Navigation

13E033OS2 - Signal Processing 2

Course specification
Course title Signal Processing 2
Acronym 13E033OS2
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 Signals and systems, Telecommunications 1
The goal Objective of the course is to present advanced signal processing techniques. The focus is on random signal analysis in time and frequency domains, analysis of finite worldlength effects, multirate systems and filter banks.
The outcome Students will learn advanced techniques for spectrum analysis suitable for solving of practical problems. They will learn basics of multirate signal processing and digital filter banks. They will be trained to use MATLAB (MATLAB clone) in solving practical problems related to telecommunications and processing of audio signals. They will learn how to use one evaluation DSP module.
Contents
URL to the subject page http://telit.etf.rs/kurs/obrada-signala-2/
URL to lectures https://teams.microsoft.com/l/team/19%3a4GawC0cw8ExnZmGyvPcmqpXJKgDKf8tkZcUNw7qGukQ1%40thread.tacv2/conversations?groupId=cc400782-f8ee-4f36-ae73-1197a384e3f2&tenantId=1774ef2e-9c62-478a-8d3a-fd2a495547ba
Contents of lectures Discrete random signals, analysis of finite wordlength effects, DSP processor fundamentals, development tools, multirate digital signal processing, digital filter banks, applications of digital signal processing, discrete analytic signal and discrete Hilbert transformer, adaptive filters, analysis and processing of signal using software MATLAB and evaluation DSP modules.
Contents of exercises Algorithms analysis and synthesis in MATLAB (MATLAB clone). Programing of DSP processor (evaluation board).
Literature
  1. Introduction to Digital Signal Processing (in Serbian), Lj. Milić i Z. Dobrosavljević, Publisher: Akademska misao, Belgrade, 2004
  2. Digital Signal Processing, M. Popović, Nauka, 1994.
  3. Digital Signal processing: A Computer Based Approach, S. Mitra, Mc Graw Hill, 2006.
  4. Digital Signal Processing: Principles, Algorithms, and Applications, J. Proakis, D. Manolakis, Prentice Hall, 1996
  5. Discrete-Time Signal Processing, A. Oppenheim and R. Schaffer, Prentice Hall, 1976.
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, laboratory exercises
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures 0 Test paper 0
Practical lessons 0 Oral examination 30
Projects
Colloquia 30
Seminars 40