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Магистратура 2019/2020

Цифровая обработка сигналов

Направление: 11.04.02. Инфокоммуникационные технологии и системы связи
Когда читается: 2-й курс, 1 модуль
Формат изучения: с онлайн-курсом
Прогр. обучения: Интернет вещей и киберфизические системы
Язык: английский
Кредиты: 4
Контактные часы: 2

Course Syllabus

Abstract

The goal, for students of this course, will be to learn the fundamentals of Digital Signal Processing from the ground up. Start-ing from the basic definition of a discrete-time signal, we will work our way through Fourier analysis, filter design, sampling, interpolation and quantization to build a DSP toolset complete enough to analyze a practical communication system in detail. Hands-on examples and demon-stration will be routinely used to close the gap between theory and practice. To make the best of this class, it is recommended that you are proficient in basic calculus and linear algebra; several programming examples will be provided in the form of Python notebooks but you can use your favorite programming language to test the algorithms described in the course. https://www.coursera.org/learn/dsp
Learning Objectives

Learning Objectives

  • Digital Signal Processing is the branch of engineering that, in the space of just a few dec-ades, has enabled unprecedented levels of interpersonal communication and of on-demand enter-tainment. By reworking the principles of electronics, telecommunication and computer science into a unifying paradigm, DSP is a the heart of the digital revolution that brought us CDs, DVDs, MP3 players, mobile phones and countless other devices. The goal, for students of this course, will be to learn the fundamentals of Digital Signal Processing from the ground up. Start-ing from the basic definition of a discrete-time signal, we will work our way through Fourier analysis, filter design, sampling, interpolation and quantization to build a DSP toolset complete enough to analyze a practical communication system in detail. Hands-on examples and demon-stration will be routinely used to close the gap between theory and practice. To make the best of this class, it is recommended that you are proficient in basic calculus and linear algebra; several programming examples will be provided in the form of Python notebooks but you can use your favorite programming language to test the algorithms described in the course. The course is based on MOOC “Digital Signal Processing” https://www.coursera.org/learn/dsp (Platform - Coursera.org)
Expected Learning Outcomes

Expected Learning Outcomes

  • Basics of Digital Signal Processing
  • Signal processing and vector spaces
  • Basics of Fourier Analysis
  • Advanced Fourier Analysis
  • Introduction to Filtering
  • Image Processing , Real-time processing
  • Sampling and Quantization
  • Digital Communication Systems
  • ntroduction, manipulations Image Processing
Course Contents

Course Contents

  • Module 1: Basics of Digital Signal Processing
    1.1. Introduction to digital signal processing 1.2. Discrete-time signals 1.3.a How your PC plays discrete-time sounds 1.3.b The Karplus-Strong algorithm 1.4. Complex exponentials
  • Module 2: Vector Spaces
    2.1. Signal processing and vector spaces 2.2.a Vector space 2.2.b Signal spaces 2.3. Bases 2.4. Subspace-based approximations
  • Module 3: Part 1 - Basics of Fourier Analysis
    3.1.a The frequency domain 3.1.b The DFT as a change of basis 3.2.a DFT definition 3.2.b Examples of DFT calculation 3.2.c Interpreting a DFT plot 3.3.a DFT analysis 3.3.b DFT example - analysis of musical instruments 3.3.c DFT synthesis5 3.3.d DFT example - tide prediction in Venice 3.3.e DFT example - MP3 compression 3.4.a The short-time Fourier transform 3.4.b The spectrogram 3.4.c Time-frequency tiling:
  • Module 3: Part 2 - Advanced Fourier Analysis
    3.5.a Discrete Fourier series 3.5.b Karplus-Strong revisited and DFS 3.6.a Karplus-Strong revisited and the DTFT 3.6.b Existence and properties of the DTFT 3.6.c The DTFT as a change of basis 3.7.a Sinusoidal modulation 3.7.b Tuning a guitar 3.8 Relationship between transforms 3.9 The fast Fourier transform
  • Module 4: Part 1 Introduction to Filtering
    4.1.a Linear time-invariant filters 4.1.b Convolution 4.2.a The moving average filter 4.2.b The leaky integrator 4.3.a Filter classification in the time domain3 4.3.b Filter stability 4.4.a The convolution theorem 4.4.b Examples of frequency response 4.5.a Filter classification in the frequency domain 4.5.b The ideal lowpass filter 4.5.c Ideal filters derived from the ideal lowpass filter 4.5.d Demodulation revisited
  • Module 4: Part 2 Filter Design
    4.6.a Impulse truncation and Gibbs phenomenon 4.6.b Window method 4.6.c Frequency sampling 4.7.a The z-transform 4.7.b Region of convergence and stability 4.8.a Intuitive IIR designs 4.9.a Filter specifications 4.9.b IIR design 4.9.c FIR design 4.8.b Fractional delay and Hilbert filter 4.10 Implementation of digital filters 4.11 Real-time processing 4.12 Dereverberation and echo cancellation
  • Module 5: Sampling and Quantization
    5.1.a The continuous-time paradigm 5.1.b Continuous-time signal processing 5.2.a Polynomial interpolation 5.2.b Local interpolation 5.3.a The spectrum of interpolated signals 5.3.b The space of bandlimited functions 5.3.c The sampling theorem 5.4.a Raw sampling 5.4.b Sinusoidal aliasing 5.4.c Aliasing for arbitrary spectra 5.4.d Sampling strategies 5.5.a Stochastic signal processing 5.5.b Quantization 5.5.c Clipping, saturation and conpanding 5.6 Practical sampling and interpolation 5.7 Bandpass sampling 5.8 Multirate signal processing 5.9 FIR-based sampling rate conversion 5.10 Analog-to-digital and digital-to-analog converters 5.11 Oversampling
  • Module 6: Digital Communication Systems
    6.1.a The success factors for digital communications 6.1.b The analog channel constraints 6.1.c The design problem 6.2.a Upsampling 6.2.b Fitting the transmitter spectrum 6.3.a Noise and probability of error 6.3.b PAM and QAM 6.4.a Modulation and demodulation 6.4.b Design example5 6.5.a Receiver design 6.5.b Delay compensation 6.5.c Adaptive equalization 6.6.a ADSL design8 6.6.b Discrete multitone modulation
  • Module 7: Image Processing
    7.1 Introduction to image processing 7.2 Image manipulations 7.3 Frequency analysis 7.4 Image filtering 7.5 Image compression 7.6 The JPEG compression algorithm
Assessment Elements

