Convex Optimization Laboratory
Lecturer: Wolfgang Utschick with Sadaf Syed
Target Audience: Master EI and MSCE
Language: English
Next Exam: oral exam in summer 2024 (no responsibility is taken for the correctness of this information)
Additional Information: TUMonline and Moodle
Content
This laboratory provides insights and practical instructions for designing algorithms in the field of communications engineering and signal processing based on mathematical optimization theory by a series of successive teaching and hands-on units. Each unit includes the understanding and analysis of a typical problem of the addressed application scenarios, its mathematical modeling, and the design and implementation of an adequate solution in MATLAB. Designed algorithms from a previous unit of the laboratory are supposed to be reused.
The addressed topics will cover
- CVX solver
- disciplined convex programming rules
- gradient methods
- linear programming
- interior-point method
- Lagrangian duality
- dual decomposition method
- subgradient method
- cutting plane methods
- conic optimization
- SDTP3 solver
- YALMIP solver
- non-convex optimization
- monotonic optimization
- greedy methods