čs en |

Signal processing and system identification (E371096)

Departments: | ústav přístrojové a řídící techniky (12110) | ||

Abbreviation: | ZSI | Approved: | 11.06.2019 |

Valid until: | ?? | Range: | 2P+2C |

Semestr: | * | Credits: | 5 |

Completion: | Z,ZK | Language: | 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

• 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

• 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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