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en:projects:details:har02 [2009/06/05 10:26]
cronie removed
en:projects:details:har02 [2009/06/05 23:04]
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-=== The football match problem === 
-In a football match problem with n games there are n pairs of teams playing playing ​ 
-against one another. The outcome of every game is given by the numbers 0, 1, and 2,  
-according to whether the game was a draw, whether the home team won, or whether ​ 
-the home team lost. It is possible to bet on the outcomes of these games. A series of n  
-bets gives a win if at most 2 of the games in the series were predicted in error. ​ 
-The classical problem asks for the smallest number of bets such that, no matter the 
-outcome, there is a winning bet.  
-This problem can be solved with coding theory. We can identify the possible outcomes ​ 
-of the games by a vector of length n over the field GF(3). The task is to find the smallest ​ 
-number of vectors (=bets) such that any vector in GF(3)^n (=outcome of the games) has  
-Hamming distance at most 2 from a bet.  
-In this project we are interested in a soft version of this problem in which there are prior  
-probabilities for the outcome of each game, and there is a confidence level, P; the task is  
-to find the smallest number of bets such that, given the prior probabilities,​ with probability ​ 
-at most P none of the bets wins. The student should study optimization techniques for  
-finding a good set of bets.  
 ---- dataentry project ---- ---- dataentry project ----
-title : The football match problem+title : Joint Source Channel Coding for Image Transmission
 contactname:​ Harm Cronie contactname:​ Harm Cronie
 contactmail_mail:​ harm.cronie@epfl.ch contactmail_mail:​ harm.cronie@epfl.ch
-contacttel: 021 6931205 +contacttel: 021 6936793 
-contactroom: ​BC 150 +contactroom: ​BC150 
-type : bachelor ​semester+type : master ​semester
 status : available status : available
 +created_dt : 2009-06-05
 +taken_dt :  YYYY-MM-DD
 +completed_dt : YYYY-MM-DD
 table : projects table : projects
-created_dt : 2009-01-01 
-taken_dt :  
-completed_dt : 
-by :  
-output_media : 
 ====== ======
 template:​datatemplates:​project template:​datatemplates:​project
 ---- ----
 +In this assignment we consider the efficient transmission of images
 +over a noisy channel. On one hand we would like to represent the image
 +with as less bits as possible. This is done by image compression
 +methods such as jpeg compression. On the other hand we need some
 +redundancy in the form of an error-correcting code to ensure reliable
 +transmission over the channel. Traditionally,​ these two tasks are
 +solved separately. One of the disadvantages of this approach is that a
 +few residual errors after decoding the error-correcting code usually
 +lead to a very large error in image reconstruction.
 +Joint source channel coding methods can provide a finer trade-off
 +between the image reconstruction quality and the amount of noise the
 +system can deal with. In this assignment you will implement signal
 +processing algorithms to represent an image efficiently. These methods
 +include image transforms such as the discrete cosine transform and
 +quantization. After this signal processing stage, a Raptor code can be
 +applied to allow for reliable transmission over the channel. The goal
 +is to reconstruct the image at the receiver side with as less
 +distortion as possible given the signal to noise ratio of the channel.