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Second order self-adaptive dynamical system for sparse signal reconstruction and applications to image recovery

Author

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  • Che, Haitao
  • Liu, Kaiping
  • Chen, Haibin
  • Yan, Hong

Abstract

In this article, we consider sparse signal reconstruction problems by an alternative second order self-adaptive dynamical system. By split feasibility problem of sparse signal reconstruction, we introduce a new second order self-adaptive dynamical system. Then, we prove that the proposed system has a unique solution under reasonable conditions. Furthermore, it is shown that the corresponding orbit of the system always converges. Finally, all kinds of numerical results on synthetic data and data from practical problems verify the efficiency of the proposed approach.

Suggested Citation

  • Che, Haitao & Liu, Kaiping & Chen, Haibin & Yan, Hong, 2023. "Second order self-adaptive dynamical system for sparse signal reconstruction and applications to image recovery," Applied Mathematics and Computation, Elsevier, vol. 451(C).
    • Handle: RePEc:eee:apmaco:v:451:y:2023:i:c:s0096300323001881
    DOI: 10.1016/j.amc.2023.128019
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    References listed on IDEAS

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    1. Haiying Li & Yulian Wu & Fenghui Wang & Xiaolong Qin, 2021. "New Inertial Relaxed CQ Algorithms for Solving Split Feasibility Problems in Hilbert Spaces," Journal of Mathematics, Hindawi, vol. 2021, pages 1-13, February.
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    Cited by:

    1. Yue, Yuanyuan & Liu, Qingshan, 2024. "Distributed dual consensus algorithm for time-varying optimization with coupled equality constraint," Applied Mathematics and Computation, Elsevier, vol. 474(C).

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