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Retour à Digital Signal Processing 1: Basic Concepts and Algorithms

Avis et commentaires pour d'étudiants pour Digital Signal Processing 1: Basic Concepts and Algorithms par École polytechnique fédérale de Lausanne

466 évaluations

À propos du cours

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. In this series of four courses, you will 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....

Meilleurs avis


21 juil. 2020

very good course, but it require some math and a brief reading of a book in signals, there are only few courses in coursera that are challenging, this is one of them, 10/10


15 juil. 2020

It is a really comprehensive course with quizzes that were a bit tricky and challenging. I liked the python notebooks for complementing the theory of the course

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1 - 25 sur 87 Avis pour Digital Signal Processing 1: Basic Concepts and Algorithms

par Rayeed R (

21 oct. 2020

Needs to be improved with more math, more examples and problems. The course is okay but i feel it is more suited to students who have already learnt dsp and have come back for some revision. So not suitable to beginners at all. Math background should also be good before tackling the course. Plus having a dsp book to read things from is a must since a lot of the stuff is just briefly explained away.

par J N B P

16 août 2020

Not good for beginners in DSP.

par Brian L

23 août 2020

Excellent first look into DSP, especially in the context of Fourier. Fairly math heavy so a strong math background is recommended.

par Piotr

22 août 2021

Course has potential and some of the material such as certain lectures and Python notebooks are very interesting and fun. Unfortunately the presented material does not prepare well for the exams and the student often has to access a myriad of other resources to even just understand what the exam questions refer to. This makes the overall experience very time consuming and frustrating. Unfortunately I don't think there are many alternative courses covering the same range of topics available at least on Coursera.

par Johan A B A

22 juil. 2020

very good course, but it require some math and a brief reading of a book in signals, there are only few courses in coursera that are challenging, this is one of them, 10/10

par Vladimir R P B

29 déc. 2020

The video lectures are great, but the quizes are awful. The practice homework you are given doesn't prepare you at all for them and the quizes have zero feedback, so often you can't be sure of what you are doing wrong and learning from your mistakes is very difficult. If you add that the course and the quizes are quite mathy, it can get very frustrating. I can only recomend this course to people who already know the subject and want to refresh his memories, to very mathy people or to extremely patient people.

par Pasan J

26 nov. 2020

not suitable for people without prior dsp knowledge

par Tommi J

5 déc. 2020

Wonderful - all previous Digital Signal Processing courses I had taken (in a few different universities) had mainly left me confused with a lot of maths and only a vague understanding of the true interpretations and meanings of frequency domain analysis, or the differences between DFT, DFS, DTFT and FFT. This course is exactly the right approach for someone wanting to get real understanding and insight on how to apply these concepts to real problems. Even if there is a big focus on interpretation and understanding, the presented maths are rigorous and the lecturers are clearly experts of the field. It is a challenging course and you should be prepared to spend up to around 8h per week if you really want to work through the exercises with thought. The Python notebooks are a great addition as well - my only suggestion would have perhaps been to make these interactive graded exercises (e.g. filling in missing functions that implement some DSP algorithms). Recommended thoroughly and I will continue to the next courses in the series!

par Roger H

16 juil. 2020

It is a really comprehensive course with quizzes that were a bit tricky and challenging. I liked the python notebooks for complementing the theory of the course

par Mohamed I F

4 nov. 2020

If you have enough patience to go through the math, you'll find this course and the subsequent courses in the specialization extremely rewarding.

par Arkadeb S

14 août 2020

Thoroughly engaging. One of the better courses on this platform.

par CJ

7 juin 2020

Nice Course, lots of applications. math is challenging when proving a problem. But it is a great course to start up. i would integrate more the programming component in class although there are Python Notes in IPython.

par Felipe D B S

20 juil. 2022

The course have a lot of wasted potential, the python notebooks are great and the initial lectures are good but the following lectures are boring and short, meaning they are tedious and have a high density of information, making them very tiresome.

