Specialization profile--Signal Processing
The Signal Processing discipline focuses on the theory, design, and application of advanced signal processing methods. Students gain expertise in topics such as array processing, detection and estimation, sampling theory, distributed processing, convex optimization, graph signal processing, and machine learning. Applications range from audio and acoustics to wireless communication, radio astronomy, biomedical imaging (MRI, ultrasound, EEG, ECG), and video analysis.
Signal Processing also addresses cutting-edge domains like distributed sensing from space and signal systems for autonomous driving. You will combine theoretical foundations with practical system design for solving real-world challenges in science and engineering.
This discipline prepares for a thesis in the SPS Section.
By selecting certain courses, you could follow a profile into one of the following directions:
- Signal processing for communication
- Audio and acoustic signal processing
- Biomedical signal procesing
- Machine learning
- Distributed autonomous systems
Suggested courses
| AP3232 | Medical imaging signals and systems | 4/4/0/0 | 6 EC | details | |||
| BM41055 | Anatomy and physiology | 2/2/0/0 | 4 EC | details | |||
| CESE4120 | Smart phone sensing | 0/0/0/2 | 5 EC | details | |||
| DSAIT4305 | Graph machine learning | 4/0/0/0 | 5 EC | details | |||
| EE4530 | Applied convex optimization | 0/4/0/0 | 5 EC | details | |||
| EE4540 | Distributed signal processing | 0/0/0/4 | 5 EC | details | |||
| EE4595 | Wavefield imaging | 0/0/4/0 | 5 EC | details | |||
| EE4685 | Bayesian machine learning | 0/0/4/0 | 5 EC | details | |||
| EE4715 | Array processing | 0/0/0/4 | 5 EC | details | |||
| EE4740 | Sparse signal processing | 0/0/4/0 | 5 EC | details | |||
| EE4750 | Tensor networks for green AI and signal processing | 3/0/0/0 | 4 EC | details | |||
| EE4760 | Probablistic sensor fusion | 0/0/2/0 | 4 EC | details | |||
| EE4845 | Fundamentals of radar and applications | 0/4/0/0 | 5 EC | details | |||
| EE4C12 | Machine learning for Electrical Engineering | 4/0/0/0 | 5 EC | details | |||
| ET4358 | Fundamentals of wireless communications | 0/4/0/0 | 5 EC | details | |||
| ET4386 | Estimation and detection | 0/4/0/0 | 5 EC | details | |||
| RO47002 | Machine learning for robotics | 6/0/0/0 | 5 EC | details | |||
| RO47019 | Intelligent control systems | 0/0/4/0 | 4 EC | details | |||
| SC42015 | Control theory | 6/0/0/0 | 6 EC | details | |||
| SC42025 | Filtering and identification | 0/4/0/0 | 6 EC | details | |||
| SC42056 | Optimization in Systems and Control | 4/0/0/0 | 3 EC | details | |||
| SC42075 | Modeling and control of hybrid systems | 0/0/0/4 | 3 EC | details | |||
| SC42101 | Networked and distributed control systems | 0/0/0/4 | 4 EC | details | |||
| SC42125 | Model predictive control | 0/0/4/0 | 4 EC | details |
MSc project proposals
Some examples of thesis topics (this list is not exhaustive):Thesis examples
Contact person
For more information about the research group, possible thesis topics, and suggestions for your ISP:prof.dr.ir. Alle-Jan van der Veen
Signal Processing Systems Group
Department of Microelectronics
