|Course Code :||2001WETDSB|
|Semester:||Semester: 2nd semester|
|Study load (hours):||168|
|Contract restrictions: ||No contract restriction|
|Language of instruction :||Dutch|
|Exam period:||exam in the 2nd semester|
Dirk Van Dyck
At the start of this course the student should have acquired the following competences:
- Competences corresponding the final attainment level of secondary school
An active knowlegde of :
Specific prerequisites for this course:
- General knowledge of the use of a PC and the Internet
A bachelor degree in sciences is required.
2. Learning outcomes
To impart knowledge and understanding of analysis of signals and systems when considered in the time and frequency domains, and to enable the student to formally analyse systems through the use of spectral analysis and correlations. The student will also be able to take account of the effects of sampling in the time and frequency domain and understand how these affect the practical analysis procedures. The students will be able to select the appropriate infinite or finite impulse response digital filter and undertake the design of the filter coefficients. The student should gain a familiarity with the derivation of the fast Fourier transform (FFT) algorithm and with its computational advantages. An appreciation of simple sample rate changes and their effect on the filter design process would also be expected.
A student should be able to:
Explain the relationships between and be able to manipulate time domain and frequency domain representations of signals.
Apply correlation techniques to an analytic or numerical problem, and relate the outcome to the properties of the signal source(s).
- recall how the discrete Fourier transform arises and recognise the effect of resolution and windowing functions upon the discrete Fourier transform;
- derive the structure of the fast Fourier transform from the equation of the discrete Fourier transform
- analyse the effects of downsampling and upsampling on a signal and recognise the importance of decimation and interpolation filtering.
3. Course contents
The digital signal processing course consists of the following chapters:
- signals and systems
- time domain description and convolution
- LTI system and its properties
- Fourier transformations
- Laplace transform
- Filter design
- wavelet transform
Next to the theory, theoretical as well as Matlab exercises will be given.
4. Teaching method
Class contact teaching: LecturesPractice sessionsLaboratory sessions
Personal work: Exercises
5. Assessment method and criteria
Examination: Oral with written preparationClosed bookOpen-question
6. Study material
Course notes and slides will be provided.
The following study material can be studied on a voluntary basis:
 P. Wambacq and H. Mannaert, “Handboek Signaalverwerking”, Uitgeverij ACCO, 1998.
 V. Madissetti and D. B. Williams, “Signal Processing Handbook”, IEEE Press, 1998.
 B. Mulgrew and P. Grant and J. Thompson, “Digital Signal Processing”, Palgrave Macmillan,
 R. Cristi, “Modern Digital Signal Processing”, Thomson Brooks/Cole, 2004.
 V. Ingle and J. Proakis, “Digital Signal Processing”, Thomson Brooks/Cole, 2000.
 A. V. Oppenheim and R. W. Schafer and J. R. Buck, “Discrete-time Signal Processing”,
Prentice-Hall, Second Ed., 1999.
 Zhi-Pei Liang and Paul Lauterbur, Principles of Magnetic Resonance Imaging: A Signal Processing Perspective, IEEE Press Series in Biomedical Engineering
7. Contact information
Prof. Dr. Jan Sijbers
Universiteitsplein 1, B-2610 Wilrijk, Belgium
Tel: +32 3 265 24 64 Fax: +32 3 265 22 45
(+)last update: 12/10/2012 18:19 jan.sijbers