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.
1.4.1.a Discrete Fourier series
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Skills You'll Learn
Algorithms, Critical Thinking, Mathematical Theory & Analysis, Calculus, Linear Algebra
Reviews
4.5 (621 ratings)
- 5 stars69.40%
- 4 stars20.28%
- 3 stars5.79%
- 2 stars1.61%
- 1 star2.89%
JA
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
RM
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
From the lesson
Module 1.4: Fourier Analysis: More Advanced Tools
Delving deeper in the world of Fourier analysis.
Taught By
Paolo Prandoni
Lecturer
Martin Vetterli
Professor