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Many applications that involve inference and learning in signal processing, communication and artificial intelligence can be cast into a graph framework. Factor graphs are a type of network that can be studied and solved by propagating belief messages with the sum/product algorithm. In this paper we provide explicit matrix formulas for inference and learning in finite alphabet Forney-style factor graphs, with the precise intent of allowing rapid prototyping of arbitrary topologies in standard software like MATLAB.
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