Information on individual educational components (ECTS-Course descriptions) per semester

Higher Mathematics 3

Degree programme Mechatronics
Subject area Engineering & Technology
Type of degree Master
Full-time
Winter Semester 2024
Course unit title Higher Mathematics 3
Course unit code 024612030601
Language of instruction German, English
Type of course unit (compulsory, optional) Compulsory
Teaching hours per week 2
Year of study 2024
Level of the course / module according to the curriculum
Number of ECTS credits allocated 3
Name of lecturer(s) Thomas STEINBERGER
Requirements and Prerequisites

Higher Mathematics 1 and 2

Course content

The students learn how to solve non-linear systems of equations and non-linear optimization problems with and without constraints mostly in an iterative and approximative way. Theory of solving elliptic partial differential equations, Ritz Galerkin method for approximative solutions and the application of this theory to FEM will be discussed.

Learning outcomes

The students know how to treat some typical nonlinear optimization problems and are able to apply standard methods for their solution. A mostly geometrical interpretation and intuition shall be learned for the formulation and solution of the problems. Theory of solving elliptic partial differential equations, Ritz Galerkin method for approximative solutions and the application of this theory to FEM should be understood.

Planned learning activities and teaching methods

Integrated course: Besides the lectures the participants work on many exercises at home and during the course.

Assessment methods and criteria

Exam

Comment

None

Recommended or required reading

„EE103 - Applied Numerical Computing (Fall 2011-12)“ (o. J.): EE103 - Applied Numerical Computing (Fall 2011-12). Online im Internet:http://www.seas.ucla.edu/~vandenbe/ee103.html (Zugriff am: 08.02.2017).

Topics: # non-linear equations # non-linear optimization.

Mode of delivery (face-to-face, distance learning)

Face to face