Assessment Elements

  • non-blocking Самостоятельная работа
  • non-blocking Экзамен
    В ходе освоения дисциплины формируются следующие компетенции: УК-1, УК-6, УК-7, УК-8, ОПК-3, ПК-21
Interim Assessment

Interim Assessment

  • Interim assessment (1 module)
    0.5 * Самостоятельная работа + 0.5 * Экзамен
Bibliography

Bibliography

Recommended Core Bibliography

  • Unpingco, J. Python for Signal Processing. – Springer International Publishing, 2014. – 128 pp.
  • Вадутов О. С. - ЭЛЕКТРОНИКА. МАТЕМАТИЧЕСКИЕ ОСНОВЫ ОБРАБОТКИ СИГНАЛОВ. Учебник и практикум для академического бакалавриата - М.:Издательство Юрайт - 2019 - 307с. - ISBN: 978-5-9916-6551-3 - Текст электронный // ЭБС ЮРАЙТ - URL: https://urait.ru/book/elektronika-matematicheskie-osnovy-obrabotki-signalov-433991
  • Марков Ю. В., Боков А. С. ; под науч. ред. Никитина Н.П. - УСТРОЙСТВА ПРИЕМА И ОБРАБОТКИ СИГНАЛОВ: ПРОЕКТИРОВАНИЕ. Учебное пособие для вузов - М.:Издательство Юрайт - 2019 - 109с. - ISBN: 978-5-534-10132-4 - Текст электронный // ЭБС ЮРАЙТ - URL: https://urait.ru/book/ustroystva-priema-i-obrabotki-signalov-proektirovanie-429417
  • Нефедов В. И., Сигов А. С. ; Под ред. Нефедова В.И. - РАДИОТЕХНИЧЕСКИЕ ЦЕПИ И СИГНАЛЫ. Учебник для СПО - М.:Издательство Юрайт - 2019 - 266с. - ISBN: 978-5-534-03409-7 - Текст электронный // ЭБС ЮРАЙТ - URL: https://urait.ru/book/radiotehnicheskie-cepi-i-signaly-433793

Recommended Additional Bibliography

  • Pereyra, M. C., & Ward, L. A. (2012). Harmonic Analysis : From Fourier to Wavelets. Providence, R.I.: AMS. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=971297
  • Белов Л. А. - РАДИОЭЛЕКТРОНИКА. ФОРМИРОВАНИЕ СТАБИЛЬНЫХ ЧАСТОТ И СИГНАЛОВ 2-е изд., пер. и доп. Учебник для бакалавриата и магистратуры - М.:Издательство Юрайт - 2019 - 229с. - ISBN: 978-5-534-09062-8 - Текст электронный // ЭБС ЮРАЙТ - URL: https://urait.ru/book/radioelektronika-formirovanie-stabilnyh-chastot-i-signalov-441251
  • Осадченко В. Х., Волкова Я. Ю., Кандрина Ю. А. ; Под общ. ред. Осадченко В. Х. - ЭЛЕКТРОТЕХНИКА: ФИЛЬТРЫ ВЫСОКИХ И НИЗКИХ ЧАСТОТ. Учебное пособие для вузов - М.:Издательство Юрайт - 2019 - 80с. - ISBN: 978-5-9916-9936-5 - Текст электронный // ЭБС ЮРАЙТ - URL: https://urait.ru/book/elektrotehnika-filtry-vysokih-i-nizkih-chastot-438172
  • Петров В.М. - Узкополосные управляемые фильтры для DWDM систем: учебное пособие - Издательство "Лань" - 2019 - 164с. - ISBN: 978-5-8114-3665-1 - Текст электронный // ЭБС ЛАНЬ - URL: https://e.lanbook.com/book/115491