1. A computer-implemented method for decompression in data compression systems comprising: partitioning a plurality of decoder side-information signals into a plurality of subsets, wherein the decoder side-information signals include pre-stored and received statistical information; determining a conditional probability function for each of the subsets of the decoder side-information signals; estimating a plurality of a-posteriori probability functions of a source signal, each a-posteriori probability function based on a respective one of the conditional probability functions and extrinsic information; evaluating a stopping criterion for decompression given the plurality of a-posteriori probability functions; generating the extrinsic information based on the a-posteriori probability functions; and determining a likelihood threshold for determining a most probable value of quantized source signal based on the a-posteriori probability functions and outputting the quantized source upon determining to stop decompression, wherein the extrinsic information is generated using the following equation E 1 ⁡ ( X ) = λ 0 ⁢ f ⁡ ( X ) + ∑ i ∈ { 1 , … ⁢ , K } , i ∈ 1 ⁢ λ i ⁢ Q i ⁡ ( X ) , wherein E 1 (X) is an extrinsic information function, Q i (X) is an a-posteriori probability function, f(X) is a marginal probability distribution of the source signal, K is a number of a-posteriori probability functions, and λ are weights fixed or determined on the basis of f(X) or Q i (X).