| 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 |
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| 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) |