Graph Signal Processing, Learning and Optimization
| Module Number | 18-pe-2080 |
| Degree Programs | MSc ETiT |
| Credit Points (CP) | 6 |
| Language | English |
| Form of Teaching | Lectures (3 SWS) and tutorials (1 SWS) |
| Form of Examination | Written or oral exam |
Teaching Content
Graph signal processing (i.e., processing of signals defined over graphs) and network analysis form an interdisciplinary research area with many diverse applications. The course provides a systematic introduction to the theory of graph signal processing, graphical network analysis, graph topology learning, optimization over graphs and learning with graph neuronal networks. In this course the students will learn the main concepts, algorithms and application areas that are fundamental in graph signal processing.
Outline:
- Motivation and applications
- Fundamentals
- Graph signal processing
- Network topology inference
- Graph analysis
- Optimization over graphs
- Graph neuronal (convolutional) network
