[Forside] [Hovedområder] [Perioder] [Udannelser] [Alle kurser på en side]
The aim of the course is to give participants insight into methods for processing and analyzing of real world signals with a stochastic or incomplete nature. Participants will gain experience with methods for interpolation, analysis and prediction of stochastic signals based on advanced filtering techniques. Participants will also gain familiarity with different models used for spectral analysis of stochastic signals.
Real world signals, such as music, images or physiological signal from the human body, are stochastic in nature. Sometimes such signals are also corrupted and incomplete. The course will present different methods for interpolation, reconstruction and prediction of such signals based on advanced filtering techniques. Also methods for analysis of such signals will be presented i.e. methods for signal modeling and spectral estimation.
Students most know of signal analyses and signal processing at the level of a bachelor degree in electronic engineering or software engineering. Bachelors in computer science, physics or mathematics, with primary knowledge of signal analyses and signal processing will also be able to attend the course. Primary knowledge of stochastic signal processing is required.
Jakob Juul Larsen
Lectures and labs.
To be announced
March, re-examination after appointment with lecturer
Aarhus School of Engineering (ASE)
The participants must at the end of the course be able to:
Written exam, 2 hours. Grades on the 7-scale. External examinor.