About this Course
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Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 33 hours to complete

Suggested: 8-10 hours/week...

English

Subtitles: English
User
Learners taking this Course are
  • Machine Learning Engineers
  • Engineers
  • Researchers
  • Systems Engineers
  • Data Scientists

Skills you will gain

Signal ProcessingDiscrete Fourier TransformData TransmissionIpythonFourier AnalysisConvolutionLinear AlgebraDigital Signal Processing
User
Learners taking this Course are
  • Machine Learning Engineers
  • Engineers
  • Researchers
  • Systems Engineers
  • Data Scientists

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 33 hours to complete

Suggested: 8-10 hours/week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
7 hours to complete

Module 1: Basics of Digital Signal Processing

7 videos (Total 93 min), 7 readings, 1 quiz
7 videos
1.1.a Introduction to digital signal processing25m
1.2.a Discrete-time signals16m
1.3.a How your PC plays discrete-time sounds3m
1.3.b The Karplus-Strong algorithm19m
Signal of the Day: Goethe's temperature measurement8m
1.4.a Complex exponentials14m
7 readings
Introduction to Module 15m
Introduction to Lecture 1.15m
Introduction to Lecture 1.25m
Introduction to Lecture 1.35m
Introduction to Lecture 1.45m
Notes and external resources15m
Practice homework for Module 11h
1 practice exercise
Homework for Module 11h 45m
Week
2
5 hours to complete

Module 2: Vector Spaces

6 videos (Total 63 min), 7 readings, 1 quiz
6 videos
Signal of the Day: Exoplanet hunting9m
2.2.a Vector space15m
2.2.b Signal spaces4m
2.3.a Bases13m
2.4.a Subspace-based approximations16m
7 readings
Introduction to Module 25m
Introduction to Lecture 2.15m
Introduction to Lesson 2.25m
Introduction to Lecture 2.35m
Introduction to Lecture 2.45m
Notes and external resources15m
Practice homework for Module 21h
1 practice exercise
Homework for Module 21h 30m
Week
3
9 hours to complete

Module 3: Part 1 - Basics of Fourier Analysis

14 videos (Total 95 min), 11 readings, 1 quiz
14 videos
3.1.b The DFT as a change of basis10m
3.2.a DFT definition5m
3.2.b Examples of DFT calculation13m
3.2.c Interpreting a DFT plot4m
3.3.a DFT analysis11m
3.3.b DFT example - analysis of musical instruments4m
3.3.c DFT synthesis5m
3.3.d DFT example - tide prediction in Venice4m
3.3.e DFT example - MP3 compression4m
Signal of the Day: The first man-made signal from outer space5m
3.4.a The short-time Fourier transform5m
3.4.b The spectrogram7m
3.4.c Time-frequency tiling5m
11 readings
Introduction to Module 310m
Introduction to Lesson 3.15m
Summary of Lesson 3.110m
Introduction to Lesson 3.25m
Summary of Lesson 3.210m
Introduction to Lesson 3.35m
Summary of Lesson 3.310m
Real-valued Transforms10m
Introduction to Lesson 3.45m
Summary of Lesson 3.410m
Practice homework for Module 3 Part 11h
1 practice exercise
Homework for Module 3 Part 12h
Week
4
8 hours to complete

Module 3: Part 2 - Advanced Fourier Analysis

10 videos (Total 116 min), 7 readings, 1 quiz
10 videos
3.5.b Karplus-Strong revisited and DFS7m
3.6.a Karplus-Strong revisited and the DTFT13m
3.6.b Existence and properties of the DTFT7m
3.6.c The DTFT as a change of basis9m
3.7.a Sinusoidal modulation7m
3.7.b Tuning a guitar4m
Signal of the Day: Tristan Chord6m
3.8* Relationship between transforms14m
3.9* The fast Fourier transform42m
7 readings
Introduction to Lesson 3.55m
Summary of Lesson 3.510m
Introduction to Lesson 3.65m
Summary of Lesson 3.610m
Introduction to Lesson 3.75m
Notes and external ressources15m
Practice homework for Module 3 Part 21h
1 practice exercise
Homework for Module 3 Part 22h
4.7
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Top reviews from Digital Signal Processing

By JAJul 2nd 2017

Definitely an interesting course that is explained well. The math gets to a pretty high level after a few sections, but it still seems manageable to understand. I would recommend it for sure!

By GCOct 2nd 2018

A good course with awesome instructors, good for learning the basic level of signal processing. It will initiate you for more advanced levels of signal processing. Fun experience overall.

Instructors

Avatar

Paolo Prandoni

Lecturer
School of Computer and Communication Science
Avatar

Martin Vetterli

Professor
School of Computer and Communication Sciences

About École Polytechnique Fédérale de Lausanne

Frequently Asked Questions

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