Smoothing Strategy Along with Conjugate Gradient Algorithm for Signal Reconstruction

被引:0
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作者
Caiying Wu
Jing Wang
Jan Harold Alcantara
Jein-Shan Chen
机构
[1] Inner Mongolia University,College of Mathematics Science
[2] National Taiwan Normal University,Department of Mathematics
[3] De La Salle University,Mathematics and Statistics Department
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关键词
-norm regularization; Signal recovery; Conjugate gradient algorithm; Sparse solution; 90C33;
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摘要
In this paper, we propose a new smoothing strategy along with conjugate gradient algorithm for the signal reconstruction problem. Theoretically, the proposed conjugate gradient algorithm along with the smoothing functions for the absolute value function is shown to possess some nice properties which guarantee global convergence. Numerical experiments and comparisons suggest that the proposed algorithm is an efficient approach for sparse recovery. Moreover, we demonstrate that the approach has some advantages over some existing solvers for the signal reconstruction problem.
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