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


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