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13E033OS1 - Signal Processing 1

Course specification
Course title Signal Processing 1
Acronym 13E033OS1
Study programme Electrical Engineering and Computing
Module
Type of study bachelor academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB 6.0 Status mandatory
Condition Siganls and systems, Telecommunications 1
The goal Objective of the course is to present basic signal processing techniques. The focus is on signal analysis in time and frequency domains, ideal and real system for digital processing of continuous-time signals, spectrum analysis and fundamental FIR and IIR filter design and realization.
The outcome Student will be able to understand basic concept related to digital signal processing. They will learn basic techniques for spectrum analysis of digital signals. They will be trained to design basic types of FIR and IIR digital filters. They will be trained to use MATLAB (MATLAB clone) in solving simple problems of spectrum analysis and digital filter design and analysis.
Contents
Contents of lectures Analysis of discrete signals in time and frequency domains, analysis of discrete systems by Fourier and Z transform, ideal and real system for digital processing of continuous-time signals, discrete Fourier Transform (DFT), Fast Fourier Transform (FFT), properties of linear time invariant systems, FIR and IIR filters design, digital filter realizations, introduction to multirate systems.
Contents of exercises Software implementation in MATLAB
Literature
  1. Lj. Milić, Z. Dobrosavljević: Introduction to Signal Processing (in Serbian), Akademska misao, Belgrade
  2. Digital Signal processing: A Computer Based Approach, S. Mitra, Mc Graw Hill, 2006.
  3. Digital Signal Processing: Principles, Algorithms, and Applications, J. Proakis and D. Manolakis, Prentice Hall, 1996.
Number of hours per week during the semester/trimester/year
Lectures Exercises OTC Study and Research Other classes
3 1 1
Methods of teaching lectures, exercises, labaratory exercises, homeworks
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures 0 Test paper 50
Practical lessons 20 Oral examination 0
Projects
Colloquia 30
Seminars 0