4 ECTS credits
110 h study time

Offer 1 with catalog number 4019809ENR for all students in the 1st semester at a (E) Master - advanced level.

Semester
1st semester
Enrollment based on exam contract
Impossible
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Yes
Enrollment Requirements
Students of the Master in Electronics and Information Technology Engineering who want to register for this ‘Option package’ course must have successfully accomplished or must at least be registered for 30 ECTS of compulsory courses of the common core.
Taught in
English
Partnership Agreement
Under interuniversity agreement for degree program
Faculty
Faculty of Engineering
Department
Electricity
Educational team
John LATAIRE (course titular)
Activities and contact hours
24 contact hours Lecture
24 contact hours Seminar, Exercises or Practicals
Course Content

General goal of the course 

Engineers and scientists build models to understand, describe, predict and control the behaviour of the environment. In order to create these models it is necessary to combine the mathematical models with (noisy) measurements.  

In this advanced course, we will explore the consequences of having systems which do not satisfy the basic assumptions made when making frequency response function measurements. That is, we will learn how to deal with nonlinearities and time variations. 

Also, an introduction is given to the measurement of very high frequency signals and systems, and to the use of recursive identification techniques. In addition to a sound theoretical basis, we will also provide the students with hand on experiences in the labs.

 

Short outline 

  • Measuring high frequency signals and systems 

  • Taking into account time variations and nonlinear distortions 

  • Use of recursive identification, and the Kalman filter (state estimation) 

Study Material  

Lecture notes are available that cover the complete material, including the labs. 

Literature 

  • P. Eykhoff, System Identification, London, John Wiley and Sons, 1974. 

  • G.C. Goodwin and R.L. Payne, Dynamic System Identification. New York, Academic Press, 1977. 

  • L. Ljung, System Identification : theory for the user. Englewood Cliffs, Prentice-Hall, 1987.  

  • J. Schoukens and R. Pintelon, Identification of Linear Systems : A practical guideline for accurate modeling. London, Pergamon Press 1991.  

  • T. Soderstrom and P. Stoica, System Identification, Englewood Cliffs, Prentice-Hall, 1998.  

  • Oran E Brigham , The Fast Fourier Transform, Addison Wesley 

  • Pintelon and Schoukens, System Identification. A frequency domain approach. IEEE press, John Wiley, 2012.  

  • SchoukensPintelon, and Rolain.  Mastering system identification in 100 Exercises. IEEE press, John Wiley, 2012. 

  • Morrisson , Solving interference problems in electronics, Wiley

    Additional info

    Prior knowledge 

    • A basic knowledge of statistics is needed 

    • A basic knowledge of signals and systems theory is needed. Mainly, the Discrete and Continuous Fourier Transforms, the impulse response functions, and transfer functions are to be understood 

    • Measurements of Frequency response functions are understood and can be performed in practice 

    • A basic knowledge in system identification

      Learning Outcomes

      Algemene competenties

       

      General expectation 

      An independent problem solving and critical attitude are main skills for an engineer and are therefore mandatory for any item treated in this course. 

      Detailed outcomes 

      To successfully complete the course, you are expected to master theoretic concepts. 

      • Understand and explain the appearance of nonlinearities and time variations in engineering applications. 

      • Master basic tools to detect and quantify nonlinearities and time variations in measurements. 

      • Understand, explain and interpret analogue spectral measurements 

      Since for an engineer practical application of the material is crucial, you are also expected to 

      • Independently perform spectral measurements, assess the presence and correct the influence of problems where possible 

      • Independently design and realize a measurement on the hardware platform provided in the labs 

      • Apply the detection and quantification tools for nonlinear distortions and time variations 

      • Relate practical hardware settings and choices to the theoretic developed concepts 

      Factors that determine the judgement 

      • You are critical with respect to your explanations and results 

      • You solve simple, practical problems that are in direct relation to the course 

      • You fluently understand the hypotheses used in the theory and can indicate their importance. 

      • You show some practical measurement experience 

      • You express yourself in a clear, structured way, both in oral and written communication 

      We expect that you already have prior knowledge: the required background is taught in the course on measurement and identification. 

      This course contributes to the following programme outcomes of the Master in Electronics and Information Technology Engineering:

      The Master in Engineering Sciences has in-depth knowledge and understanding of
      1. exact sciences with the specificity of their application to engineering
      3. the advanced methods and theories to schematize and model complex problems or processes

      The Master in Engineering Sciences can
      4. reformulate complex engineering problems in order to solve them (simplifying assumptions, reducing complexity)
      6. correctly report on research or design results in the form of a technical report or in the form of a scientific paper
      8. collaborate in a (multidisciplinary) team
      9. work in an industrial environment with attention to safety, quality assurance, communication and reporting
      10. develop, plan, execute and manage engineering projects at the level of a starting professional
      11. think critically about and evaluate projects, systems and processes, particularly when based on incomplete, contradictory and/or redundant information

      The Master in Engineering Sciences has
      12. a creative, problem-solving, result-driven and evidence-based attitude, aiming at innovation and applicability in industry and society
      13. a critical attitude towards one’s own results and those of others
      16. an attitude of life-long learning as needed for the future development of his/her career

      The Master in Electronics and Information Technology Engineering:
      17. Has an active knowledge of the theory and applications of electronics, information and communication technology, from component up to system level.
      18. Has a profound knowledge of either (i) nano- and opto-electronics and embedded systems, (ii) information and communication technology systems or (iii) measuring, modelling and control.
      19. Has a broad overview of the role of electronics, informatics and telecommunications in industry, business and society.
      20. Is able to analyze, specify, design, implement, test and evaluate individual electronic devices, components and algorithms, for signal-processing, communication and complex systems.
      21. Is able to model, simulate, measure and control electronic components and physical phenomena.
       

      Grading

      The final grade is composed based on the following categories:
      Other Exam determines 100% of the final mark.

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

      • Exam with a relative weight of 1 which comprises 100% of the final mark.

      Additional info regarding evaluation

      Oral examination on the complete material. Emphasis is on the understanding of the material, just reproducing without understanding is not sufficient to succeed. 

      • 50 % of the score is on the theory 
      • 50 % of the score is on the lab 

      Important note: absence at one or more parts of the exam results in an "absence" evaluation for the whole course.

      Academic context

      This offer is part of the following study plans:
      Master of Electronics and Information Technology Engineering: Standaard traject (only offered in Dutch)
      European Master of Photonics: Standaard traject
      Master of Electrical Engineering: Standaard traject BRUFACE J