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Main menu for Browse IS/STAG
Course info
KEI / CZS
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Course description
Department/Unit / Abbreviation
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KEI
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CZS
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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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Digital 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, English
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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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0 / -
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0 / -
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0 / -
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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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Winter semester
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Semester taught
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Winter 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, English
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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 |
No
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Fundamental course |
Yes
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Fundamental theoretical course |
No
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Evaluation scale |
1|2|3|4 |
Evaluation scale for credit before examination |
S|N |
Substituted course
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KAE/CZS
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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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N/A
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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 aim of this study subject is to familiarise students with principles of Digital Signal Processing of signals. Student will learn about discretization of continouous signals, sampling, quanization and coding. More the differences between discrete and analogue signal will be explained. After introduction to the signals, the introduction to discrete digital systems follows. An LTI system is defined, explained, students learns its characteristics, such as linearity, time-invariance, stability, causality, etc. After the system is defined, the theory of discrete filters follows. Student learns about NRDF/RDF filter design, its description and implementation
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Requirements on student
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Laboratory Credits: Attend the labs, lab reports.
Exam requirements: consists of two parts - written part and oral exams.
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Content
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Content of Lectures
1. Introduction, literature, Why DSP, history of electrical engineering- briefly, Signals, definition of signals, classes, advantages/disadvantages of DSP
2. Basic signals used in DSP, energy and power of sequences, periodicity of discrete signals, complex exponential + harmonically bounded complex exponentials, data sequences represented by delta function
3. Definition of LTI system, Linearity, Time-Invariance, Input - output relations of LTI systems, convolution, correlation (auto/cross), Stability, Causality of LTI systems.
4. Time-domain description of LTI system, Difference equation, Impulse response. Frequency-domain description of LTI system, frequency characteristic, system function, Z-transformation
5. ROC (Region of Convergence of Z-transformation), System function, roots of nominator/denominator, poles/zeros of system and its influence on the frequency behavior of the system, ROC (Region of Convergence of Z-transformation)
6. Analog Front-End: Sampling definition, sampling theorem, aliasing in time/frequency domains, Anti Aliasing Filters (AAF), over-sampling, under-sampling, AAF filter design examples, example of AAF filter used in phone line networks, Sigma-Delta ADC, real sampling, errors of ADCs, aperture and sampling jitters, SNR, ENOB, SINAD
7. Analog Front-End: interpolation, signal reconstruction, DACs, impulse and frequency responses of DACs, sinc(x), interpolation filters design. Quantization, coding of data, data representation in memory, computing errors, rounding, ceiling
8. Limit cycles, non-linearity founded in digital systems: saturation/over-flow, statistical model of quantizer, SNR calculations, noise of digital systems.
9. Non-Recursive Digital Filters (NRDF): description, phase linearity phenomenon, impulse responses of NRDF filters - FIR, design of NRDF filters, examples, windowing methods, Gibbs oscillations, equiripple design
10. Recursive Digital Filters (RDF) description, phase non-linearity, impulse response of RDF filters - IIR/FIR, design of RDF filters, transformation H(p)-H(z), bilinear and impulse-invariance transformations, design examples
11. Implementation structures of digital filters, structures suitable for NRDF/RDF filters, advanced structures, dual structures, structure?s transposition.
Discrete unitary transformations (DUT), kernel of transformations, base vectors, DFT matrix and linear equation forms, deep insight to the theory and understanding, fast-convolution method description.
12. Fast Fourier Transformation - FFT, principles, DIT/DIF FFT, algorithm in-place, bit-reverse. IFFT.
Spectrum analyses - rank of transformation, frequency step and resolution, zero-padding, leakage, input data windowing
13. Multi-rate Digital Signal Processing, re-sampling, interpolation/decimation. Applications: Digital Voice Recorder, Digital Harmonic Oscillators, Goertzel Algorithm.
Content of Laboratory Tasks
1. Basic signals used in DSP processing
2. Correlation, Convolution
3. Description and Analyzing of System in Time-Domain
4. Zeros and Poles of the System ? Analyzing of System in Frequency-Domain
5. Voice Signal Processing and Filter Design - using Simulink / Matlab
6. Sampling and Reconstruction of Analogue Signals ? ADC, DAC using Matlab
7. Data representation in processors ? fix / float arithmetic examples
8. Windowing method used in DSP
9. Design of NRDF/FIR filters on Motorola 68HC16Z1 EVB
10. Design of RDF/IIR filters on Motorola 68HC16Z1 EVB
11. Design of NRDF/FIR filters on Texas Instruments DSP 320C5xx EVB
12. Design of digital oscillators on Texas Instruments DSP 320C5xx EVB
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Activities
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Fields of study
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Guarantors and lecturers
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Literature
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Recommended:
Jan, Jiří. Číslicová filtrace, analýza a restaurace signálů. 2., upr. a rozš. vyd. V Brně : VUTIUM, 2002. ISBN 80-214-1558-4.
