Recovery of Sparse Signals Using Multiple Orthogonal Least Squares

  title={Recovery of Sparse Signals Using Multiple Orthogonal Least Squares},
  author={Jian Wang and Ping Li},
  journal={IEEE Transactions on Signal Processing},
Sparse recovery aims to reconstruct sparse signals from compressed linear measurements. In this paper, we propose a sparse recovery algorithm called multiple orthogonal least squares (MOLS), which extends the well-known orthogonal least squares (OLS) algorithm by allowing multiple <inline-formula><tex-math notation="LaTeX">$L$</tex-math> </inline-formula> indices to be selected per iteration. Owing to its ability to catch multiple support indices in each selection, MOLS often converges in fewer… CONTINUE READING
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