Network Information Theory
GIAN Course on
Organized by
Department of Electrical Engineering, IIT Kanpur
and supported by MHRD under GIAN (Global Initiative of Academic Networks)
March 15th - 24th 2018
1. |
Introduction to Information Theory for Discrete Variables: Entropy, Mutual Information, and Divergence |
2. |
Information Theory Inequalities |
3. |
Typical sequences and Asymptotic Equipartition Property |
4. |
Coding of Discrete Memoryless Sources |
5. |
Coding of Discrete Stationary Sources |
6. |
Noisy channel coding theorem and joint typicality |
7. |
Channel capacity |
8. |
Introduction to Information Theory for Continuous Variables: Differential Entropy |
9. |
Gaussian channel, parallel Gaussian channel |
10. |
Rate Distortion Theory |
11. |
Distributed lossless compression: Slepian Wolf coding |
12. |
Lossy Source Coding with Side Information: Wyner-Ziv coding |
13. |
Coding for Channels with State |
14. |
An introduction to Broadcast Channels |
15. |
An introduction to Multiple Access Channels |
16. |
An introduction to Interference Channels |
17. |
An introduction to Relay Channels |
18. |
Memoryless Networks |