Signal Processing Course code: 317111 | 8 ECTS credits
Basic information
Level of Studies:
Year of Study:
1
Semester:
2
Requirements:
Goal:
Signal processing introduction. Principles of signal processing and practical applications.
Outcome:
Students can understand the principles and capabilities of signal processing and its visualization through practical examples and application possibilities.
Contents of the course
Theoretical instruction:
- Introduction.
- Signal processing history. Application examples.
- Signal visualization (Matlab, Python, Excel).
- Discrete complex exponential signal. Music signal synthesis.
- Fourier analysis. Discrete-time Fourier transforms (DTFT). Fast Fourier transforms. Application in spectral analysis and oscilloscopes.
- Linear filters. Convolution. Ideal and real filters. Filter design. Application of convolution in GPS systems.
- Interpolation and sampling. Continuous time signals. Sampling theorem. Processing continuous signals at discrete time. Simulink examples.
- Stochastic signal processing. Quantisation. Analog-to-digital converter (ADC) and digital-to-analog converter (DAC).
- Statistical signal processing. Application in communication systems.
- Two-Dimensional (2D) Fourier analysis, Image processing.
- Feature extraction from a signal. Speech recognition. Facial recognition.
- Signal representation, coding, and compression for transmission purposes.
- Digital communication systems, analog channels, bandwidth limits, frequency range, power, modulation and demodulation.
- Signal transmission by various analog and digital systems, signal conversions.
- Recapitulation of knowledge and final considerations.
Practical instruction (Problem solving sessions/Lab work/Practical training):
- Practical training program follows the lecture.
Textbooks and References
- Z. Dobrosavljević, Lj. Milić, Uvod u digitalnu obradu signala, Akademska misao, Beograd, 2009
- M. Popović, Digitalna obrada slike, Akademska misao, Beograd, 2006
- D. Manolakis, V. Ingle, Applied Digital Signal Processing, Theory and Practice, Cambridge University Press, 2011
- R. Lyons, Understanding Digital Signal Processing, Prentice Hall, 2004
- J. Guttag, Introduction to Computation and Programming Using Python, The MIT Press, 2013
Number of active classes (weekly)
Lectures:
4
Practical classes:
3
Other types of classes:
0
Grading (maximum number of points: 100)
Pre-exam obligations
Points
activities during lectures
10
activities on practial excersises
0
seminary work
20
colloquium
20
Final exam
Points
Written exam
20
Oral exam
30