This course is part of the Digital Signal Processing Specialization

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Paolo Prandoni +1 more instructor

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Digital Signal Processing SpecializationÉcole Polytechnique Fédérale de Lausanne

About this Course

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Digital Signal Processing is the branch of engineering that, in the space of just a few decades, has enabled unprecedented levels of interpersonal communication and of on-demand entertainment. 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. Starting 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 demonstration 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.

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Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Course 2 of 4 in the

Digital Signal Processing Specialization

Intermediate Level

Approx. 18 hours to complete

English

What you will learn

Digital filters, how they work
Digital filter design
Adaptive signal processing

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 2 of 4 in the

Digital Signal Processing Specialization

Intermediate Level

Approx. 18 hours to complete

English

Instructors

Instructor rating

4.75/5 (42 Ratings)

Paolo Prandoni

Lecturer

School of Computer and Communication Science

107,146 Learners

5 Courses

Martin Vetterli

Professor

School of Computer and Communication Sciences

107,146 Learners

5 Courses

Offered by

École Polytechnique Fédérale de Lausanne

Syllabus - What you will learn from this course

Week1

Week 1

7 hours to complete

Module 2.1 Digital Filters

7 hours to complete

13 videos (Total 78 min), 12 readings, 1 quiz

13 videos

2.1.1.a Linear time-invariant filters4m2.1.1.b Convolution6m2.1.2.a The moving average filter8m2.1.2.b The leaky integrator5m2.1.3.a Filter classification in the time domain3m2.1.3.b Filter stability5m2.1.4.a The convolution theorem6m2.1.4.b Examples of frequency response14m2.1.5.a Filter classification in the frequency domain1m2.1.5.b The ideal lowpass filter6m2.1.5.c Ideal filters derived from the ideal lowpass filter2m2.1.5.d Demodulation revisited2mSOTD: Can one hear the shape of a room?10m

12 readings

Welcome to DSP Two!5mIntroduction1mWhat have we learned?3mIntroduction1mWhat have we learned?3mIntroduction1mWhat have we learned?2mIntroduction2mWhat have we learned?3mIntroduction2mWhat have we learned?3mPractice homework1h

1 practice exercise

Homework for Module 2.12h 30m

Week2

Week 2

8 hours to complete

Module 2.2: Filter Design

8 hours to complete

13 videos (Total 147 min), 11 readings, 1 quiz

13 videos

2.2.1.a Impulse truncation (and the Gibbs phenomenon)3m2.2.1.b The window method10m2.2.1.c Frequency sampling2m2.2.2.a The z-transform14m2.2.2.b Region of convergence and stability15m2.2.3 Intuitive IIR designs10m2.2.4.a Filter specifications6m2.2.4.b IIR design3m2.2.4.c FIR design7m2.2.4.d Fractional delay and Hilbert filter16m2.2.5.a Implementation of digital filters12m2.2.5.b Real-time processing22mSignal of the Day: Image Resolution and Space Exploration19m

11 readings

Introduction5mWhat have we learned?2mIntroduction5mWhat have we learned?5mIntroduction1mWhat have we learned?2mIntroduction2mWhat have we learned?5mIntroduction3mPractice homework1hNotes and Supplementary Materials3m

1 practice exercise

Homework for Module 2.21h 30m

Week3

Week 3

3 hours to complete

Module 2.3: Stochastic and Adaptive Signal Processing

3 hours to complete

8 videos (Total 75 min), 6 readings, 1 quiz

8 videos

2.3.1.a Random Variables10m2.3.1.b Stochastic Processes10m2.3.1.c Power Spectral Density18m2.3.1.d Filtering Random Processes4m2.3.2.a Optimal Least Squares10m2.3.2.b LPC Speech Coding7m2.3.2.c The LMS Filter8m2.3.2.d Echo Cancellation4m

6 readings

Introduction8mWhat have we learned?5mIntroduction3mWhat have we learned?10mPractice Homework10mNotes and Supplementary Material5m

1 practice exercise

Homework for Module 2.3

Reviews

4.7

23 reviews

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TOP REVIEWS FROM DIGITAL SIGNAL PROCESSING 2: FILTERING

by MCDec 20, 2021

Had to use a lot of outside material - mostly YouTube videos from Rich Radke and Barry Van Veen to complete this course.

by PGSep 4, 2020

Add some numerical problems and solve them in your video lectures for the better understanding of concepts.

by BLAug 30, 2020

Excellent continuation to EPFL's DSP series. Be aware that the 3rd week requires a good foundation in statistics.

by SMOct 7, 2020

Best material on Signal Processing. Instructors emphasized on concepts. This course is enjoyable

View all reviews

About the Digital Signal Processing Specialization

This Specialization provides a full course in Digital Signal Processing, with a focus on audio processing and data transmission. You will start from the basic concepts of discrete-time signals and proceed to learn how to analyze data via the Fourier transform, how to manipulate data via digital filters and how to convert analog signals into digital format. Finally, you will also discover how to implement real-time DSP algorithms on a general-purpose microcontroller. The solid theoretical bases provided by the four courses in this specialization are complemented by applied examples in Python, in the form of Jupyter Notebooks; exercises with solutions provide a wealth of examples in order to tackle the weekly homework.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
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The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

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Digital Signal Processing 2: Filtering

About this Course

What you will learn