4 ECTS credits
110 h study time
Offer 1 with catalog number 4013754ENR for all students in the 1st semester at a (E) Master - advanced level.
The aim of the course is to cover in depth major topics in digital signal processing and present their latest applications in various fields, ranging from image/video acquisition to signal processing for finance and the internet of things. The course content primarily focuses on the following topics:
Efficient computations of the discrete Fourier transform and its applications in filtering long data sequences.
Structures for the realization of discrete–time systems, including direct-form, cascaded-form and lattice structures, as well as digital filter design.
Digital signal acquisition systems including A/D and D/A conversion methods, quantization and coding, analysis of quantization errors, oversampling A/D and D/A conversion.
Multirate digital signal processing, including decimation, interpolation, and sampling rate conversion.
Sparse signal processing, including compressed sensing, sparse signal reconstruction, and applications in imaging and big data acquisition.
The goal of this course is to introduce the fundamental concepts, methods, and technologies relevant for the design of digital signal processing pipelines with emphasis on the latest applications. The students will have the opportunity to follow a set of lectures and to implement the concepts during lab sessions in Matlab.
-aims and objectives :
This course is intended as an introductory course. It's goal is to show the most essential theoretical concepts involved, as well as practical applicability such as to give the student a good feeling for practical use of digital signal processing.
-exam requirements :
Students should know and understand the basic theoretic concepts and be prepared for practical use of digital signal processing. The material described in the theoretical part and it's use in the practical sessions constitute the requirements for the theoretical and practical exams, respectively.
This course contributes to the following programme outcomes of the Master in Electronics and Information Technology Engineering:
The Master in Engineering Sciences has in-depth knowledge and understanding of
2. integrated structural design methods in the framework of a global design strategy
The Master in Engineering Sciences can
4. reformulate complex engineering problems in order to solve them (simplifying assumptions, reducing complexity)
The Master in Engineering Sciences has
15. the flexibility and adaptability to work in an international and/or intercultural context
16. an attitude of life-long learning as needed for the future development of his/her career
The Master in Electronics and Information Technology Engineering:
17. Has an active knowledge of the theory and applications of electronics, information and communication technology, from component up to system level.
18. Has a profound knowledge of either (i) nano- and opto-electronics and embedded systems, (ii) information and communication technology systems or (iii) measuring, modelling and control.
20. Is able to analyze, specify, design, implement, test and evaluate individual electronic devices, components and algorithms, for signal-processing, communication and complex systems.
21. Is able to model, simulate, measure and control electronic components and physical phenomena.
The final grade is composed based on the following categories:
Other Exam determines 100% of the final mark.
Within the Other Exam category, the following assignments need to be completed:
The final theory exam is a written evaluation, where the students address theoretical questions as well as questions related to filter and algorithmic design.
The practical exam is a coding evaluation, which examines the students’ involvement in the seminar sessions, evaluates their in-depth understanding, and assesses their practical skills in solving signal processing problems.
The final grade is composed based on the following examinations: (1) the result of the final theory exam, which determines 70% of the final mark; and (2) the result of the final practical exam, which determines 30% of the final mark.
This offer is part of the following study plans:
Master of Electronics and Information Technology Engineering: Standaard traject (only offered in Dutch)
Master of Applied Sciences and Engineering: Computer Science: Artificial Intelligence
Master of Applied Sciences and Engineering: Computer Science: Multimedia
Master of Applied Sciences and Engineering: Computer Science: Software Languages and Software Engineering
Master of Applied Sciences and Engineering: Computer Science: Data Management and Analytics
Master of Electrical Engineering: Standaard traject BRUFACE J