TSBB06 · 6 credits · Advanced level (A1N) · Elektroteknik
Multidimensional Signal Analysis
Active · next start HT 2026
91%
passed the latest ordinary exam
TEN2 · 14 Jan 2026 · 32 students
84%
passed the ordinary exams, all sittings over the last 5 years
TEN2 · 119 students
60%
Harder than 60% of courses at advanced level
Compared with 285 courses at the same level, ordinary exams over the last three academic years. 63 students.
Part of 7 programmes
- Master of Science in Computer Science and Engineering
- Master of Science in Applied Physics and Electrical Engineering
- Master of Science in Information Technology
- Master of Science in Biomedical Engineering
- Master of Science in Computer Science and Software Engineering
- Master's Programme in Biomedical Engineering
- Master's Programme in Mathematics
Exam
TEN2 Written Examination
- 5
- 4
- 3
- U
Ordinary exams
84% passed · 119 students
- 91%32
- 74%31
- 90%21
- 75%12
- 87%23
Re-exams
64% passed · 22 students
- 86%7
- 57%7
- 50%8
- Pass the re-exam: 64% (22 students), compared with 84% (119 students) on the ordinary exam
- Get 4 or 5: 43% (141 students)
Show small sittings (8)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 50%2
- 100%2
- 100%1
- 33%3
- 100%2
- 0%1
- 100%1
- 100%3
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
LAB1 Laboratory Work
- G
Main rounds
100% passed · 80 students
- 100%27
- 100%22
- 100%13
- 100%18
Later rounds
No sittings with at least 5 students.
Show small sittings (7)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%2
- 100%1
- 100%1
- 100%1
- 100%1
- 100%1
- 100%1
Hand-in or lab
LAB2 Laboratory Work
- G
Main rounds
100% passed · 35 students
- 100%35
Later rounds
No sittings with at least 5 students.
Other module
KTR1 Optional Written Test
- G
- U
Main rounds
78% passed · 69 students
- 85%26
- 63%24
- 89%19
Later rounds
90% passed · 10 students
- 90%10
- Pass a later round: 90% (10 students), compared with 78% (69 students) on the ordinary exam
Show small sittings (1)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 0%1
Other module
KTR2 Optional Written Test
- G
- U
Main rounds
66% passed · 29 students
- 66%29
Later rounds
No sittings with at least 5 students.
About the course
Aim
An objective of the course is to provide a solid theoretical foundation for further studies and applications in 3D computer vision and in machine learning with images. Passing the course means that the student is able to use concepts and methods in signal and image analysis that are based on linear algebra. The student is then able to:
- Explain and use homogeneous coordinates for geometric calculations in two and three dimensions. This includes points and lines in two dimensions, points, planes, and lines in three dimensions, homographies, camera projections, and epipolar geometry.
- Explain and use least squares techniques to define estimation problems for different geometric objects. This includes triangulation, image filtering, and rigid transformations.
- Use bases, dual bases, subspace bases and frames to perform calculations for signal analysis
- Apply linear signal representations on practical problems, such as normalized convolution, over-sampling, PCA, wavelet-transform and filter banks.
Content
Signal spaces and signal bases, dual bases. Least squares problem, normalized convolution. Eigenvalue and singular value analysis. Principal component analysis. Frames. Wavelet transform and filterbanks. Projective spaces, homogeneous coordinates, homographies, camera projections, epipolar geometry. Representation and estimation of various types of geometric objects.
- Examiner
- Mårten Wadenbäck
- Scheduled hours
- 68 h
- Main field of study
- Elektroteknik