Matrix algorithms
Additional Info
- ECTS credits: 6
- University: Hamburg University of Technology
- Semester: 3
- Lecturer 1: J.-P Zemke
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Objectives:
The aim of the course is to enable the students to name, state and classify state-of-the-art Krylov subspace methods for the solution of the core problems of the engineering sciences, namely, eigenvalue problems, solution of linear systems, and model reduction; they gather basic knowledge about approaches for the solution of matrix equations.
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Topics:
Part A (Krylov subspace methods): derivation (Richardson and power method); computation of a basis; Ritz, OR, and MR approaches; Arnoldi-based methods (Arnoldi, GMRes); Lanczos-based methods (Lanczos, CG, BiCG, QMR, SymmLQ, PvL); Sonneveld-based methods (IDR, BiCGStab, TFQMR, IDR(s)). Part B (matrix equations): Sylvester equation; Lyapunov equation; algebraic Riccati equation.