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Coursebooks 2017-2018
Nonlinear signal modeling and prediction
EE-714
Lecturer(s) :
Vesin Jean-MarcLanguage:
English
Frequency
Every 2 yearsRemarque
Every 2 years. Next time: Spring 2018Summary
The literature on nonlinear signal processing has exploded, and it becomes more and more difficult to identify the most useful approaches for specific contexts. This course presents promising developments for the practical application of nonlinear signal models in various fields of engineering.Content
1. Introduction
2. Summary of linear AR and ARMA modeling
3. Nonlinear AR and ARMA modeling, polynomial models and their estimation
4. Specific nonlinear models (threshold AR, ...)
5. Neural network based modeling and prediction
6. Model selection
7. Chaos theory and applications
8. Kernel-based approaches
9. Laboratory exercises: application of nonlinear modeling/prediction to synthetic and experimental data
Keywords
Signal modeling, Signal prediction, Nonlinear autoregression, Parameter estimation.
Learning Prerequisites
Recommended courses
Statistical signal processing
Assessment methods
Multiple.
In the programs
- Semester
- Exam form
Multiple - Credits
4 - Subject examined
Nonlinear signal modeling and prediction - Lecture
28 Hour(s) - Exercises
28 Hour(s)
- Semester
Reference week
Lecture
Exercise, TP
Project, other
legend
- Autumn semester
- Winter sessions
- Spring semester
- Summer sessions
- Lecture in French
- Lecture in English
- Lecture in German