6 ECTS credits
150 h study time

Offer 1 with catalog number 4016447ENR for all students in the 1st semester at a (E) Master - advanced level.

1st semester
Enrollment based on exam contract
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Taught in
Partnership Agreement
Under interuniversity agreement for degree program
Faculteit Ingenieurswetenschappen
Educational team
Leo Van Biesen
Ivan Markovsky (course titular)
Activities and contact hours
42 contact hours Lecture
18 contact hours Seminar, Exercises or Practicals
Course Content

1 From the telegraph to the internet
  - Telegraph
  - Landline telephone
  - Going digital
  - Communication media
  - The "last mile"
  - Mobile revolution
  - What is coming next?

2 Behavioral system theory
  - Kernel, image, and input/state/output representtions
  - Simulation, analysis and design problems
  - From data to models

3 Case study: noise filtering
  - Heuristic filtering methods
  - Optimal model-based filtering
  - Model-free filtering methods

4 Markov processes and queuing theory
  - Stochastic matrices and probability vectors
  - Multi-step transition process
  - Regular Markov chains and limiting distributions
  - Classification of states
  - Transient state analysis
  - The Google page rank algorithm

5 Information theory and coding
  - Convolutional codes
  - Trellis diagram
  - Viterbi decoding
  - Turbo coding/decoding
  - Applications

6 Navigation (Leo Van Biesen)
  - Introduction to geodesy and chart projection systems
  - GPS and differential GPS
  - GPS signals
  - GPS code measurement
  - Impact of atmosphere on GPS
  - Types of localization methods (TA, TOA, E-OTD, A-GPS)
  - GPS – Glonass – Galileo

Additional info

Slides, reading materials, and homework assignements will be posted during the semester at the course webpage: http://homepages.vub.ac.be/~imarkovs/vint

Learning Outcomes

Algemene competenties

This course contributes to the following generic learning outcomes of the Master in Electronics and Information Technology Engineering programme:
  - In-depth knowledge and understanding of the advanced methods and theories to schematize and model complex problems or processes.
  - Can correctly report on research or design results in the form of a technical report or in the form of a scientific paper.
  - Think critically about and evaluate projects, systems and processes, particularly when based on incomplete, contradictory and/or redundant information.
  - Has a creative, problem-solving, result-driven and evidence-based attitude, aiming at innovation and applicability in industry and society.
  - Has a profound knowledge of measuring, modelling and control.
  - Is able to analyze, specify, design, implement, test and evaluate individual electronic devices, components and algorithms, for signal-processing, communication and complex systems.
  - Is able to model, simulate, measure and control electronic components and physical phenomena.


The final grade is composed based on the following categories:
Oral Exam determines 70% of the final mark.
PRAC Lab Work determines 30% of the final mark.

Within the Oral Exam category, the following assignments need to be completed:

  • exam with a relative weight of 1 which comprises 70% of the final mark.

Within the PRAC Lab Work category, the following assignments need to be completed:

  • WPO werk with a relative weight of 1 which comprises 30% of the final mark.

Additional info regarding evaluation

The total mark is a weighted sum of the marks for part 1 (taught by Ivan Markovsky) and part 2 (taught by Leo Van Biesen). For part 1, 10 points are based on assignments (given in class) and 10 points on a mini-project (practical sessions). For part 2, the mark is 100% based an open book oral examination.

Allowed unsatisfactory mark
The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context

This offer is part of the following study plans:
Master in Applied Sciences and Engineering: Applied Computer Science: Standaard traject
Master of Applied Sciences and Engineering: Computer Science: Artificial Intelligence
Master of Applied Sciences and Engineering: Computer Science: Multimedia
Master of Applied Sciences and Engineering: Computer Science: Software Languages and Software Engineering
Master of Applied Sciences and Engineering: Computer Science: Data Management and Analytics
Master of Photonics Engineering: On campus traject
Master of Photonics Engineering: Online/Digital traject
Master of Electrical Engineering: Standaard traject BRUFACE J