analysis and decision making based on the signals. Participants will obtain practical experience, through work on a smaller number of topic reports.
The course will present nonlinear methods for analyzing and decision making based on real world signals. Techniques from estimation/detection theory and machine learning will be presented and applied on specific cases (tentative 4 mini projects).
Human Computer Interface based on brain signals (physiological signal from the human body).
Students most know of signal analyses and signal processing at the level of a bachelor degree in electronic engineering or software engineering supplemented with the course in Advanced Signal Processing and Analysis. Bachelors in computer science, physics or mathematics, with primary knowledge of stochastic signal analyses and signal processing will also be able to attend.
Peter Ahrendt and Henrik Karstoft
Lectures, labs and mini reports.
To be announced
June, re-examination after appointment with lecturer
Aarhus School of Engineering (ASE)
The participants must at the end of the course be able to:
Oral examination (30. min) based on curriculum questions (67%) and mini report (33%). Grades on the 7-scale. External examiner.