Modul

Success is assessed in the form of an oral examination lasting approx. 30 minutes.

Graduates can explain the ideas of compressive sensing and can name areas of application. They can apply and compare the basic algorithms and analyze their convergence behavior.

• What is compressive sensing and where is it used?
• Sparse solutions of underdetermined linear systems of equations
• Basic algorithms
• Restricted isometry property
• Sparse solutions of underdetermined linear systems of equations with random matrices

The course "Introduction to stochastics" is recommended.

Total workload: 150 hours

Attendance: 60 hours

• lectures, problem classes, and examination 

Self-studies: 90 hours

• follow-up and deepening of the course content,
• work on problem sheets,
• literature study and internet research relating to the course content,
• preparation for the module examination