Compressed Sensing Construction for Underdetermined Source Separation.

Underdetermined blind source separation based on compressed sensing (CS) has already been proven to be an effective mechanism from an experimental viewpoint. In this study, we develop a theoretical result and show that, under a certain sparsity constraint for the restricted isometry property, the accuracy of CS when retrieving sources is guaranteed. This theoretical result can be regarded as a generalization of the blocked polynomial deterministic matrix theory and has been confirmed using numerical examples. [ABSTRACT FROM AUTHOR]