Back to Digital Signal Processing 1: Basic Concepts and Algorithms

stars

329 ratings

•

62 reviews

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....

JA

Jul 21, 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

MF

Nov 3, 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.

Filter by:

By Rayeed R (

•Oct 21, 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.

By J N B P

•Aug 16, 2020

Not good for beginners in DSP.

By Johan A B A

•Jul 22, 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

By Brian L

•Aug 23, 2020

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

By Pasan J

•Nov 26, 2020

not suitable for people without prior dsp knowledge

By Tommi J

•Dec 5, 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!

By Roger G H M

•Jul 16, 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

By Arkadeb S

•Aug 14, 2020

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

By CJ

•Jun 7, 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.

By Thejas C S

•Aug 17, 2020

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

By Abhishek T

•Sep 10, 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.

By Nghĩa N T

•Feb 21, 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.

By Sophia L

•Nov 5, 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.

By Hazem K 2

•Oct 1, 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.

By Reema S

•Dec 31, 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.

By Thiago C C

•Mar 10, 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.

By Булат Р И

•Dec 3, 2020

It will be great if there are more exercises. May be from some educational books. They could be optional. Thank you for your course! Very like your "signal of the day". It is great.

By Mohamed I F

•Nov 4, 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.

By 肖湘

•Feb 15, 2021

it's fantastic, i really enjoy it. the only thing can be prove is that could the instructor give solution to the excercise on the book?

By Prakriti M

•Jun 6, 2020

The lectures were extremely good. Concepts were well-explained. Very engaging lessons and coursework.

By Yashwanth

•Sep 13, 2020

The state space approach to explaining the basics of signal processing has been handled well.

By Fenghua W

•Aug 21, 2020

Lecture explains concepts very clearly. Python labs provide very good hands-on experience.

By Arbaaz J

•Aug 27, 2020

Course was very interesting and the quizzes were tough but you definitely learn a lot.

By Daniel S

•Dec 28, 2020

Really nice course, the topics were really understanbale and easy to get.

By Balakrishna M

•Aug 13, 2020

Amazing course and assignment questions are framed well .

- Finding Purpose & Meaning in Life
- Understanding Medical Research
- Japanese for Beginners
- Introduction to Cloud Computing
- Foundations of Mindfulness
- Fundamentals of Finance
- Machine Learning
- Machine Learning Using Sas Viya
- The Science of Well Being
- Covid-19 Contact Tracing
- AI for Everyone
- Financial Markets
- Introduction to Psychology
- Getting Started with AWS
- International Marketing
- C++
- Predictive Analytics & Data Mining
- UCSD Learning How to Learn
- Michigan Programming for Everybody
- JHU R Programming
- Google CBRS CPI Training

- Natural Language Processing (NLP)
- AI for Medicine
- Good with Words: Writing & Editing
- Infections Disease Modeling
- The Pronounciation of American English
- Software Testing Automation
- Deep Learning
- Python for Everybody
- Data Science
- Business Foundations
- Excel Skills for Business
- Data Science with Python
- Finance for Everyone
- Communication Skills for Engineers
- Sales Training
- Career Brand Management
- Wharton Business Analytics
- Penn Positive Psychology
- Washington Machine Learning
- CalArts Graphic Design

- Professional Certificates
- MasterTrack Certificates
- Google IT Support
- IBM Data Science
- Google Cloud Data Engineering
- IBM Applied AI
- Google Cloud Architecture
- IBM Cybersecurity Analyst
- Google IT Automation with Python
- IBM z/OS Mainframe Practitioner
- UCI Applied Project Management
- Instructional Design Certificate
- Construction Engineering and Management Certificate
- Big Data Certificate
- Machine Learning for Analytics Certificate
- Innovation Management & Entrepreneurship Certificate
- Sustainabaility and Development Certificate
- Social Work Certificate
- AI and Machine Learning Certificate

- Computer Science Degrees
- Business Degrees
- Public Health Degrees
- Data Science Degrees
- Bachelor's Degrees
- Bachelor of Computer Science
- MS Electrical Engineering
- Bachelor Completion Degree
- MS Management
- MS Computer Science
- MPH
- Accounting Master's Degree
- MCIT
- MBA Online
- Master of Applied Data Science
- Global MBA
- Master's of Innovation & Entrepreneurship
- MCS Data Science
- Master's in Computer Science
- Master's in Public Health