Near rate-distortion bound performance of sparse matrix codes

We study an ill-posed linear inverse problem, where a binary sequence will be reproduced using a sparse matrix of LDPC type. We propose an iterative algorithm based on belief propagation technique. Numerical results show that the algorithm can empirically saturate the theoretical limit for the sparse construction of our codes, which also is very close to the rate-distortion function itself.