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