Basic signal processing concepts, Fourier analysis and filters. This module can be used as a starting point or a basic refresher in elementary DSP.
Course Details
| Language | English |
| Duration | 4 Weeks |
| Effort | 8-10 hours / week |
Description
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.
What you will learn
- The nature of discrete-time signals
- Discrete-time signals are vectors in a vector space
- Discrete-time signals can be analyzed in the frequency domain via the Fourier transform
Prerequisites
Some related experience required
Plan
The course is structured into 4 weeks:
- Module 1.1 Digital Signal Processing the Basics
- Module 1.2 Signal Processing Meets Vector Space
- Module 1.3 Fourier Analysis: the Basics
- Module 1.4 Fourier Analysis More Advanced Tools
