IEEE Transactions on Information Theory · 1974 · 5.2K citations · 5 references
EngineeringElectrical EngineeringMathematicsDigital CommunicationInformation TheoryProbability TheoryChannel CodingChannel EstimationCoding TheoryError Control CodingError DetectionError-correcting CodesA Posteriori KnowledgeConvolutional CodesDecoding AlgorithmsDiscrete Memoryless ChannelsLinear Block CodesLinear CodesMarkov StatesMaximum-likelihood Decoding
The general problem of estimating the a posteriori probabilities of the states and transitions of a Markov source observed through a discrete memoryless channel is considered. The decoding of linear block and convolutional codes to minimize symbol error probability is shown to be a special case of this problem. An optimal decoding algorithm is derived.
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