SGN-25006 Vector Space Methods for Signal and Image Processing, 5 cr

Lisätiedot

Suitable for postgraduate studies.

Vastuuhenkilö

Alessandro Foi

Osaamistavoitteet

After completing this course, the student will - be able to model and solve signal processing problems through a wide range of vector-space methods - be able to extend the geometrical intuition from familiar 2D and 3D to very high-dimensional settings within a rigorous framework - be able to implement a wide range of fixed and adaptive signal transforms and understand their general properties - master the geometrical structures inherent to basic signal processing techniques, including color transforms, convolution filters, sliding window methods. - be able to design and implement consistent multi-dimensional differential operators for discrete signals - be analyze the propagation of signal distortions (e.g., noise) across transformations

Ohjeita opiskelijalle osaamisen tasojen saavuttamiseksi

Measures of learning: Exam and mandatory Matlab exercises/mini-project. The grade is determined by the exam and execution of the Matlab exercises/mini-project.

Arvosteluasteikko:

Numerical evaluation scale (0-5)

Oppimateriaali

Vastaavuudet

Opintojakso ei vastaan mitään toista opintojaksoa