Soft decision decoding with unknown source distribution

A soft decision approach is given for decoding the output of a noisy binary communication system with an unknown source probability distribution and a memoryless channel. The novelty of our procedure is the use of probabilistic conditional confidence coefficients as a measure of reliability, leading to a conditional maximum likelihood decoding rule.