SubjectsSubjects(version: 965)
Course, academic year 2019/2020
  
Advanced Methods of Signal Processing - M402033
Title: Pokročilé metody zpracování signálů
Guaranteed by: Department of Analytical Chemistry (402)
Faculty: Faculty of Chemical Engineering
Actual: from 2019
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: unlimited / unlimited (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Level:  
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Kukal Jaromír doc. Ing. Ph.D.
Interchangeability : N402100
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 contain both general principles and real applications in analytical chemistry.
Last update: Kukal Jaromír (23.02.2018)
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: Pátková Vlasta (05.01.2018)
Syllabus -

1. General definition of continuous and discrete signal.

2. Signal sampling, Nyquist theorem, signal quantization.

3. Signal with random component and its properties.

4. Convolution in the cases of continuous and discrete signal, circular convolution.

5. Causal filtering vs smoothing of continuous and discrete signal, transfer function.

6. Definition and properties of continuous Fourier transform.

7. Definition and properties of discrete Fourier transform.

8. Continuous and discrete Hilbert transform.

9. Analytic signal and its advantages in Fourier domain.

10. Special filters I: Savitzky-Golay, motivation and properties in Fourier domain.

11. Special filters II: Wiener, motivation and properties in Fourier domain.

12. Special filters III: Kalmán, motivation and properties in Fourier domain.

13. Amplitude, frequency, and phase modulation.

14. Amplitude, frequency, and phase demodulation.

Last update: Kukal Jaromír (23.02.2018)
Learning resources -

None.

Last update: Pátková Vlasta (05.01.2018)
Learning outcomes -

Students will be able:

to solve tasks related to decoding 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: Kukal Jaromír (23.02.2018)
Registration requirements -

Mathematics

Physics

Last update: Kukal Jaromír (23.02.2018)
Teaching methods
Activity Credits Hours
Účast na přednáškách 1.1 30
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 0.4 10
Práce na individuálním projektu 0.7 20
Příprava na zkoušku a její absolvování 0.4 10
Účast na seminářích 0.9 26
4 / 5 96 / 140
Coursework assessment
Form Significance
Regular attendance 50
Defense of an individual project 30
Oral examination 20

 
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