Nonconvex compressed sensing with partially known signal support

We study recovering sparse and compressible signals using I-p minimization with p < 1 when some part of the support of the signal is known a priori. Sparse reconstruction method based on I-p minimization with partially known set is proposed and recovery conditions are given. Theoretical results show that I-p minimization with partially known support is stable and robust. Experimental results are presented to expose the modification of I-p minimization improves performance and need fewer samples to reconstruct the signal. (C) 2012 Elsevier B.V. All rights reserved.