---- dataentry project ----
title :  Expectation Propagation Decoding   
contactname: Masoud Alipour
contactmail_mail: masoud.alipour@epfl.ch
contacttel: 021 6937529
contactroom: BC 150
type : master semester 
state : unavailable
created_dt : 2009-06-03
taken_dt :  
completed_dt : 
by : 
output_media : 
table : projects
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**Expectation Propagation** is a method for approximate inference in Graphical Models. The aim of this project is to treat the tanner graph of LDPC code as a graphical model and to use EP technique for decoding. The proportion of theoretical and empirical (programming, simulation) work in this project is 40-60 percent.

Requirement:
  * Good familiarity with basic probability theory
  * Good programming skills in Matlab and/or C/C++
What will you learn
  * LDPC codes
  * Learning and Inference in Graphical Models
  * Expectation Propagation
  * Fast implementation of approximate inference in graphical models
Suggested Readings and References 
  * [[http://research.microsoft.com/en-us/um/people/minka/papers/ep/|Thomas Minka's EP page]]
  * [[http://videolectures.net/abi07_walsh_cip/|A Completed Information Projection Interpretation of Expectation Propagation]]