  Accurate modeling of the correlation between the sources plays a crucial role
in the efficiency of distributed source coding (DSC) systems. This correlation
is commonly modeled in the binary domain by using a single binary symmetric
channel (BSC), both for binary and continuous-valued sources. We show that
"one" BSC cannot accurately capture the correlation between continuous-valued
sources; a more accurate model requires "multiple" BSCs, as many as the number
of bits used to represent each sample. We incorporate this new model into the
DSC system that uses low-density parity-check (LDPC) codes for compression. The
standard Slepian-Wolf LDPC decoder requires a slight modification so that the
parameters of all BSCs are integrated in the log-likelihood ratios (LLRs).
Further, using an interleaver the data belonging to different bit-planes are
shuffled to introduce randomness in the binary domain. The new system has the
same complexity and delay as the standard one. Simulation results prove the
effectiveness of the proposed model and system.
