Convex Optimization Laboratory
Lecturer: Wolfgang Utschick with Sadaf Syed
Target Audience: Master EI and MSCE
Language: English
Next Exam: oral exam in summer 2025 (no responsibility is taken for the correctness of this information)
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