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Smoothing Strategy Along with Conjugate Gradient Algorithm for Signal Reconstruction

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Abstract

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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Acknowledgements

The authors would like to thank the anonymous referees for their valuable comments and suggestions which have significantly improved the original version of the paper.

Funding

Caiying Wu and Jing Wang are supported by the Natural Science Foundation of Inner Mongolia Autonomous Region (2018MS01016). Jan Harold Alcantara and Jein-Shan Chen are supported by the Ministry of Science and Technology, Taiwan.

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Authors and Affiliations

  1. College of Mathematics Science, Inner Mongolia University, Hohhot, 010021, China

    Caiying Wu & Jing Wang

  2. Department of Mathematics, National Taiwan Normal University, Taipei, 11677, Taiwan

    Jan Harold Alcantara & Jein-Shan Chen

  3. Mathematics and Statistics Department, De La Salle University, Manila, 1004, Philippines

    Jan Harold Alcantara

Authors
  1. Caiying Wu
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  2. Jing Wang
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  3. Jan Harold Alcantara
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  4. Jein-Shan Chen
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Correspondence to Jein-Shan Chen.

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Caiying Wu, Jing Wang, research is supported by the Natural Science Foundation of Inner Mongolia Autonomous Region (2018MS01016). Jan Harold Alcantara, Jein-Shan Chen, research is supported by Ministry of Science and Technology, Taiwan.

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Wu, C., Wang, J., Alcantara, J.H. et al. Smoothing Strategy Along with Conjugate Gradient Algorithm for Signal Reconstruction. J Sci Comput 87, 21 (2021). https://doi.org/10.1007/s10915-021-01440-z

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  • DOI: https://doi.org/10.1007/s10915-021-01440-z

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