Syllabus Application
EE 672
System Identification
Faculty
Faculty of Engineering and Natural Sciences
Semester
Fall 2025-2026
Course
EE 672 -
System Identification
Time/Place
Time
Week Day
Place
Date
12:40-14:30
Mon
FENS-L058
Sep 29, 2025-Jan 3, 2026
11:40-12:30
Tue
FENS-L058
Sep 29, 2025-Jan 3, 2026
Level of course
Masters
Course Credits
SU Credit:3, ECTS:10
Prerequisites
-
Corequisites
-
Course Type
Lecture
Instructor(s) Information
Mustafa Ünel
- Email: munel@sabanciuniv.edu
Course Information
Catalog Course Description
Aims to provide the fundamental theory of identification of dynamical systems, i.e. how to use measured input-output data to build mathematical models, typically in terms of differential or difference equations. It covers: The mathematical foundations of System Identification, Non-parametric techniques, Parametrizations and model structures, Parameter estimation, Asymptotic statistical theory, User choices, Experimental design, Choice of model structure.
Course Learning Outcomes:
| 1. | - select inputs and outputs of a system, and characterize disturbances acting on the system. |
|---|---|
| 2. | - design suitable excitation signals, |
| 3. | - use measured input-output data to build mathematical models, |
| 4. | - solve linear regression problems by least squares methods, |
| 5. | - develop nonlinear NARX and Hammerstein-Wiener models |
| 6. | - preprocess data, |
| 7. | - validate obtained models |
Course Objective
Objective of the course is to provide graduate students with a strong background in linear and nonlinear system identification to build mathematical models from experimental data.
Sustainable Development Goals (SDGs) Related to This Course:
| Sustainable Cities and Communities |
Course Materials
Resources:
Textbook
System Identification, Theory for the User, 2nd Edition, Lennart Ljung, Prentice Hall, 1999.
Readings
System Identification, Karel J. Keesman, Springer-Verlag London Limited, 2011
Nonlinear System Identification, Oliver Nelles, Springer, 2001.
System Identification, Theory for the User, 2nd Edition, Lennart Ljung, Prentice Hall, 1999.
Readings
System Identification, Karel J. Keesman, Springer-Verlag London Limited, 2011
Nonlinear System Identification, Oliver Nelles, Springer, 2001.