Course syllabus - Advanced Signal Processing
Scope
7.5 credits
Course code
ELA412
Valid from
Spring semester 2022
Education level
Second cycle
Progressive Specialisation
A1F (Second cycle, has second-cycle course/s as entry requirements).
Main area(s)
School
School of Innovation, Design and Engineering
Ratified
2020-12-15
Literature lists
Course literature is preliminary up to 8 weeks before course start. Course literature can be valid over several semesters.
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Books
Signals and systems
International ed of 2nd revised ed. : Harlow, Essex : Pearson Education Ltd., cop. 2014 - ii, 938 s.
ISBN: 9781292025902 LIBRIS-ID: 14912545
Bioelectromagnetism : principles and applications of bioelectric and biomagnetic fields
New York : Oxford University Press, 1995 - 1 online resource (xxii, 482 p.)
ISBN: 9780199847839 LIBRIS-ID: 12921754
Objectives
The purpose of the course is to provide students with knowledge, understanding and practical insight of different digital signal processing techniques and how these should be applied on common biosignals to extract features and obtain information.
Learning outcomes
After completing the course, the student should be able to:
1. explain the importance of digital signal processing and applications,
2. know different types of biosignals, their underlying mechanisms and relevant signal characteristics to extract,
3. demonstrate an understanding of random signal properties, as well as understanding of signal and spectrum estimation,
4. have a good understanding of advanced filter design principles and methods,
5. apply appropriate digital signal processing technique to reduce noise, remove artifacts and extract relevant information from measured signals,
6. critically evaluate effects and results from different signal processing techniques.
Course content
Common biosignals and their underlying mechanisms, advanced filter design, time-frequency analysis, spectral analysis of biosignals, blind-source separation techniques, identification and handling of different types of artifacts, noise reduction, random processes, power spectral density, pattern recognition and classification of extracted features, ethical aspects.
Specific requirements
Measurement technique 7.5 credits, Signal processing 7.5 credits, Probability and statistical theory 7.5 credits, Calculus I 7.5 credits, Linear algebra or Vector algebra 7.5 credits, or similar. In addition, Swedish course B/Swedish course 3 and English course A/English course 6 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 3.
Examination
Take-home examination (HEM1), 4,5 credits, examines the learning outcomes 1-4, marks Fail (U), 3, 4 or 5.
Project (PRO1), An assignment that is presented with a report and a demonstration of the project, 3 credits, examines the learning outcomes 2-6, marks Fail (U), 3, 4 or 5.
A student who has a certificate from MDU regarding a disability has the opportunity to submit a request for supportive measures during written examinations or other forms of examination, in accordance with the Rules and Regulations for Examinations at First-cycle and Second-cycle Level at Mälardalen University (2020/1655). It is the examiner who takes decisions on any supportive measures, based on what kind of certificate is issued, and in that case which measures are to be applied.
Suspicions of attempting to deceive in examinations (cheating) are reported to the Vice-Chancellor, in accordance with the Higher Education Ordinance, and are examined by the University’s Disciplinary Board. If the Disciplinary Board considers the student to be guilty of a disciplinary offence, the Board will take a decision on disciplinary action, which will be a warning or suspension.
Grade
Pass with distinction, Pass with credit, Pass, Fail
Interim Regulations and Other Regulations
The course completely overlaps with ELA409 Advanced Signal Processing.