Error-correcting Codes on a Bethe-like Lattice

Vicente, Renato, Saad, David, Kabashima, Yoshiyuki

Neural Information Processing Systems 

We analyze Gallager codes by employing a simple mean-field approximation that distorts the model geometry and preserves important interactions between sites. The method naturally recovers the probability propagation decoding algorithm as an extremization of a proper free-energy. We find a thermodynamic phase transition that coincides with information theoretical upper-bounds and explain the practical code performance in terms of the free-energy landscape.

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