Information Theory

Description

After completing this course, the student should be able to:

• Demonstrate knowledge and understanding of the fundamentals of information theory at the end of this course.
• Understand the concept of fundamental limits in communication systems, and more broadly in all systems.
• Gain a more in-depth understanding of communication systems.
• Apply information theory concepts to various disciplines in information science.

Syllabus :

1. (A) Course Preliminaries

• About this course

 

(B) Chapter 1 Information Measures 

• Week 1 Introduction
• Chapter 

 

(C) Chapter 2 Information Measures - Part 1

• Chapter 2 - Section 2.1 A
• Chapter 2 - Section 2.1 B
• Chapter 2 - Section 2.1 C
• Chapter 2 - Section 2.2
• Chapter 2 - Section 2.3

 

2. Chapter 2 Information Measures - Part 2

• Week 2 Introduction
• Chapter 2 - Section 2.4
• Chapter 2 - Section 2.5
• Chapter 2 - Section 2.6
• Chapter 2 - Section 2.7
• Chapter 2 - Section 2.8
• Chapter 2 - Section 2.10

 

3. Chapter 3 The I-Measure - Part 1

• Week 3 Introduction
• Chapter 3 - Section 3.1
• Chapter 3 - Section 3.3 A
• Chapter 3 - Section 3.3 B
• Chapter 3 - Section 3.4
• Chapter 3 - Section 3.5 A

 

4. (A) Chapter 3 The I-Measure - Part 2

• Week 4 Introduction
• Chapter 3 - Section 3.5 B
• Chapter 3 - Section 3.6 A
• Chapter 3 - Section 3.6 B

 

(B) Chapter 4 Zero-Error Data Compression - Part 1

• Chapter 4 - Section 4.1
• Chapter 4 - Section 4.2 A
• Assignment 4 Video Preview

 

5. (A) Chapter 4 Zero-Error Data Compression - Part 2

• Week 5 Introduction
• Chapter 4 - Section 4.2 B
• Chapter 4 - Section 4.2 C
• Chapter 4 - Section 4.3

 

(B) Chapter 5 Weak Typicality

• Chapter 5 - Section 5.1
• Chapter 5 -Section 5.2
• Assignment 5 Video Preview

 

6. Chapter 6 Strong Typicality

• Week 6 - Introduction
• Chapter 6 - Section 6.1 A
• Chapter 6 - Section 6.1 B
• Chapter 6 - Section 6.2
• Chapter 6 - Section 6.3 A
• Chapter 6 - Section 6.3 B
• Chapter 6 - Section 6.4
• Assignment 6 Video Preview

 

7. Chapter 7 Discrete Memoryless Channels - Part 1

• Week 7 Introduction
• Chapter 7 - Section 7.1 A
• Chapter 7 - Section 7.1 B
• Chapter 7 - Section 7.2
• Chapter 7 - Section 7.3 A
• Chapter 7 - Section 7.3 B

 

8. Chapter 7 Discrete Memoryless Channels - Part 2

• Week 8 Introduction
• Chapter 7 - Section 7.4 A
• Chapter 7 - Section 7.4 B
• Chapter 7 - Section 7.5
• Chapter 7 - Section 7.6
• Chapter 7 - Section 7.7

 

9. Chapter 8 Rate-Distortion Theory - Part 1

• Week 9 Introduction
• Chapter 8 - Section 8.1
• Chapter 8 - Section 8.2
• Chapter 8 - Section 8.3 A
• Chapter 8 - Section 8.3 B
• Chapter 8 - Section 8.4

 

10. (A) Chapter 8 Rate-Distortion Theory - Part 2

• Week 10 Introduction
• Chapter 8 - Section 8.5 A
• Chapter 8 - Section 8.5 B

 

(B) Chapter 9 The Blahut-Arimoto Algorithms - Part 1

• Chapter 9 - Section 9.1
• Chapter 9 - Section 9.2 A
• Chapter 9 - Section 9.2 B
• Assignment 10 Video Preview

 

11. (A) Chapter 9 The Blahut-Arimoto Algorithms - Part 2

• Week 11 Introduction
• Chapter 9 - Section 9.2 C
• Chapter 9 - Section 9.3

 

(B) Chapter 10 Differential Entropy - Part 1

• Chapter 10 - Section 10.1 A
• Chapter 10 - Section 10.1 B

 

12. Chapter 10 Differential Entropy - Part 2

• Week 12 Introduction
• Chapter 10 - Section 10.2
• Chapter 10 - Section 10.3 A
• Chapter 10 - Section 10.3 B
• Chapter 10 - Section 10.4
• Chapter 10 - Section 10.5
• Chapter 10 - Section 10.62

 

13. Chapter 11 Continuous-Valued Channels - Part 1

• Week 13 Introduction
• Chapter 11 - Section 11.1
• Chapter 11 - Section 11.2
• Chapter 11 - Section 11.3 A
• Chapter 11 - Section 11.3 B

 

14. Chapter 11 Continuous-Valued Channels - Part 2

• Week 14 Introduction
• Chapter 11 - Section 11.4
• Chapter 11 - Section 11.5
• Chapter 11 - Section 11.6

 

15. Chapter 11 Continuous-Valued Channels - Part 3

• Week 15 Introduction
• Chapter 11 - Section 11.7 A
• Chapter 11 - Section 11.7 B
• Chapter 11 - Section 11.81
• Chapter 11 - Section 11.91

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