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19E034OS2 - Signal Processing 2

Course specification
Course title Signal Processing 2
Acronym 19E034OS2
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
The goal Objective of the course is to teach students advanced signal processing techniques related to telecommunications and audios systems. The focus is on real-time frequency analysis, random signal analysis in time and frequency domains, multirate systems, adaptive filters and non-standard filter structures.
The outcome Students will be able to: -apply advanced DSP techniques in time and frequency domains suitable for solving practical problems -design simple multirate systems and digital filter banks -use MATLAB (MATLAB clone) in solving problems in telecommunications and audio systems -integrate theoretical concepts into the practical systems.
Contents
URL to the subject page http://telit.etf.rs/kurs/obrada-signala-2/
Contents of lectures Real-time spectrum analysis; discrete random signals, finite word-length effects; basic concepts of hardware platforms DSP processors and FPGA chips; multirate signal processing; digital filter banks; variable filters; digital analytical signals and Hilbert transformers; adaptive filters; analysis and processing in MATLAB (MATLAB clone) and dedicated DSP hardware.
Contents of exercises Analysis and synthesis of advanced signal processing algorithms in MATLAB (MATLAB clone) environment.
Literature
  1. Lj. Milić: Multirate Filtering for Digital Signal Processing, IGI global, 2009 (Original title)
  2. S. Mitra: Digital Signal processing: A Computer Based Approach, Mc Graw Hill, 2006 (Original title)
  3. J. Ćertić, Lj. Milić: Selected topics in digital signal processing - lecture notes
Number of hours per week during the semester/trimester/year
Lectures Exercises OTC Study and Research Other classes
2 2 1
Methods of teaching lectures, exercises, laboratory exercises, homework
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures Test paper
Practical lessons Oral examination 30
Projects 30
Colloquia 40
Seminars