Information Theory And Error Control Coding - Crash Course

Information Theory for Digital Communication

What you'll learn
Information Theory in Digital Communication
Basic Knowledge of Information Theory and Error Control Coding
Digital Communication, Error Correcting Codes, Source Coding
Probability and Random Process
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 made from Digital Communication Point of View.3. If you have any experience in any Communication related Courses prior to this then you can have a look.4. The Prerequisites required are mentioned in the Course Introduction Video.5. This is a Theoretical and Analytical Course.6. This Course is exclusively made from Beginners point of view.7. If you want to learn Applying Probability on Digital Communication.8. Solutions of Each Problem will be in Detail.8. You will be able to learn different topics with this Course like Entropy, Joint Conditional Probability, Source Coding Error Correction.9. You will be able to Imagine this Course Visually after finishing this Course.Information Theory and Error Correcting Codes is one of the Difficult Subjects in the Field of Electronics and Communication - You will learn it easily on this Course.Q:- Will the course teach me Analog or Digital Communication?A:- No, This topic is dealt in separate Course called Analog Communication and Digital Communication, and they require separate Attention all together.With over 3+ Years of Experience and a 4.0 Instructor Rating in Udemy, I am Coming Up with Core Electronics and Communication Course of more than 4+ Hours of Theory and Problem Solving called Information Theory and Error Control Coding - Crash Course.The curriculum was developed over a period of 4 Months.If you are satisfied in any way, Check out my other Courses as well.So what are you waiting for? Click the buy now button and join me on this Wonderful course.

Overview

Section 1: Course Introduction

Lecture 1 Course Introduction

Section 2: Information

Lecture 2 Introduction

Lecture 3 Information

Lecture 4 Entropy

Lecture 5 Information Rate

Lecture 6 Summary of Information, Entropy and Information Rate

Section 3: Source Coding Techniques

Lecture 7 Source Coding Techniques

Lecture 8 Shannon Fano Coding

Lecture 9 Hofmann Coding

Lecture 10 Summary

Section 4: Binary Channels

Lecture 11 Conditional Probability Matrix

Lecture 12 Joint Probability Matrix

Lecture 13 Summary of CPM JPM

Lecture 14 Binary Channels

Lecture 15 Examples on Binary Channels

Lecture 16 Conditional and Joint Entropy

Lecture 17 Caution Point

Section 5: Mutual Information and Channel Capacity

Lecture 18 Mutual Information

Lecture 19 Channel Capacity

Lecture 20 AWGN Channel

Section 6: Error Control Coding

Lecture 21 Introduction to Error Control Coding

Lecture 22 Hamming Weight and Hamming Distance

Lecture 23 Generator Matrix

Lecture 24 Example on LBC

Lecture 25 Error Detection and Error Correction of LBC

Lecture 26 Parity Check Matrix

Lecture 27 Caution on G and H

Lecture 28 Syndrome Decoding

Lecture 29 Error and Detection of Syndrome Decoding

Lecture 30 Hamming Bound and Hamming Code

Lecture 31 Kraft's Inequality

Lecture 32 Special Channels

Lecture 33 Convolution Code

Lecture 34 Viterbi Algorithm

Lecture 35 Repetition of Input

Lecture 36 Repetition of Input Example

Lecture 37 Repetition of Input Example 2

Lecture 38 Different Codes

Section 7: Conclusion

Lecture 39 Few Extra Points

Lecture 40 Course Conclusion

Lecture 41 Thank You Note

Electronics and Telecommunication,Who had prior experience in some Communication Courses