Linear Complexity Lossy Compressor for Binary Redundant Memoryless   Sources
  A lossy compression algorithm for binary redundant memoryless sources is presented. The proposed scheme is based on sparse graph codes. By introducing a nonlinear function, redundant memoryless sequences can be compressed. We propose a linear complexity compressor based on the extended belief propagation, into which an inertia term is heuristically introduced, and show that it has near-optimal performance for moderate block lengths. 
Kazushi Mimura
cs.IT cond-mat.dis-nn math.IT