LEC # | TOPICS | KEY DATES |
---|---|---|

1 | Introduction, entropy | |

2 | Jensen’s inequality, data processing theorem, Fanos’s inequality | |

3 | Different types of convergence, asymptotic equipartition property (AEP), typical set, joint typicality | |

4 | Entropies of stochastic processes | Problem set 1 due |

5 | Data compression, Kraft inequality, optimal codes | Problem set 2 due |

6 | Huffman codes | Problem set 3 due |

7 | Shannon-Fano-Elias codes, Slepian-Wolf | |

8 | Channel capacity, binary symmetric and erasure channels | |

9 | Maximizing capacity, Blahut-Arimoto | Problem set 4 due |

10 | The channel coding theorem | |

11 | Strong coding theorem, types of errors | Problem set 5 due |

12 | Strong coding theorem, error exponents | |

In-class midterm | ||

13 | Fano’s inequality and the converse to the coding theorem | Problem set 6 due |

14 | Feedback capacity | |

15 | Joint source channel coding | Problem set 7 due |

16 | Differential entropy, maximizing entropy | |

17 | Additive Gaussian noise channel | Problem set 8 due |

18 | Gaussian channels: parallel, colored noise, inter-symbol interference | |

19 | Gaussian channels with feedback | Problem set 9 due |

20 | Multiple access channels | |

21 | Broadcast channels | Problem set 10 due |

In-class presentations (2 sessions) | ||

22 | Finite state Markov channels | |

23 | Channel side information, wide-band channels |

## Calendar

## Course Info

##### Instructor

##### Departments

##### As Taught In

Spring
2010

##### Level

##### Topics

##### Learning Resource Types

*assignment*Problem Sets

*notes*Lecture Notes