MGander Scientific Computing

Faculty of Science
Autumn 2008
Extent and Intensity
4/0. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
prof. Walter Gander (lecturer), prof. RNDr. Ivanka Horová, CSc. (deputy)
Guaranteed by
prof. RNDr. Ivanka Horová, CSc.
Department of Mathematics and Statistics – Departments – Faculty of Science
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 12 fields of study the course is directly associated with, display
Course objectives
NONLINEAR EQUATIONS
We will continue the topic presented by Prof. Horova and discuss the sensitivity of roots of polynomials, the convergence rates of iterative methods and the derivation of third order methods. We will illustrate the theory with examples and demonstrations using Maple and Matlab. If time permits we will also show how to solve a system of nonlinear equations.

SINGULAR VALUE DECOMPOSITION
The singular value decomposition (SVD) of a matrix has become the "Swiss Army Knife" of computational linear algebra. This is the merit of G. Golub and Chr. Reinsch who developed the robust algorithm used today in every software library. We will discuss the Golub-Reinsch algorithm and show several applications of the SVD.
Syllabus
  • 1.Nonlinear Equations
  • 2. Singular Value Decomposition
Language of instruction
English
Further Comments
The course is taught only once.
The course is taught: in blocks.
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