On convergence of iterative thresholding algorithms to approximate sparse solution for composite nonconvex optimization
Yaohua Hu,
Xinlin Hu,
Xiaoqi Yang
Abstract:This paper aims to find an approximate true sparse solution of an underdetermined linear system. For this purpose, we propose two types of iterative thresholding algorithms with the continuation technique and the truncation technique respectively. We introduce a notion of limited shrinkage thresholding operator and apply it, together with the restricted isometry property, to show that the proposed algorithms converge to an approximate true sparse solution within a tolerance relevant to the noise level and the … Show more
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