česky  čs
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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.
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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