Recovering sparse signals from a few linear measurements is attracting growing attention. Bsides sparsity, the signals usually are nonnegative, nonpositive or restricted in some domain. This paper proposes an algorithm for recovering the sparse signal with some certain property on learning the sparsity. We propose this algorithm by combining the projective method with the iterative hard thresholding...
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.