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Factor graphs and the sum-product algorithm

IEEE Transactions on Information Theory · 2001 · Vol. 47(2) · pp. 498–519
Frank R. KschischangBrendan J. FreyHans‐Andrea Loeliger

Abstract

Algorithms that must deal with complicated global functions of many variables often exploit the manner in which the given functions factor as a product of "local" functions, each of which depends on a subset of the variables. Such a factorization can be visualized with a bipartite graph that we call a factor graph, In this tutorial paper, we present a generic message-passing algorithm, the sum-product algorithm, that operates in a factor graph. Following a single, simple computational rule, the sum-product algorithm computes-either exactly or approximately-various marginal functions derived from the global function. A wide variety of algorithms developed in artificial intelligence, signal processing, and digital communications can be derived as specific instances of the sum-product algorithm, including the forward/backward algorithm, the Viterbi algorithm, the iterative "turbo" decoding algorithm, Pearl's (1988) belief propagation algorithm for Bayesian networks, the Kalman filter, and certain fast Fourier transform (FFT) algorithms.

Error Correcting Code TechniquesAlgorithms and Data CompressionBayesian Modeling and Causal InferenceFactor graphAlgorithmComputer sciencePrime-factor FFT algorithmViterbi algorithmBipartite graphMathematicsGraphDecoding methodsTheoretical computer science

Funding

  • Massachusetts Institute of Technology
Citations
6,415
FWCI
118.26
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References
37
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100%
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