Kod przedmiotu: |
103A-TCTCM-ISA-EDISP |
Kod Erasmus / ISCED: |
(brak danych)
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(brak danych)
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Nazwa przedmiotu: |
Digital Signal Processing |
Jednostka: |
Wydział Elektroniki i Technik Informacyjnych |
Grupy: |
( Courses in English )--eng.-EITI
( Przedmioty techniczne )---EITI
( Technical Courses )--eng.-EITI
( Telecommunication Systems )-Computer Science, Telecommunications-B.Sc.-EITI
( Telecommunications - Foundation )-Telecommunications-M.Sc.-EITI
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Punkty ECTS i inne: |
(brak)
Podstawowe informacje o zasadach przyporządkowania punktów ECTS: - roczny wymiar godzinowy nakładu pracy studenta konieczny do osiągnięcia zakładanych efektów uczenia się dla danego etapu studiów wynosi 1500-1800 h, co odpowiada 60 ECTS;
- tygodniowy wymiar godzinowy nakładu pracy studenta wynosi 45 h;
- 1 punkt ECTS odpowiada 25-30 godzinom pracy studenta potrzebnej do osiągnięcia zakładanych efektów uczenia się;
- tygodniowy nakład pracy studenta konieczny do osiągnięcia zakładanych efektów uczenia się pozwala uzyskać 1,5 ECTS;
- nakład pracy potrzebny do zaliczenia przedmiotu, któremu przypisano 3 ECTS, stanowi 10% semestralnego obciążenia studenta.
zobacz reguły punktacji
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Język prowadzenia: |
angielski
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Jednostka decyzyjna: |
103000 - Wydział Elektroniki i Technik Informacyjnych
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Kod wydziałowy: |
EDISP
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Numer wersji: |
1
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Skrócony opis: |
(tylko po angielsku) An introductory course on digital signal processing basics for students in computer science and engineering, designed to teach students the fundamentals of digital signal processing theroy and show the basics of DSP application. Topics covered: discrete-time signals and systems, frequency domain analysis of DT signals, DTFT and DFT, FFT algorithm basics, FFT applications in spectral analysis, digital filtering, FIR/IIR filter design and implementation, digital signal processors overview, fundamentals of DT random signals, basic autocorrelation and PSD estimation techniques, 2D signal processing, advanced DSP techniques overview.,
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Pełny opis: |
(tylko po angielsku) An introductory course on digital signal processing basics for students in computer science and engineering, designed to teach students the fundamentals of digital signal processing theroy and show the basics of DSP application. Topics covered: discrete-time signals and systems, frequency domain analysis of DT signals, DTFT and DFT, FFT algorithm basics, FFT applications in spectral analysis, digital filtering, FIR/IIR filter design and implementation, digital signal processors overview, fundamentals of DT random signals, basic autocorrelation and PSD estimation techniques, 2D signal processing, advanced DSP techniques overview.,
Lecture contents DT signals and systems review. Review of DT signals and systems basics: discretisation in time and in amplitude, inherently discrete signals, DT system properties: linearity, shift-invariance. Description of LTI systems: impulse response, step response, difference equations, linear convolution (4h).
Frequency-domain methods. Concept of frequency in DT domain, periodicity definition, DTFT properties (periodic and limited energy signals), DFT definition and properties. DFT implementations (FFT) and applications. Windowing theory and applications. Circular convolution vs. linear convolution (5h).
Review and test I.(1h+1h) Instantaneous spectrum. Application of FFT and windowing to analysis of signals with changing properties (1h).
Z-transform. Review of z-transform basics, applications to analysis of DT signals and systems. Z-domain transfer function, differential equation of a system and its frequency characteristics (2h).
Filter design. FIR filter design by window and optimisation methods. IIR filter design from CT prototype (impulse invariance and bilinear transform) and optimisation methods. Filter implementation problems (2h). Digital signal processors. The idea of DSP. Architectural properties (pipelining, parallelism, hardware enhancements, Harvard memory architecture). DSP56002 as an example of typical DSP: arithmetic, addressing, programming overview (2h).
Introduction to random DT signals. Random signal properties. Random process and its realization. Autocorrelation and PSD. Filtering of random signals. Estimation of parameters. Applications of random signal theory: signal modelling, system modelling, detection (3h).
Review and test II. (1h+1h) Two-dimensional signal processing. 2D signals. 2D FFT - definition and properties. Filtering of 2D signals. Application to image processing (3h).
Advanced techniques overview. Examples of practical applications and implementations of the ideas and algorithms learned at the lecture - audio processing, video compression, radar, sonar, telecommunication (2h).
Summary and review (2h).
Laboratory contents
- Matlab as a DSP tool (2h)
- DT signals, systems, frequency concept (4h)
- Spectral analysis of deterministic signals (4h)
- Instantaneous spectrum and spectrogram (4h)
- Digital filtering and filter design (4h)
- Digital signal processors (basic programming)
- Random signals
- Image processing
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Literatura: |
(tylko po angielsku) Basic
- Alan V. Oppenheim, Roland Schäfer. Disrete-time signal processing. (any edition, including previous version entitled Digital signal processing)
Optional
- Steven W. Smith, The Scientist and Engineer`s Guide to Digital Signal Processing, www.dspguide.com
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