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Optimization with applications

This is the study programme for 2019/2020. It is subject to change.

The course presents traditional techniques used for finding optimal solutions to problems in electrical engineering using linear algebra. Many examples are given.

Learning outcome

  • To understand abstract vector spaces and how they can be applied to optimisation problems.

  • To formulate, and then solve optimisation problems in electrical engineering.

General competance:
  • Upon course completion, the student have established a basic understanding of linear algebra and its applications in electrical engineering.


Basic definitions of abstract vector spaces, inner product, Hilbert space, the projection theorem and its applications, dual approximation, eigenvalues and eigenvectors, nonlinear optimisation, convexity, gradient searches and Lagranges multiplicator method.

Required prerequisite knowledge



Weight Duration Marks Aid
Written exam1/14 hoursA - F

Coursework requirements

There are in total 9 pen-and-paper/computer assignments, where the last one is compulsory, and at least 6 must be approved by the subject teacher within the specified deadlines.

Course teacher(s)

Course coordinator
Sven Ole Aase
Head of Department
Tom Ryen

Method of work

5 hours lectures, 1 hour computer similations in Matlab.

Open to

Master studies at the Faculty of Science and Technology.

Course assessment

Form and/or discussion


Lecture notes.
Support literature:
Moon & Stirling: "Mathematical methods and algorithms for signal processing., Pearsons 2000.
Wayne L. Winston: "Introduction to mathematical programming: Applications and algorithms", International Thomson Publishing 1995.
David G. Luenberger: "Optimization by vector space methods", Wiley 1968.

This is the study programme for 2019/2020. It is subject to change.

Sist oppdatert: 27.05.2020