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

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1. |
Introduction to Information Theory for Discrete Variables: Entropy, Mutual Information, and Divergence |
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2. |
Information Theory Inequalities |
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3. |
Typical sequences and Asymptotic Equipartition Property |
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4. |
Coding of Discrete Memoryless Sources |
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5. |
Coding of Discrete Stationary Sources |
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6. |
Noisy channel coding theorem and joint typicality |
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7. |
Channel capacity |
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8. |
Introduction to Information Theory for Continuous Variables: Differential Entropy |
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9. |
Gaussian channel, parallel Gaussian channel |
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10. |
Rate Distortion Theory |
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11. |
Distributed lossless compression: Slepian Wolf coding |
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12. |
Lossy Source Coding with Side Information: Wyner-Ziv coding |
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13. |
Coding for Channels with State |
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14. |
An introduction to Broadcast Channels |
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15. |
An introduction to Multiple Access Channels |
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16. |
An introduction to Interference Channels |
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17. |
An introduction to Relay Channels |
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18. |
Memoryless Networks |