English

Not applicable.

It is required knowledge of the related mathematical basis, including the statistics and signal processing fundamentals.

 

The conditions for successful completion of the course are given in the annually updated decree of the course guarantor. Students will be evaluated by credit on the basis of gaining points from practice (max. 30 points, min. 15 points) and the final exam (max. 70 points, min. 35 points). Exercise points can be obtained by test in exercises (max. 15 points) and individual work (max. 15 points). The test consists of numerical or graphical examples and analysis of the data sets in MATLAB. The test cannot be repeated. Absence from the exam for serious reasons will be solved individually. The final exam can be obtained on the basis of written (max. 60 points) and oral (max. 10 points) part. The written final exam consists of two parts, a numerical part and a theoretical part, and covers the content of lectures and exercises.
The definition of controlled teaching and the method of its implementation is determined by the annually updated decree of the subject guarantor. Computer exercises are mandatory.

The aim of the course is to familiarize students with selected topics of mathematics, statistics and signal processing, which are needed for successive specialized courses. The course includes selected operations of linear algebra and matrix decomposition, theory of random variables and random processes, introduction to system reliability, detectors and signal detection, parameter estimation, Kalman filtering and Hilbert transform.

The graduate of the course is able to: (a) apply mathematical techniques related to selected areas of the field of study, (b) apply decision and detection theory, (c) estimate signal parameters and examine an estimation quality, (d) use general and Kalman filtering techniques in relevant areas signal processing, (e) apply the Hilbert transform to determine complex functions. 

Not applicable.

Not applicable.

BARKAT, M. Signal Detection and Estimation. 2nd ed. Norwood: Artech House, 2005. ISBN: 9781580530705 (EN)
MOON, T. K., STIRLING, W. C. Mathematical Methods and Algorithms for Signal Processing. New Jersey: Prentice Hall, 2000, ISBN: ‎978-0201361865 (EN)

HIPPENSTIEL, R. D. Detection Theory: Applications and Digital Signal Processing, 1st edition,CRC Press, 2001, ISBN: 9780849304347 (EN)