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0. Consider the conditional entropy and mutual information for the binary symmetric channel. The input source has alphabet X = {0, 1} and associated probabilities {1 / 2, 1 / 2}. The channel matrix is where p is the transition probability. Then the conditional entropy is given by:
1
- plog(p) - (1 - p)log(1 - p)
1 + p log(p) + (1 - p)log(1 - p)
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where p is the transition probability. Then the conditional entropy is given by:
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