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