Syllabus for |
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| LMA224 - Mathematical supplementary course |
| Matematisk överbryggningskurs |
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| Syllabus adopted 2019-03-01 by Head of Programme (or corresponding) |
| Owner: TIMAL |
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7,5 Credits
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| Grading: TH - Five, Four, Three, Fail |
| Education cycle: First-cycle |
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Major subject: Mathematics |
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Department: 11 - MATHEMATICAL SCIENCES
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Teaching language: Swedish
Application code: 65121
Open for exchange students: No
Block schedule:
D
| Module |
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Credit distribution |
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Examination dates |
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Sp1 |
Sp2 |
Sp3 |
Sp4 |
Summer course |
No Sp |
| 0107 |
Examination |
7,5c |
Grading: TH |
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7,5c
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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.