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Convex Optimization (Konvexe Optimierung) (3V/1U)
- Lecturer
- Assistant
- Time and place (3h lecture + 1h exercise)
- Course description (Engineer@work)
- Linear programming (LP)
- Semidefinite programming (SDP)
- Linear matrix inequalities (LMIs)
- Duality theory
- Relaxation techniques
- Polynomial optimization
- Numerical algorithms
- Applications
| First lecture: Thursday, October 20th, 2011 | ||
| Wednesday 9:45-11:15, V 9.3.243 | ||
| Thursday 9:45-11:15, V 9.3.243 |
|
Over the past 15 years, convex optimization has become an important tool in many areas of engineering and applied sciences, such as systems theory and control, mechanics, signal processing, communication, combinatorics and graph theory, machine learning, operations research, electronic circuit design and biology. This course gives an introduction to the theory and application of convex optimization. The software used in the course is Matlab in combination with Yalmip. Some of the covered topics are: No specific course prerequisites are required. The course is given in English. |
Universität Stuttgart
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