Module Content

The module covers
  • vector spaces,
  • linear transformations,
  • orthogonality,
  • and explains how these topics can be applied to
  • signal processing,
  • computer graphics,
  • data fitting.

Module Coordinates

  • Lecturer: Tobias Rossmann
  • Lectures: pre-recorded videos of lectures will be made available via Blackboard
  • Tutorials: Tuesday 1-2pm (online for now) beginning in week 2
  • Recomended text: David C. Lay, "Linear Algebra and Its Applications", Fourth Edition, Pearson, 2012
  • Problem sheet: available here.
  • Module Website: Information and module documents will be posted to this site, which is linked from the Blackboard MA313 Linear Algebra pages. Blackboard will also be used for announcements and for posting grades.

Module Assessment

  • End of semester examination: 50%.
  • Continuous assessment: 30%.
  • Communications skils: 20%.

Supplementary Material and News

A model paper is avaialble here.

Clicker opinion polling may be used in some lectures.

Lecture Notes

Lecture Notes
(click on number)

Lecture Summaries
1
Introduction and course overview. Definition of a vector space. Rn is a vector space.
2
Examples of vector spaces. Subspaces.
3
Further examples of subspaces. Linear combinations.
4
Spans. Null spaces.
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