A modified reconstruction algorithm for compressed sensing with least square residual - Shengqi Liu; Ronghui Zhan; Qinglin Zhai; Jiemin Hu; Jun Zhang (2015 International Conference on Communications and Signal Processing (ICCSP), 2015)
L 1 -norm based solver has been successfully used for sparse signal reconstruction in compressed sensing. In the paper, we propose a modified method to boost the decoding performance with least-square residual for L 1 algorithms. A further performance improvement is obtained by applying iteratively reweighted L 1 minimization for sparsity pattern detection. Numerical experiments show that both the proposed methods lead to a better sparsity-measurement tradeoff than their benchmark algorithms.