Faculty of Engineering and Natural Sciences
Department of Electrical and Electronic Engineering

Code Name Level Year Semester
EEE 334 Digital Signal Processing Undergraduate 3 Fall
Status Number of ECTS Credits Class Hours Per Week Total Hours Per Semester Language
Area Elective 5 2 + 2 120 English

Instructor Assistant Coordinator
Jasmin Kevrić, Assist. Prof. Dr. Jasmin Kevrić, Assist. Prof. Dr.
[email protected] no email

The aim of this course is to provide fundamental concepts in digital signals and systems, as an introduction to advance digital signal processing. Digital signal processing represents a base upon which various engineering systems are build, including communication systems, image processing, speech processing, consumer electronics, and data processing. This course aims at preparing the student for basic DSP activities, focusing mostly on digital filter design, providing a solid ground for upgrade and work on practical DSP devices, as well as general purpose hardware in role of DSP

  1. Sampling Theory
  2. Sampling Theory
  3. Discrete-Time S&S
  4. Discrete-Time S&S
  5. The Z-Transform
  6. The Z-Transform
  7. Midterm Review
  8. M I D T E R M E X A M
  9. Fourier Analysis of Discrete-Time S&S
  10. Fourier Analysis of Discrete-Time S&S
  11. Design of Discrete Filters
  12. Design of Discrete Filters
  13. Applications
  14. Applications
  15. Final Review


    • Interactive Lectures
    • Practical Sessions
    • Excersises
    • Problem solving
    Description (%)
    Method Quantity Percentage (%)
    Midterm Exam(s)135
    Final Exam140
    Total: 100
    Learning outcomes
    • Describe the properties of discrete LTI systems;
    • Understand mathematical descriptions and representations of discreet signals and systems and draw parallel with continuous time signals and systems
    • Understand how to sample the continuous time signal at hand;
    • Familiarize with the idea of representing discrete time signals and LTI systems in the Z domain;
    • Familiarize with the idea of representing discrete time signals and LTI systems in the frequency domain;
    • Understand spectral representation of signals via DTFT, DFT, and FFT, and their properties and applications;
    • Ability to solve difference equations;
    • Ability to design digital filters;
    • Luis F. Chaparro, “Signals and Systems using MATLAB”, Academic Press, 2010

    ECTS (Allocated based on student) WORKLOAD
    Activities Quantity Duration (Hour) Total Work Load
    Lecture (14 weeks x Lecture hours per week)14228
    Laboratory / Practice (14 weeks x Laboratory/Practice hours per week)14228
    Midterm Examination (1 week)122
    Final Examination(1 week)122
    Preparation for Midterm Examination11515
    Preparation for Final Examination12525
    Assignment / Homework/ Project10220
    Seminar / Presentation 0
    Total Workload: 120
    ECTS Credit (Total workload/25): 5