Exploiting Prior Knowledge in the Recovery of Non-Sparse Signals from Noisy Random Projections

This paper illustrates that exploiting the source statistics in the recovery process results in significant performance gains, even if the signal is reconstructed in a basis in which it does not admit a sparse representation. Successful recovery will depend on the capability of exploiting all available a priori information in the basis where reconstruction is performed. The proposed framework is similar to joint source-channel coding schemes in digital communications, but applies on the analog domain.