Laboratory of Information Processing 2

Course Description

Depending on the choice of theoretical courses the student will gain practical knowledge and hands-on experience in two out of four areas: formal methods in system design, communication signal processing, estimation theory and multimedia communications.

General Competencies

Formal methods in system design: Knowledge in theoretical foundations of formal design methods with practical procedures. Knowledge in tools for formal methods application to system design. Signal Processing in Communications: Skills in programming within Matlab environment. Ability to analyze, model and simulate behavior of data transmission systems. Practical knowledge about lower layers of communication systems. Estimation theory: Practical knowledge to make identification experiments on linear systems, select optimal model structure and to estimate the system model using Matlab System Identification Toolbox. Multimedia communications: Coding formats, content synchronization, quality of presentation, multiuser multimedia applications, quality of service in Internet.

Learning Outcomes

  1. match theoretical foundations of formal design methods with practical procedures
  2. analyze and classify results obtained by the application of tools for formal system verification
  3. develop various parts of communication systems, for example filters, Hilbert transformers, multipliers, decimators and interpolators, modulators and demodulators, frequency synthesizers
  4. develop behavioral model of software defined radio receiver in Matlab environment
  5. apply nonparametric and parametric methods for estimation of mathematical models of systems
  6. apply state estimators of stochastic systems with Gaussian distribution
  7. explain Voice over IP (VoIP) and network and application management protocols on
  8. create VoIP sessions following the given scenarios

Forms of Teaching





Laboratory Work


Experimental Exercises




Grading Method

By decision of the Faculty Council, in the academic year 2019/2020. the midterm exams are cancelled and the points assigned to that component are transferred to the final exam, unless the teachers have reassigned the points and the grading components differently. See the news for each course for information on knowledge rating.
Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Laboratory Exercises 0 % 50 % 0 % 0 %
Mid Term Exam: Written 0 % 25 % 0 %
Final Exam: Written 0 % 25 %

Week by Week Schedule

  1. Introduction.
  2. Formal Methods in System Design: Hardware verification (e.g. multiple request arbiter).
  3. Formal Methods in System Design: Formal verification of critical operating systems synchronization and communication protocols.
  4. Formal Methods in System Design: Formal verification of communication protocols in distributed systems.
  5. Communication signal processing: Analysis of continuous-time signals using discrete Fourier transform. Design of filters with real and complex coefficients. Design of Hilbert transformers. Generation of complex envelope of amplitude, phase and angle modulated signals.
  6. Communication signal processing: Modeling of analog transmission systems in Matlab environment. Modeling of software defined radio receivers in Matlab environment.
  7. Communication signal processing: Digital communication systems. Baseband transmission of pulses. Performance measuring of transmission systems.
  8. Midterm exam.
  9. Estimation theory: Nonparametric identification methods.
  10. Estimation theory: Parametric identification methods.
  11. Estimation theory: Estimation of the satellite position in the planar orbit around Earth.
  12. Multimedia communications: Analysis of VOIP session traffic.
  13. Multimedia communications: Analysis of user behaviors in networked virtual environments I.
  14. Multimedia communications: Analysis of user behaviors in networked virtual environments II.
  15. Final exam.

Study Programmes

University graduate
Information Processing (profile)
(2. semester)


Michael Huth, Mark Ryan (2004.), Logic in Computer Science, Cambridge University Press
Goran Molnar, Mladen Vučić (2009.), Obrada signala u komunikacijama - laboratorij profila, FER
Zoran Vukić, Ivan Petrović, Mario Vašak (2008.), Estimation Theory - Instructions for laboratory work, FER
Maja Matijašević, Željka Car (2011.), Lecture notes and recommended literature for the courses, FER
(2005.), MATLAB User Manual, The MathWorks Inc

Laboratory exercises


ID 35237
  Summer semester
L0 English Level
L1 e-Learning
15 Lectures
0 Exercises
30 Laboratory exercises
0 Project laboratory

Grading System

88 Excellent
75 Very Good
62 Good
50 Acceptable