  Compressed sensing of sparse sources can be improved by incorporating prior
knowledge of the source. In this paper we demonstrate a method for optimal
selection of weights in weighted $L_1$ norm minimization for a noiseless
reconstruction model, and show the improvements in compression that can be
achieved.
