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Course info
KKY / ZSI
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Course description
Department/Unit / Abbreviation
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KKY
/
ZSI
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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Title
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Signal processing
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Form of course completion
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Exam
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Form of course completion
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Exam
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Accredited / Credits
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Yes,
6
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
3
[Hours/Week]
Tutorial
2
[Hours/Week]
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Course credit prior to examination
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Yes
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Course credit prior to examination
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Yes
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Included in study average
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YES
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Language of instruction
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Czech
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Occ/max
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Summer semester
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24 / -
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0 / -
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1 / -
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Included in study average
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YES
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Winter semester
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0 / -
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0 / -
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0 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Summer semester
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Semester taught
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Summer semester
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Minimum (B + C) students
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10
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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Czech
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
1|2|3|4 |
Periodicity |
každý rok
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Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
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Fundamental theoretical course |
Yes
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Fundamental course |
No
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Fundamental theoretical course |
Yes
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Evaluation scale |
1|2|3|4 |
Evaluation scale for credit before examination |
S|N |
Substituted course
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None
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Preclusive courses
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N/A
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Prerequisite courses
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N/A
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Informally recommended courses
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N/A
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Courses depending on this Course
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KKY/AKSZ, KKY/ROSZ, KKY/SZKUI
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Histogram of students' grades over the years:
Graphic PNG
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XLS
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Course objectives:
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The goal of the course is to familiarize students with basic of information theory and methods of signal processing in both the time and also in the frequency domain.
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Requirements on student
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Understanding the basic principles and methods in computer signal processing. Coming to the exam will be conditioned by elaborating individual practical tasks from the area of signal processing. The exam will contain both written (test) and oral parts.
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Content
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The signal properties, sampling and quantization of signal, Shannon sampling theorem, signal reconstruction. Information theory, channel coding, entropy. Z-transform, Fourier analysis of continuous and discrete-time signals, convolution and correlation, discrete Fourier transform, fast algorithms for the Fourier transform evaluation, Hartley transform, Cosine transform, interpolation of the signal, filters with finite and infinite response and their design, noise and signal distortion, signal enhancement method in noise, the scaling of stochastic time-frequency domain, homomorphic signal processing, cepstral analysis, correlation analysis of signals, time-frequency signal analysis, the uncertainty principle Wavelet transform, Wigner-Villeova distribution, instantaneous frequency, analytic signal, Hilbert transform, empirical modal decomposition and Hilbert-Huang transform, order analysis - Vold-Kalman filter, full spectrum and identification of precession.
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Activities
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Fields of study
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Guarantors and lecturers
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Guarantors:
doc. Ing. Mgr. Josef Psutka, Ph.D. (100%),
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Lecturer:
Ing. Jindřich Liška, Ph.D. (100%),
doc. Ing. Mgr. Josef Psutka, Ph.D. (100%),
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Tutorial lecturer:
Ing. Jindřich Liška, Ph.D. (100%),
doc. Ing. Mgr. Josef Psutka, Ph.D. (100%),
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Literature
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Presentation preparation (report) (1-10)
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5
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Practical training (number of hours)
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26
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Preparation for an examination (30-60)
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45
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Individual project (40)
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40
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Contact hours
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39
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Total
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155
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
ovládat základy matematické analýzy |
orientovat se v lineálních systémech |
algoritmizovat |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
dekomponovat úlohu na subúlohy |
pracovat s lineárními časově invariantními systémy |
aplikovat znalosti z matematické analýzy |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
vysvětlit zpracování signálů spojitých a disktrétních v čase |
formulovat úlohu převodu signálu do spektra a zpět |
vysvětlit principy filtrace signálu |
interpretovat časo-frekvenční analýzu signálu |
vysvětlit úplné spektrum a řádovou analýzu |
Skills - skills resulting from the course: |
převést navzorkovaný signál do spektra |
navrhnout a realizovat FIR a IIR filtry |
provádět kepstrální analýzu |
realizovat časo-frekvenční analýzu |
odhadnout úplné spektrum a identifikovat precesi |
Competences - competences resulting from the course: |
N/A |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Combined exam |
Skills - skills achieved by taking this course are verified by the following means: |
Seminar work |
Competences - competence achieved by taking this course are verified by the following means: |
Combined exam |
Seminar work |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture with visual aids |
Lecture supplemented with a discussion |
One-to-One tutorial |
Skills - the following training methods are used to achieve the required skills: |
Practicum |
Individual study |
Competences - the following training methods are used to achieve the required competences: |
Lecture supplemented with a discussion |
Task-based study method |
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