Course: Advanced signal processing methods

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Course title Advanced signal processing methods
Course code KE/IDSZS
Organizational form of instruction no contact
Level of course Doctoral
Year of study not specified
Semester Winter and summer
Number of ECTS credits 0
Language of instruction Czech, English
Status of course Optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Filip Aleš, doc. Ing. CSc.
Course content
The content of the course are the following chapters: Random signals - characteristics of random signals in time and frequency domain. Estimates of random and nenáhodných parameters. Cramer-Raova limit. Formalized filtering and restoration of signals. Wiener filtering for continuous and discrete time. Kalman filtering for continuous and discrete time, its use for modeling system Adaptive filtering and identification. Adaptive filtering algorithms. Parametric methods of signal processing. Time-frequency analysis, wavelet transform - a principle used for processing and compression of signals. Multidimensional signals and spectra, selected integral transformation (Hadamard, Walsh, Haar wavelet transform and 2D). Nonparametric methods for signal processing - analysis of eigenvalues and vectors of correlation matrices, the signal degradation and noise subspace, the chosen methods. Selected applications - identifying the direction of arrival of signals, frequency analysis with high resolution.

Learning activities and teaching methods
Monologic (reading, lecture, briefing)
Learning outcomes
The aim of the course is to acquaint students with modern methods of signal processing.
Advanced Signal Processing
Prerequisites
Advanced Signal Processing

Assessment methods and criteria
Oral examination, Written examination

Exam prerequisites: Attendance at seminar Submitting Protocols of exercises and teacher approval Submitting the results of computer exercises and teacher approval Test conditions The test consists of written and oral.
Recommended literature
  • CASTLEMAN K. R.:. Digital Image Processing. Prentice-Hall, New Jersey, USA, 1996.
  • KAY, S. M.:. Fundamentals of Statistical Signal Processing - Detection Theory. Prentice Hall, 1993.
  • KAY, S. M.:. Fundamentals of Statistical Signal Processing - Estimation Theory. Prentice Hall, 1993.
  • KAY, S. M.:. Modern Spectral Estimation: Theory and Application.. EngleWood Cliffs, New Jersey: Prentice-Hall, 1988.
  • MADISETTI, V. K., WILLIAMS, D. B. (ed.):. The Digital Signal Processing Handbook. USA, CRC & IEEE Press,, 1998.
  • MARPLE, S. L, Jr.:. Digital spectral analysis with applications.. Englewood Cliffs, Prentice-Hall, Inc., New York, 1987.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Information, Communication and Control Technologies (2013) Category: Electrical engineering, telecommunication and IT - Recommended year of study:-, Recommended semester: -
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Information, Communication and Control Technologies (2013) Category: Electrical engineering, telecommunication and IT - Recommended year of study:-, Recommended semester: -
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Information, Communication and Control Technologies (2013) Category: Electrical engineering, telecommunication and IT - Recommended year of study:-, Recommended semester: -
Faculty: Faculty of Electrical Engineering and Informatics Study plan (Version): Information, Communication and Control Technologies (2013) Category: Electrical engineering, telecommunication and IT - Recommended year of study:-, Recommended semester: -