Signal processing and system identification (E371096)
Departments:ústav přístrojové a řídící techniky (12110)
Abbreviation:ZSIApproved:11.06.2019
Valid until: ??Range:2P+2C
Semestr:*Credits:5
Completion:Z,ZKLanguage:EN
Annotation
Explanation of basic concepts relating to the processing and analysis of signals and their use to obtain a description of a deterministic or stochastic system for the purpose of automatic control. The experimental identification of systems that can be described by linear models is explained in more detail.
Teacher's
prof. Ing. Milan Hofreiter CSc.
Zimní 2021/2022
Structure
• Basic concepts of signal processing and system identification
• Analog and digital filters, classification and their implementation
• Linear time invariant continuous and discrete models
• Discretization, sampling, frequency properties, anti-aliasing filter
• Parametrization of step and frequency responses
• Concepts of probability theory and stochastic processes
• Characteristics of stochastic processes
• Continuous and discrete Fourier Transform
• Power spectrum, periodogram, white noise
• Identification of dynamic systems in the time domain (linear regression)
• Identification of dynamic systems in the frequency domain
• Time-discrete parametric stochastic models of signals and systems
• Kalman filter - optimal filtration based on the internal description of the system
Structure of tutorial
Literarture
• Hofreiter, M.: Identifikace systémů I, ČVUT v Praze, 2009, 202 s. ISBN 978-80-01-04228-1
• https://moodle.fs.cvut.cz/course/view.php?id=44
• E. W. Kamen and B. S. Heck: Fundamentals of Signals and Systems (2nd Edition), Prentice Hall, 2006
• L. Ljung: System Identification: Theory for the User (2nd Edition), Prentice Hall, 1999
• O. Alkin: Signals and Systems (1st Edition), Taylor & Francis Group, 2014
Requirements
Keywords
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