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Valid for year : 2011
 
TSBB06 Multidimensional Signal Analysis, 6 ECTS credits.
/Multidimensionell signalanalys/

For:   BME   D   I   Ii   IT   Y  

 

Prel. scheduled hours: 48
Rec. self-study hours: 112

  Area of Education: Technology

Main field of studies: Electrical Engineering

  Advancement level (G1, G2, A): A

Aim:
Passing the course means that the student is able to use concepts and methods in signal and image processing that are based on linear algebra. The student is then able to:
  • Use homogeneous coordinates for the Euclidean geometry of two and three dimensions. This includes points and lines in two dimensions, points, planes, and lines in three dimensions, homographies and camera projections.
  • Use least squares estimation for solving various problems within the area of signal and image processing. This includes filter optimization, total least squares, eigenvalue and singular value problem, principal component analysis (PCA)
  • Use bases and frames to formulate signal transformations, for example, the wavelet transformation and filter banks.


Prerequisites: (valid for students admitted to programmes within which the course is offered)
Basic Linear Algebra: bases, scalar product, least squares problem, eigenvalue problems. Basic signal processing (corresponding to Linear Systems): sampling, convolution and Fourier transform of one-variable signals. Basic skills in Matlab is recommended.

Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding.
Supplementary courses:
Computer Vision Systems and Theory, Image and Audio Coding, Medical Image Analysis, Neural Networks and Learning Systems, Image Sensors
Organisation:
The course has approximately 10 lectures that present basic concepts and theory. These lead to a set of exercises where various computational tasks are solved using Matlab. The course runs over the entire autumn semester.
Course contents:
Signal spaces and signal bases, dual bases. Least squares problem, filteroptimering, normalized convolution. Eigenvalue and singular value analysis. Principal component analysis. Frames. Wavelet transform and filterbanks. Projective spaces, homogeneous coordinates, homographies, camera projections. Representation and estimation of 3D transformations.
Course literature:
Chapters in textbooks and articles that are presented at course start.
Examination:
Written examination
Laboratory work
 3 ECTS
3 ECTS
 


Course language is Swedish/English.
Department offering the course: ISY.
Director of Studies: Klas Nordberg
Examiner: Klas Nordberg
Link to the course homepage at the department


Course Syllabus in Swedish

Linköping Institute of Technology
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Contact: TFK , val@tfk.liu.se
Last updated: 06/11/2015