Lossy data compression with random gates.
We introduce a new protocol for a lossy data compression algorithm which is based on constraint satisfaction gates. We show that the theoretical capacity of algorithms built from standard parity-check gates converges exponentially fast to the Shannon's bound when the number of variables seen by each gate increases. We then generalize this approach by introducing random gates. They have theoretical performances nearly as good as parity checks, but they offer the great advantage that the encoding can be done in linear time using the survey inspired decimation algorithm, a powerful algorithm for constraint satisfaction problems derived from statistical physics.
Ciliberti
Stefano
S
Laboratoire de Physique Théorique et Modèles Statistiques, Université de Paris-Sud, Bâtiment 100, 91405 Orsay Cedex, France.
Mézard
Marc
M
Zecchina
Riccardo
R