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Digital Signal Processing 3: Analog vs Digital 

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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

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Credential

Certificate

Digital Signal Processing 3: Analog vs Digital
Table of content
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  • Overview
  • Highlights
  • Course Details
  • Curriculum

Digital Signal Processing 3: Analog vs Digital
 at 
Coursera 
Highlights

  • This Course Plus the Full Specialization.
  • Shareable Certificates.
  • Graded Programming Assignments.
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Digital Signal Processing 3: Analog vs Digital
 at 
Coursera 
Course details

Skills you will learn
More about this course
  • 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.
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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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Digital Signal Processing 3: Analog vs Digital
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