FSF3847 Convex Optimization with Engineering Applications 6.0 credits

• Convex sets

• Convex functions

• Convex optimization

• Linear and quadratic programming

• Geometric and semidefinite programming

• Duality

• Smooth unconstrained minimization

• Sequential unconstrained minimization

• Interior-point methods

• Decomposition and large-scale optimization

• Applications in estimation, data fitting, control and communications

After completed course, the student should be able to

• characterize fundamental aspects of convex optimization (convex functions, convex sets, convex optimization and duality);

• characterize and formulate linear, quadratic, geometric and semidefinite programming problems;

• implement, in a high level language such as Matlab, crude versions of modern methods for solving convex optimization problems, e.g., interior methods;

• solve large-scale structured problems by decomposition techniques;

• give examples of applications of convex optimization within statistics, communications, signal processing and control.

The course requires basic knowledge of calculus and linear algebra.

S. Boyd och L. Vandenberghe, Convex Optimization, Cambridge University Press, 2004, ISBN: 0521833787

If the course is discontinued, students may request to be examined during the following two academic years.

• INL1 - Assignment, 6.0 credits, grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Successful completion of homework assignments and the presentation of a short lecture on a special topic.

There will be a total of four sets of homework assignments distributed during the course. Late homework solutions are not accepted.

The short lecture should sum up the key ideas, techniques and results of a (course-related) research paper in a clear and understandable way to the other attendees.

Anders Forsgren

• All members of a group are responsible for the group's work.
• In any assessment, every student shall honestly disclose any help received and sources used.
• In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.