MM862: Selected topics in numerical anlysis II

The Study Board for Science

Teaching language: English
EKA: N310068102
Assessment: Second examiner: Internal
Grading: 7-point grading scale
Offered in: Odense
Offered in: Spring
Level: Master

STADS ID (UVA): N310068101
ECTS value: 5

Date of Approval: 13-10-2025


Duration: 1 semester

Version: Approved - active

Entry requirements

None

Academic preconditions

Students taking the course are expected to:

  • have knowledge of elementary mathematical background as provided by the courses Calculus, Linear Algebra, Mathematical and Numerical Analysis and Ordinary Differential Equations

Basic skills in scientific programming may be helpful but are not mandatory.

Course introduction

The aim of the course is to enrich the students' skills and range in numerical analysis and applied mathematics and to show prospects for possible thesis topics. and enabled the student to:  
  • understand advanced principles of numerical thinking
  • understand and work with numerical analysis in a broad range of applications
  • compare and contrast the methods introduced in the course
  • transfer the learning content to new problems
  • to make use of the techniques in practical applications

Expected learning outcome

The learning objective of the course is that the student demonstrates the ability to:
  • know the definitions of the quantities and terms that were introduced in the lecture.
  • relate the main purpose and raison d'être of every section of the whole lecture
  • know the key ideas for the derivation of the main theorems and algorithms that are introduced in the lecture
  • demonstrates the ability to cover some selected topics in full detail, including proof techniques
  • adapt and transfer known concepts to new, related application scenarios
  • to formulate the problems (including proofs) in a correct and formal mathematical language
  • to analyze, apply and modify the introduced techniques

Content

The following main topics are contained in the course: Introduction to one or more topics in numerical analysis.
This could, for example, be:

  • Matrix analysis and matrix decompositions
  • Iterative solutions of eigenvalue problems
  • Design and analysis of computer experiments
  • Model reduction
  • Matrix manifolds and applications such as interpolation and optimization
  • Matrix completion

(The precise selection complements or expands on the course "MM566").

Literature

See itslearning for syllabus lists and additional literature references.

Examination regulations

Exam element a)

Timing

June

Tests

Oral

EKA

N310068102

Assessment

Second examiner: Internal

Grading

7-point grading scale

Identification

Student Identification Card - Name

Language

Normally, the same as teaching language

Examination aids

All aids allowed

ECTS value

5

Indicative number of lessons

42 hours per semester

Teaching Method

Planned lessons:
Total number of planned lessons: 42
Hereof:
Common lessons in classroom/auditorium: 28
Team lessons in classroom/auditorium: 14

In the lectures, concepts, theories and models are introduced and put into perspective. In the tutorial sessions, the students train their skills through exercises and dig deeper into the subject matter.

Other planned teaching activities:
  • Reading of suggested literature
  • Preparation of exercises in study groups
  • Contributing to online learning activities related to the course

Teacher responsible

Name E-mail Department
Ralf Zimmermann zimmermann@imada.sdu.dk Computational Science

Timetable

Administrative Unit

Institut for Matematik og Datalogi (matematik)

Team at Registration

NAT

Offered in

Odense

Recommended course of study

Profile Education Semester Offer period

Transition rules

Transitional arrangements describe how a course replaces another course when changes are made to the course of study. 
If a transitional arrangement has been made for a course, it will be stated in the list. 
See transitional arrangements for all courses at the Faculty of Science.