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Graduate courses

Departments' graduate courses for PhD-students.

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Syllabus for

Academic year
LMA224 - Mathematical supplementary course
Matematisk överbryggningskurs
 
Syllabus adopted 2019-03-01 by Head of Programme (or corresponding)
Owner: TIMAL
7,5 Credits
Grading: TH - Five, Four, Three, Fail
Education cycle: First-cycle
Major subject: Mathematics
Department: 11 - MATHEMATICAL SCIENCES


Teaching language: Swedish
Application code: 65121
Open for exchange students: No
Block schedule: D

Module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0107 Examination 7,5c Grading: TH   7,5c   20 Mar 2020 am L,  09 Jun 2020 pm L,  26 Aug 2020 am L

In programs

TIELL ELECTRICAL ENGINEERING - Common branch of study, Year 3 (elective)
TIMEL MECHATRONICS ENGINEERING, Year 3 (elective)
TIEPL INDUSTRIAL MANAGEMENT AND PRODUCTION ENGINEERING, Year 3 (compulsory elective)
TKMAS MECHANICAL ENGINEERING, Year 2 (elective)

Examiner:

Joakim Becker

  Go to Course Homepage

Replaces

LMA221   Mathematical analysis, advanced course


Eligibility:

In order to be eligible for a first cycle course the applicant needs to fulfil the general and specific entry requirements of the programme(s) that has the course included in the study programme.

Course specific prerequisites

The courses Linear algebra and Calculus or equivalent.

Aim

The aim of the course is, together with the other mathematical courses in the programme for Mechanical engineering, to give general knowledge in mathematics that is as useful as possible in further studies or technical profession. In particular the course aims to prepare for continuation at Chalmers programme in Mechanical engineering at master level.

Learning outcomes (after completion of the course the student should be able to)

- describe the significance and meaning of the fundamental concepts of calculus (in one and several variables), linear algebra and the corresponding numerical analysis
- describe the relations between the different concepts
- use the concepts to solve mathematical problems
- apply improved skills in Matlab programming to solve computational problem

Content

Vector spaces, subspaces, linear independence, basis, change of basis. Linear transformations. The least squares method. Eigenvalues, eigenvectors and diagonalization. Numerical solution of non-linear systems of equations. Extremal values, optimization on compact domains, optimization with constraints. Numerical optimization: Newton's method and the method of gradients. Double and triple integrals, numerical computation and applications. Line integral. Green's formula. Numerical solution of ordinary differential equations. Introduction to partial differential equations: Laplace and Poisson equations, numerical solutions. Applications in Matlab.

Organisation

Lectures and computer classes.

Literature

Literature will be announced on the course web page before start of the course.

Examination including compulsory elements

The examination consists of a written exam at the end of the course and compulsory assignments.


Published: Wed 26 Feb 2020.