Digital Signal Processing 2: Filtering

This course is part of Digital Signal Processing Specialization

Instructors: Paolo Prandoni

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3 modules

Gain insight into a topic and learn the fundamentals.

196 reviews

Intermediate level

Some related experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

196 reviews

Intermediate level

Some related experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

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

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

3 assignments

Taught in English

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This course is part of the Digital Signal Processing Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 3 modules in this course

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.

How digital filters work in time and in frequency.

What's included

13 videos12 readings1 assignment2 ungraded labs1 plugin

13 videos Total 78 minutes

2.1.1.a Linear time-invariant filters 4 minutes
2.1.1.b Convolution 7 minutes
2.1.2.a The moving average filter 8 minutes
2.1.2.b The leaky integrator 5 minutes
2.1.3.a Filter classification in the time domain 3 minutes
2.1.3.b Filter stability 6 minutes
2.1.4.a The convolution theorem 7 minutes
2.1.4.b Examples of frequency response 14 minutes
2.1.5.a Filter classification in the frequency domain 1 minute
2.1.5.b The ideal lowpass filter 7 minutes
2.1.5.c Ideal filters derived from the ideal lowpass filter 3 minutes
2.1.5.d Demodulation revisited 2 minutes
SOTD: Can one hear the shape of a room? 11 minutes

12 readings Total 86 minutes

Welcome to DSP Two! 5 minutes
Introduction 1 minute
What have we learned? 3 minutes
Introduction 1 minute
What have we learned? 3 minutes
Introduction 1 minute
What have we learned? 2 minutes
Introduction 2 minutes
What have we learned? 3 minutes
Introduction 2 minutes
What have we learned? 3 minutes
Practice homework 60 minutes

1 assignment Total 150 minutes

Homework for Module 2.1 150 minutes

2 ungraded labs Total 120 minutes

Filtering Music 60 minutes
A Taste of Nonlinear Processing 60 minutes

1 plugin Total 15 minutes

Feedback W1 15 minutes

Learning how to choose and design the right filter using the z-transform and numerical tools.

What's included

13 videos11 readings1 assignment2 ungraded labs1 plugin

13 videos Total 147 minutes

2.2.1.a Impulse truncation (and the Gibbs phenomenon) 4 minutes
2.2.1.b The window method 11 minutes
2.2.1.c Frequency sampling 3 minutes
2.2.2.a The z-transform 14 minutes
2.2.2.b Region of convergence and stability 16 minutes
2.2.3 Intuitive IIR designs 10 minutes
2.2.4.a Filter specifications 6 minutes
2.2.4.b IIR design 4 minutes
2.2.4.c FIR design 8 minutes
2.2.4.d Fractional delay and Hilbert filter 16 minutes
2.2.5.a Implementation of digital filters 12 minutes
2.2.5.b Real-time processing 23 minutes
Signal of the Day: Image Resolution and Space Exploration 19 minutes

11 readings Total 93 minutes

Introduction 5 minutes
What have we learned? 2 minutes
Introduction 5 minutes
What have we learned? 5 minutes
Introduction 1 minute
What have we learned? 2 minutes
Introduction 2 minutes
What have we learned? 5 minutes
Introduction 3 minutes
Practice homework 60 minutes
Notes and Supplementary Materials 3 minutes

1 assignment Total 90 minutes

Homework for Module 2.2 90 minutes

2 ungraded labs Total 120 minutes

FIR Implementation 60 minutes
Parks-McClellan FIR Design Algorithm 60 minutes

1 plugin Total 15 minutes

Feedback W2 15 minutes

Analyzing and processing random signals and designing filters that adapt to unknown inputs.

What's included

8 videos6 readings1 assignment1 ungraded lab1 plugin

8 videos Total 75 minutes

2.3.1.a Random Variables 11 minutes
2.3.1.b Stochastic Processes 11 minutes
2.3.1.c Power Spectral Density 18 minutes
2.3.1.d Filtering Random Processes 5 minutes
2.3.2.a Optimal Least Squares 10 minutes
2.3.2.b LPC Speech Coding 7 minutes
2.3.2.c The LMS Filter 8 minutes
2.3.2.d Echo Cancellation 5 minutes

6 readings Total 41 minutes

Introduction 8 minutes
What have we learned? 5 minutes
Introduction 3 minutes
What have we learned? 10 minutes
Practice Homework 10 minutes
Notes and Supplementary Material 5 minutes

1 assignment

Homework for Module 2.3 0 minutes

1 ungraded lab Total 60 minutes

Echo Cancellation 60 minutes

1 plugin Total 15 minutes

Feedback W3 15 minutes

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Instructors

Instructor ratings

(54 ratings)

Paolo Prandoni

École Polytechnique Fédérale de Lausanne

5 Courses 130,686 learners

Offered by

École Polytechnique Fédérale de Lausanne

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Reviewed on Sep 4, 2020

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

Reviewed on Nov 27, 2020

This is a really good course that has very good exercises

Reviewed on Apr 20, 2022

It is a good starting point to know how DSP techniques are doing from a mathematical point of view. A deep knowledge allows to understand what is beneath the algorithms.

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To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. 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.

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.

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.