| TSRT78 |
Digital Signal Processing, 6 ECTS credits.
/Digital signalbehandling/
For:
D
I
Ii
IT
M
MED
SY
U
Y
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Prel. scheduled
hours: 57
Rec. self-study hours: 103
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Area of Education: Technology
Main field of studies: Electrical Engineering
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Advancement level
(G1, G2, A): A
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Aim:
The student should after the course have the ability to describe the most important methods and algorithms for signal processing, and be able to apply these on signals of various kinds. More specifically, after the course the student should have the ability to
- Compute the discrete Fourier transform (DFT) and understand scaling effects and practical limitations implied by finite data length and sampling.
- Use the DFT for filtering and know how circular convolution is avoided.
- Explain the basic signal models and their relationship.
- Perform transform-based and model-based spectral analysis, and understand the compromise between resolution and noise suppression.
- Describe the theory for model estimation, and be able to apply algorithms for this purpose and validate an estimated model.
- Describe the basics in optimal filtering and be able to compute a Wiener filter for simple examples.
- Describe the premises for Kalman filtering, and be able to apply a Kalman filter to data and tune it to compromise tracking speed, transient behavior and noise suppression.
- Describe the most important adaptive filters, some common applications, and be able to apply and tune an adaptive filter to compromise parameter tracking speed and noise suppression.
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Prerequisites: (valid for students admitted to programmes within which the course is offered)
Signal Theory, Signals and Systems.
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.
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Supplementary courses:
Sensor fusion
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Organisation:
The course is organized in lectures/classes and laboratory work.
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Course contents:
Transforms of signals and systems, in particular the discrete Fourier transform.
Spectral analysis. Filter design. Modelling of signals. Filter design using statistical theory, Wiener and Kalman filters. Methods and applications in adaptive filtering, for example noise cancelling.
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Course literature:
Theory and excercise books published by Studentlitteratur (in Swedish)
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Examination: |
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Written examination
Laboratory work
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5 ECTS
1 ECTS
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Course language is English.
Department offering the course: ISY.
Director of Studies: Johan Löfberg
Examiner: Fredrik Gustafsson
Link to the course homepage at the department
Course Syllabus in Swedish
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