SubjectsSubjects(version: 965)
Course, academic year 2019/2020
  
Advanced Methods of Signal Processing - N402100
Title: Pokročilé metody zpracování signálů
Guaranteed by: Department of Analytical Chemistry (402)
Faculty: Faculty of Chemical Engineering
Actual: from 2019 to 2020
Semester: winter
Points: winter s.:5
E-Credits: winter s.:5
Examination process: winter s.:
Hours per week, examination: winter s.:2/2, C+Ex [HT]
Capacity: unknown / unknown (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Level:  
Is provided by: M402033
Guarantor: Kukal Jaromír doc. Ing. Ph.D.
Is interchangeable with: M402033
Examination dates   Schedule   
Annotation -
The lecture will acquaint students with advanced mathematical methods of signal processing, with advanced methods of filtering, anti-aliasing, modulation and demodulation. The lecture will also contain links to work with the hardware for the management of experiments and the foundations of control experiments.
Last update: VED402 (04.10.2013)
Literature -

R: Steven W. Smith: The Scientist and Engineer's Guide to Digital Signal Processing, ISBN-10: 0966017633

R: Steven Kay: Fundamentals of Statistical Signal Processing � Estimation theory, Prentice Hall; 1 edition (April 5, 1993), ISBN-10: 0133457117

R: Steven Kay: Fundamentals of Statistical Signal Processing � Detection theory, Prentice Hall; 1 edition (February 6, 1998), ISBN-10: 013504135X

R: Monson Hayes: Statistical digital signal processing and modeling, Wiley; 1 edition (April 11, 1996), ISBN-10: 0471594318

A: Jan. J.: Číslicová filtrace, analýza a restaurace signálů, VUT v Brně, 1997

Last update: VED402 (04.10.2013)
Syllabus -

1. The general formulation of the signal and noise.

2. Stochastic signal.

3. Noise.

3. The modulation signal (amplitude, frequency, phase).

4. Demodulation of the signal.

5. Signal digitization, sampling.

6. Convolution.

7. Discrete Fourier transform.

8. Application of DFT.

9. Properties of DFT.

10. Signal filtering(Wiener filter, Kalmán filter, etc.).

11. Signal smoothing.

12. Signal synthesis.

13. Regression-linear and non-linear.

14. oftware and hardware management experiments.

Last update: VED402 (04.10.2013)
Learning resources -

None.

Last update: VED402 (04.10.2013)
Learning outcomes -

Students will be able:

to solve tasks related to decrypting of electronic information, which is the result of experimental activity. They will be able to design and create the numeric filters, they will be able to override or remove noise and they will be proficient in the use of simple or multiple modulation techniques. Numerical processing of experiments, including simulations, deconvolutions, etc.

Last update: VED402 (16.12.2013)
Registration requirements -

Mathematics

Physics

Last update: VED402 (04.10.2013)
Teaching methods
Activity Credits Hours
Účast na přednáškách 1 28
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 1 28
Příprava na zkoušku a její absolvování 2 56
Účast na seminářích 1 28
5 / 5 140 / 140
Coursework assessment
Form Significance
Defense of an individual project 20
Examination test 30
Oral examination 50

 
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