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Digital Signal Processing 4: Applications 

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Digital Signal Processing 4: Applications
 at 
Coursera 
Overview

Duration

14 hours

Total fee

Free

Mode of learning

Online

Difficulty level

Intermediate

Official Website

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Credential

Certificate

Digital Signal Processing 4: Applications
Table of content
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  • Overview
  • Highlights
  • Course Details
  • Curriculum

Digital Signal Processing 4: Applications
 at 
Coursera 
Highlights

  • This Course Plus the Full Specialization.
  • Shareable Certificates.
  • Graded Programming Assignments.
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Digital Signal Processing 4: Applications
 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 4: Applications
 at 
Coursera 
Curriculum

IMAGE PROCESSING

4.1.1.a Notation and key concepts

4.1.1.b Image manipulations

4.1.2 Frequency analysis

4.1.3.a 2D Filters

4.1.3.b Classic Filters for Images

4.1.4.a Image compression

4.1.4.b The JPEG compression algorithm

Signal of the Day: Moire Patterns

Welcome to DSP Four!

Introduction

Introduction

Introduction

Introduction

Practice Homework

Homework for Module 4.1

DIGITAL COMMUNICATIONS AND ADSL

4.2.1.a The success factors for digital communications

4.2.1.b The analog channel constraints

4.2.1.c The design problem

4.2.2.a Upsampling

4.2.2.b Fitting the transmitter spectrum

4.2.2.c Noise and probability of error

4.2.2.d PAM and QAM

4.2.3.a Modulation and demodulation

4.2.3.b Design example

4.2.3.c Receiver design

4.2.3.d Delay compensation

4.2.3.e Adaptive equalization

4.2.4.a ADSL design

4.2.4.b Discrete multitone modulation

Introduction

What have we learned?

Introduction

What have we learned?

Introduction

What have we learned?

Introduction

What have we learned?

Practice homework

Further reading

Homework for Module 4.2

MODULE 4.3: REAL-TIME AUDIO SIGNAL PROCESSING

Breakout board assembly

Wiring up everything

Oscilloscope overview, analog mode

Oscilloscope overview, digital mode

Introduction

The "Voice Transformer" Notebook

Prepare the breakout boards

Introduction

Introduction

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Digital Signal Processing 4: Applications
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