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Lecturer(s)
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Juryca Karel, Ing. Ph.D.
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Dobrovolný Martin, Ing. Ph.D.
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Doležel Petr, prof. Ing. Ph.D.
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Course content
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Lecture topics by week of the semester: 1. Signal quantization 2. Signal sampling 3. Signal aliasing 4. Fourier transform, extension to multiple dimensions, Signal spectrum, FFT 5. Signal filtering methods in the spatial/temporal and spectral domains 6. Principles of image information sensing. Analog and digital sensing elements. Analog image signal transmission 7. Principles of acoustic signal sensing 8. Sensors for the infrared region 9. Digital TV 10. Lossy and lossless compression algorithms 11. Spectrum of non-stationary signals 12. Wavelet transform 13. Wavelet transform - use for image compression The content of the exercises corresponds to the topics of the lectures.
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Laboratory work
- Contact teaching
- 24 hours per semester
- Term paper
- 40 hours per semester
- Home preparation for classes
- 52 hours per semester
- Preparation for a credit (assessment)
- 19 hours per semester
- Preparation for an exam
- 15 hours per semester
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Learning outcomes
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The course provides to students essential knowledge of data transmission theory and the principles of transmission and processing of audio and video signals. The understanding of these principles is necessary for the next study of communications systems in the next semesters.
After the course will student have the knowledges from the transmission and processing of audio and video signals area. The understanding of these principles is necessary for the next study of communications systems in the next semesters.
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Prerequisites
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The basic orientation in the MATLAB environment or any of the alternative products (SCILAB, OCTAVE...). The basic digital signal processing methods (the signal discretization, the spectrum of a signal, the one dimensional Fourier transformation). The basic matrix operations (for example the matrix inversion, transposition and multiplication). The capability of problems analysis and algorithm development.
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Assessment methods and criteria
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Oral examination, Written examination, Discussion
During the course, the student is required to participate in all exercises. During the semester, students are assigned a semester paper, the completion of which is a condition for granting credit. In the exam, the student will demonstrate active knowledge of the topics presented in the lectures.
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Recommended literature
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KUMAR, N. Suresh, Arun Kumar SANGAIAH, M. ARUN a S. ANAND. Advanced Image Processing Techniques and Applications. IGI Global. Advances in Computational Intelligence and Robotics, 2017. ISBN 9781522520535.
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Prchal, J. Šimák B. Digitální zpracování signálů v telekomunikacích. Praha: ČVUT, 2001. ISBN 80-01-02149-1.
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Sanjit K Mitra. Digital Signal Processing, 4th Edition. McGraw: Hill, 2010. ISBN 978-0073380490.
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