I can watch the videos multiple times, but i don't want to because they are boring.

I had to use multiple sources to learn the concepts, including my electrical engineering master's classes, and i realised that Digital Signal Processing (DSP) is badly taught overall.

The mathematical ideas are not hard, but the mathematical notation used in DSP is cumbersome, making it tiresome to get used to, a lot of different numerical explanations and examples are needed, these lectures don't give you that.

The image and audio quality are very good.

Here is an advice for present or future teachers, don't be afraid of explaining the same thing multiple times with different perspectives, it helps students create the mental model of the content, thats how you build knowledge in your mind, much better than listen/read the same explanation multiple times.

par Abhishek T

10 sept. 2020

Explanation in the course is very good but High improvement is needed on the basis of giving students math problems along with the teachings so that students can keep track of the course in a better way and helps in their problem-solving skills. We were given only 12 problems but we should be given more than 12 problems every week.

par Nghĩa N T

21 févr. 2021

This was a Mathematics Intuition packed course, very suitable for people looking to further their understanding of the Motivation behind technical terminologies and technique. I would love to point our some special point:

Vector Bases: This is the first SP class where i learn about vector bases, i learned about them in Applied Algebra but never really understand them outside of problem-solving. Prof. Prandoni explanation and examples "clicked" for me and helped me connect multiple concepts i never know are connected.

DFS/DFT/DTFT: Prof. Prandoni gave us very clear definition for each of them, help us define which terms is whichs - as well as their application - whether it is computational or mathematics proof.

However, while the course is strong in Mathematics intuition, there are some technicalities (especially in quizz), that are not included in the course. The technicalities can be solved by picking up your calculus (or algebra) textbook so it was not a big issue.

par Seyed A E

16 oct. 2021

I think it's quite good for one who is interested in signal processing fields and it helps you broaden your vision.

par Thejas C S

17 août 2020

It offers rigorous introduction to DSP. Besides the lectures, it requires separate study of the materials to get well acquainted with the concepts.

par Fernando D

1 juil. 2020

It is a complex course, you should refresh your calculus knowledge before starting it. I was looking for a practical approach, the course has python notebook but I still missed practical content, with real examples and put aside formulas and analytical expressions.

par Muhammed A Ç

27 mars 2021

If you don't have any signals of systems background, course is not much explanatory. Also, to understand mathematical equations you should know the theory behind them very well before taking that course


26 août 2020

needs improvement for numerical explanation.

par Soniya K

24 mai 2021

According to me the course should start from the basic. It is way too much maths for beginners .

par Sophia L

5 nov. 2020

The lectures are excellent. The videos, slides, exercises are high quality. The course is very well-organized and the instructors propose extra resources, which I very appreciate. The instructors explained well the different notions introduced. There are examples and applications that illustrate well the concepts. Quizzes are challenging. Need a (strong) maths background to follow the course, but I think this is not the most important point in order to achieve this course. If your ambition is to master concepts of DSP, I think this course is well-suitable. Thanks for sharing your teaching.

par Hazem K 2

1 oct. 2020

The course instructors are really good at delivering the concepts intuitively and it does not fall short of providing mathematical derivations as well. It also benefited me in other domains like linear algebra, in which the instructor's explanation really cemented some concepts that I felt were abstract and arbitrary before I took this course.

For full experience, I would recommend trying to implement what you learn in code, and/or do the provided jupyter notebooks on your own, in your preferred language.

par Reema S

31 déc. 2020

The problems and quizzes were difficult but very standard. The descriptions were detailed and understandable. I'd totally recommend this course. I wish it had some programming challenges as graded exercises as well. Also, I found it difficult during the quizzes that the incorrect answers were not shown, and every time you try, the options and questions change so for some of the answers that were incorrect, I couldn't find the reason.

par Thiago C C

10 mars 2021

A great course to learn about Digital Signal Processing. The professors use a variety of resources to support the content thought in the video lectures. Recommended for everyone who wants to learn the subject.