

Digital Signal Processing 3: Analog vs Digital
- Offered byCoursera
- Public/Government Institute
Digital Signal Processing 3: Analog vs Digital at Coursera Overview
Duration | 16 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course |
Credential | Certificate |
Digital Signal Processing 3: Analog vs Digital at Coursera Highlights
- This Course Plus the Full Specialization.
- Shareable Certificates.
- Graded Programming Assignments.
Digital Signal Processing 3: Analog vs Digital at Coursera Course details
- 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.
Digital Signal Processing 3: Analog vs Digital at Coursera Curriculum
Module 3.1: Interpolation and Sampling
3.1.1.a The continuous-time paradigm
3.1.1.b Continuous-time signal processing
3.1.1.c Bandlimited functions
3.1.2.a Polynomial interpolation
3.1.2.b Local interpolation
3.2.1.c Sinc interpolation
3.1.3.a The spectrum of interpolated signals
3.1.3.b The space of bandlimited functions
3.1.3.c The sampling theorem
Signal of the Day: Fukushima
Welcome to DSP Three!
Introduction
What have we learned?
Introduction
What have we learned?
Introduction
What have we learned?
Practice homework
Further reading
Homework for Module 3.1
Module 3.2: Aliasing
3.2.1.a Raw sampling
3.2.1.b Sinusoidal aliasing
3.2.1.c Aliasing for arbitrary spectra
3.2.2.a Sampling strategies
3.2.2.b Bandpass sampling
Introduction
What have we learned?
Introduction
Practice homework
Homework for Module 3.2
Module 3.3: Multirate Signal Processing
3.3.1.a Upsampling
3.3.1.b Downsampling
3.3.2 FIR-based sampling rate conversion
Introduction
What have we learned?
Practice Homework
Homework for Module 3.4
Module 3:4: A/D and D/A Conversion
3.4.1.a Quantization
3.4.1.b Clipping, saturation and companding
3.4.2 Analog-to-digital and digital-to-analog converters
3.4.3.a Practical sampling and interpolation
3.4.3.b Oversampled D/A
3.4.3.c Oversampled A/D
MP3 Compression
Signal of the Day: Lehman Brothers
Introduction
What have we learned?
Introduction
Introduction
What have we learned?
Practice homework for Module 3.4
Homework for Module 3.4
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