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FEM3220 Matrix Algebra 10.0 credits

Information per course offering

Termin

Information for Spring 2026 Start 16 Mar 2026 programme students

Course location

KTH Campus

Duration
16 Mar 2026 - 1 Jun 2026
Periods

Spring 2026: P4 (10 hp)

Pace of study

50%

Application code

10932

Form of study

Normal Daytime

Language of instruction

English

Course memo
Course memo is not published
Number of places

Places are not limited

Target group
No information inserted
Planned modular schedule
[object Object]
Schedule
Schedule is not published
Part of programme
No information inserted

Contact

Examiner
No information inserted
Course coordinator
No information inserted
Teachers
No information inserted

Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus FEM3220 (Spring 2026–)
Headings with content from the Course syllabus FEM3220 (Spring 2026–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

Main content:

1. Review of vector spaces, inner product, determinants, rank

2. Eigenvalues, eigenvectors, characteristic polynomial

3. Unitary equivalence, QR-factorization

4. Canonical forms, Jordan form, polynomials and matrices

5. Hermitian and symmetric matrices, variational characterization of eigenvalues, simultaneous diagonalization

6. Norms for vectors and matrices

7. Location and perturbation of eigenvalues

8. Positive definite matrices. Singular value decomposition

9. Nonnegative matrices, positive matrices, stochastic matrices

10. Stable matrices; Lyapunov’s theorem

11. Matrix equations and the Kronecker product, Hadamard product

12. Matrices and functions square roots, differentiation


Additional topics selected for the student presentations

Intended learning outcomes

After the course the student should be able to:

  • use and explain some fundamental tools (specified by the course content) in matrix algebra.
  • identify research problems in which matrix algebra tools may be powerful.
  • apply the knowledge to solve and analyze the identified matrix algebra problems.
  • combine several sub problems and solutions to solve and analyze more complex problems.
  • show improved skills in problem solving and proof writing as well as in critical assessment of proofs and solutions.
  • show improved skills in oral presentation of technical contents.
  • reflect on sustainability and equity aspects as well as ethical issues related to the course content and its use

Literature and preparations

Specific prerequisites

Doctoral students at the School of Electrical Engineering. External participation by admission of the examiner.

Literature

You can find information about course literature either in the course memo for the course offering or in the course room in Canvas.

Examination and completion

Grading scale

P, F

Examination

  • INL1 - Homework, 7.0 credits, grading scale: P, F
  • SEM1 - Student presentation, 1.5 credits, grading scale: P, F
  • PRA1 - Peer grading, 1.5 credits, grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

If the course is discontinued, students may request to be examined during the following two academic years.

Examiner

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Education cycle

Third cycle

Postgraduate course

Postgraduate courses at EECS/Information Science and Engineering