Modul

The module will be completed by an oral exam (ca. 30 min).

The students know the basic definitions and properties of matrix functions. They can evaluate methods for approximating matrix functions in terms of convergence and efficiency, independently solve exercises, present their own solutions and implement the methods discussed.

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• Definition of functions of matrices
• Approximations to functions of matrices for large sparse matrices
• Krylov subspace methods and rational Krylov subspace methods
• Application to the numerical solution of partial differential equations 

The courses Numerical Analysis 1 and 2 are strongly recommended.

Total workload: 240 hours

Attendance: 90 hours

• lectures, problem classes, and examination

Self-studies: 150 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