Information Theory and Error Control Coding
4.4 (23 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
73 students enrolled

Information Theory and Error Control Coding

Information Theory for Digital Communication
4.4 (23 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
73 students enrolled
Created by J P
Last updated 4/2020
English
Current price: $69.99 Original price: $99.99 Discount: 30% off
5 hours left at this price!
30-Day Money-Back Guarantee
This course includes
  • 3 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
Training 5 or more people?

Get your team access to 4,000+ top Udemy courses anytime, anywhere.

Try Udemy for Business
What you'll learn
  • Information Theory in Digital Communication
  • Basic Knowledge of Information Theory and Error Control Coding
Requirements
  • Basic Knowledge of Digital Communication
  • Basic Knowledge of Analog Communication
  • Basics of Probability Theory
  • Basics of Matrix Theory
Description

1.This Course is for Students having background in Electronics and Telecommunication or any relevant stream.

2.This Course is exclusively made from Digital Communication point of view.

3. If you have any experience in any Communication Course prior then you can have a look.

4.The Prerequisites required are mentioned in the Course Introduction Video.

5.This is a Theoretical and Mathematical Course.

Who this course is for:
  • Electronics and Telecommunication
  • Who had prior experience in some Communication Courses
Course content
Expand all 35 lectures 02:52:38
+ Information
5 lectures 18:50
Entropy
06:22
Information Rate
02:47
Summary of Information, Entropy and Information Rate
01:00
+ Source Coding Techniques
4 lectures 22:51
Source Coding Techniques
05:07
Shannon Fano Coding
08:51
Hofmann Coding
07:37
Summary
01:16
+ Binary Channels
7 lectures 44:14
Conditional Probability Matrix
07:38
Joint Probability Matrix
04:50
Summary of CPM JPM
01:05
Binary Channels
05:13
Examples on Binary Channels
11:17
Conditional and Joint Entropy
10:17
Caution Point
03:54
+ Mutual Information and Channel Capacity
3 lectures 15:53
Mutual Information
02:23
Channel Capacity
03:35
AWGN Channel
09:55
+ Error Control Coding
12 lectures 47:30
Introduction to Error Control Coding
03:34
Hamming Weight and Hamming Distance
02:35
Generator Matrix
05:20
Example on LBC
05:06
Error Detection and Error Correction of LBC
02:28
Parity Check Matrix
01:27
Caution on G and H
01:17
Syndrome Decoding
06:03
Error and Detection of Syndrome Decoding
01:44
Hamming Bound and Hamming Code
03:05
Kraft's Inequality
08:14
Special Channels
06:37
+ Conclusion
3 lectures 18:33
Few Extra Points
11:26
Course Conclusion
06:15
Thank You Note
00:52