| 1 | Signing Up
First Reading Assignment
Lecture #1 | (PDF) |
| 2 | Channels
Capacity and Mutual Information | (PDF) |
| 3 | Analysis of Repetition Code Meta-channel
Capacity of Meta-channel
Prior, Extrinsic, Posterior and Intrinsic Probabilities | (PDF) |
| 4 | Prior, Extrinsic and Posterior Probabilities, II
Normalizing Constants
Example: Symmetric Channels
Decoding Codes
Example: Parity | (PDF) |
| 5 | Parity Continued
The Gaussian Distribution
The Gaussian and Erasure Channels
The Parity Product Code
BER
Heuristic Decoding of the Parity Product Code
Confidence Intervals
How big should N be?
Plotting in MATLAB® | (PDF) |
| 6 | Introduction
Two Variables
Simplifying Computations
Three Variables
Trees | (PDF) |
| 7 | Markov Property
Simplifying Probability Computation | (PDF) |
| 8 | Vector Spaces
Duals of vector spaces
Codes and Matrices | (PDF) |
| 9 | LDPC Codes
Decoding
SNR, dB | (PDF) |
| 10 | In-class debugging session | |
| 11 | Belief Propagation on Trees
Dynamic Programming
Infnite Trees
Small Project 2 | (PDF) |
| 12 | Representing Probabilities, Equality Nodes
Representing Probabilities, Parity Nodes | (PDF) |
| 13 | The Binary Erasure Channel
Analysis of LDPC on BEC
Making the Analysis Rigorous on Trees
Using the Polynomials
Capacity Estimation, Revisited | (PDF) |
| 14 | Convolutional Codes
Trellis Representation
Decoding Convolutional Codes | (PDF) |
| 15 | Remarks on Convolutional Codes
Turbo Codes
Decoding
Exit Charts | (PDF) |
| 16 | Decoding Modules
Final Projects | (PDF) |
| 17 | Developments in Iterative Decoding
Achieving Capacity on the BEC
Encoding
Density Evolution
Exit Charts, Revisited
Why we use bad codes to make good codes? | (PDF) |