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Recommended:
Davídek, Vratislav; Sovka, Pavel. Číslicové zpracování signálů a implementace. Praha : Vydavatelství ČVUT, 2002. ISBN 80-01-02483-0.
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Recommended:
The Scientist and Engineer's Guide To Digital Signal Processing, Second Edition
(Smith, W. Steven)
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Recommended:
Sedláček, Miloš. Zpracování signálu v měřící technice. dotisk 1. vyd. Praha : ČVUT, 1996. ISBN 80-01-00900-9.
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On-line library catalogues
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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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Contact hours
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39
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Practical training (number of hours)
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26
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Graduate study programme term essay (40-50)
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40
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Preparation for an examination (30-60)
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35
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Preparation for laboratory testing; outcome analysis (1-8)
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24
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Total
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164
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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: |
rozdíl mezi analogovým a číslicovým zpracováním signálů, výhody číslicového zpracování signálů - přesnost, rychlost, opakovatelnost |
přehled základních signálů používaných v číslicovém zpracování signálů (CZS) a jejich parametry |
energie a výkon signálu, diskrétní signál jako posloupnost dat |
způsob nesení informace (amplituda, fáze, kmitočet) v diskrétním signálu |
základní operace s posloupnostmi |
definice a přehled číslicových systémů |
definice lineárního impulsně invariantního systému (LTI systému) |
relace vstupu a výstupu LTI systému - konvoluce |
stabilita a kauzalita LTI systému |
korelační analýza |
prostředky popisu LTI sytstémů v časové a frekvenční oblasti, přechod mezi časovou a frekvenční oblastí pro diskrétní posloupnosti - DTFT |
impulsní odezva a diferenční rovnice LTI diskrétního (LTID) systému |
frekvenční odezva a systémová funkce LTID systému, Z- transformace |
vzorkování, vzorkovací teorém, aliasing, AAF filtry, převzorkování, ideální a skutečné vzorkování, jittery, SNR, SINAD, ENOB |
rekonstrukce signálu - ideální a skutečný rekonstruktor, analogové rekonstukční filtry a jejich provedení, vlastnosti funkce sinc() |
kvantování a kódování signálu, způsob reprezentace dat v paměti, chyby a nelinearity při výpočtu, vliv zaokrouhlování a ořezávání výsledků |
limitní cykly, statistický model kvantizéru |
popos a návrh NRDF filtrů, definice lineární fáze a fázového zpoždění, úprava imupsní odezvy systému pomocí okénkování |
popis a návrh RDF filtrů, definice nelineární fáze, fázového a skupinového zpoždění, transformace přenosové funkce H(p) na H(z) |
struktury implementace filtrů - přímá, kaskádní, paralelní, mřížková, duální struktury |
diskrétní unitární transformace, jádro transformace, bázové vektory, příklady jader různých transformací |
diskrétní Fourierova transformace (DFT), jádro DFT, algoritmus výpočtu DFT - rychlá Fourierova transformace (FFT) |
spektrální analýza signálu - definice základních pojmů, jako frekvenční krok, zero -padding, frekvenční rozlišení, prosakování ve spektru, váhování vstupních dat |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
popsat ucelený systém číslicového zpracování signálu |
formulovat základní principy problematiky číslicového zpracování signálu |
rozpoznat vhodné metody zpracování signálu, jaký typ a kvalitu číslicového systému použít pro danou úlohu |
Skills - skills resulting from the course: |
navrhnout ucelený systém číslicového zpracování signálu |
provádět simulace navrženého systému číslicového zpracování signálu |
implementovat navržený systém číslicového zpracování signálu |
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 |
Seminar work |
Skills - skills achieved by taking this course are verified by the following means: |
Combined exam |
Competences - competence achieved by taking this course are verified by the following means: |
Combined exam |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture |
Laboratory work |
Lecture with visual aids |
Individual study |
Skills - the following training methods are used to achieve the required skills: |
Laboratory work |
Competences - the following training methods are used to achieve the required competences: |
Lecture with visual aids |
Individual study |
Laboratory work |
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