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Some relaxed iteration methods for solving matrix equation AXB=C

Author

Listed:
  • Tian, Zhaolu
  • Li, Xiaojing
  • Dong, Yinghui
  • Liu, Zhongyun

Abstract

In this paper, based on the iteration frameworks [6], several relaxed iteration methods are proposed for solving the matrix equation AXB=C by introducing a tunable parameter ω, and their convergence properties are analyzed in detail. Moreover, the optimal choices of the parameter ω to achieve the fastest convergence rate are also obtained for some special cases. Finally, numerical experiments are carried out to illustrate the effectiveness of the proposed algorithms.

Suggested Citation

  • Tian, Zhaolu & Li, Xiaojing & Dong, Yinghui & Liu, Zhongyun, 2021. "Some relaxed iteration methods for solving matrix equation AXB=C," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    • Handle: RePEc:eee:apmaco:v:403:y:2021:i:c:s0096300321002794
    DOI: 10.1016/j.amc.2021.126189
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    References listed on IDEAS

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    1. Tian, Zhaolu & Tian, Maoyi & Liu, Zhongyun & Xu, Tongyang, 2017. "The Jacobi and Gauss–Seidel-type iteration methods for the matrix equation AXB=C," Applied Mathematics and Computation, Elsevier, vol. 292(C), pages 63-75.
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    Cited by:

    1. Tian, Zhaolu & Wang, Yudong & Wu, Nian-Ci & Liu, Zhongyun, 2024. "On the parameterized two-step iteration method for solving the matrix equation AXB = C," Applied Mathematics and Computation, Elsevier, vol. 464(C).

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    2. Tian, Zhaolu & Wang, Yudong & Wu, Nian-Ci & Liu, Zhongyun, 2024. "On the parameterized two-step iteration method for solving the matrix equation AXB = C," Applied Mathematics and Computation, Elsevier, vol. 464(C).
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