Two accelerated gradient-based iteration methods for solving the Sylvester matrix equation AX + XB = C

Huiling Wang, Nian Ci Wu, Yufeng Nie

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, combining the precondition technique and momentum item with the gradient-based iteration algorithm, two accelerated iteration algorithms are presented for solving the Sylvester matrix equation AX + XB = C. