3 ECTS credits
90 h study time
Offer 1 with catalog number 4007427EER for all students in the 1st semester at a (E) Master - advanced level.
Goal: to give an intuitive insight in the behaviour of nonlinear systems. For that purpose we first provide the attendees with a theoretical framework that will be used next to develop a number of tools that can be easily used in practice to characterize nonlinear systems.
A theoretic framework
- Impact of the choice of excitation and the choice of convergence criterion
- Volterra representation of nonlinear systems
- Nonparametric representation of nonlinear systems
- Best linear approximation of nonlinear systems
- Stochastic nonlinear contributions
Practical applications
- Detection, qualification and quantification of nonlinear distortions.
- Measurement of transfer functions in the presence of nonlinear distortions.
- Measurement of Volterra kernels in time and frequency domain.
- Nonparametric measurement of nonlinear systems.
Course notes are made available during the lessons.
Goal: to give an intuitive insight in the behavior of nonlinear systems. For that purpose we first provide the attendees with a theoretical framework that will be used next to develop a number of tools that can be easily used in practice to characterize nonlinear systems.
The students understand the impact of the choice of the excitation and the convergence criterion: the students design a proper experiment. The choices are motivated from theoretical, practical, and application point of view.
The students can detect, qualify and quantify nonlinear distortions
The students use the Volterra representation of nonlinear systems as a general framework: the students can create a nonparametric representation of a nonlinear system. They understand the advantages and disadvantages of their choices. They can apply Volterra theory to analyse cascaded nonlinear systems, including the pre- and post-inverse.
The students can work with the best linear approximation of nonlinear systems: the students are able to apply linear modelling techniques in the presence of nonlinear distortions. They understand the impact of the nonlinear distortions on the properties of the framework using the concept of systematic and stochastic contributions.
The students are able to make initial choices to build nonparametric models using nonlinear state space or block oriented models.
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
3. the advanced methods and theories to schematize and model complex problems or processes
The Master in Engineering Sciences can
6. correctly report on research or design results in the form of a technical report or in the form of a scientific paper
9. work in an industrial environment with attention to safety, quality assurance, communication and reporting
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
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.
The final grade is composed based on the following categories:
Oral Exam determines 100% of the final mark.
Within the Oral Exam category, the following assignments need to be completed:
oral exam
This offer is part of the following study plans:
Master of Electronics and Information Technology Engineering: Standaard traject (only offered in Dutch)
Master of Photonics Engineering: On campus traject
Master of Photonics Engineering: Online/Digital traject
Master of Electrical Engineering: Standaard traject BRUFACE J