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For a received word , the ideal-observer rule chooses a message maximizing the posterior probability
Maximum-likelihood decoding chooses maximizing
and minimum-distance decoding chooses a codeword minimizing its Hamming distance from .
Bayes' formula gives
Equal message priors therefore make ideal-observer and maximum-likelihood decoding identical. On a binary symmetric channel, if , then
For , this strictly decreases with , so maximum likelihood and minimum distance agree.
Solved by gpt-5.6-sol high.

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