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WI4201: Scientific Computing
Responsible Instructor: C. Vuik
Instructor: Dr. D.J.P. Lahaye
Contact Hours / Week x/x/x/x: 2/2/0/0
Education Period: 1, 2
Start Education: 1
Exam Period: Exam by appointment
Course Language: English
Expected prior knowledge: A basic knowledge on partial differential equations (PDEs), on numerical methods for solving ODEs/PDEs, and on linear algebra.
Course Contents: During the course, the important steps towards the solution of real-life
applications dealing with partial differential equations will be outlined. Based on a well-known basic partial differential equation, which is representative for different application areas, we treat and discuss direct and iterative solution methods from numerical linear algebra in great detail. The discretization of the equation will result in a large system of discrete equations, which can be represented by a sparse matrix. After a discussion of direct solution methods, the iterative solution of such systems of equations is an important step during numerical simulation. Emphasis is laid upon the so-called Krylov subspace methods, like the Conjugate Gradient Methods. Finally, a concrete real life application will be presented.
Study Goals: Student is able to solve linear systems by direct and iterative method, student should be able to analyse these method, approximation methods of eigenvalues can be used.
Education Method: Lectures/computer exercises
Literature and Study Materials: Lecture notes, for further reading the book Matrix Computations, G.H. Golub and C.F. van Loan, the Johns Hopkins University, Baltimore, 1996, can be used.
Assessment: Home work/computer exercise project/oral exam
Last modified: 6 November 2013, 15:25 UTC
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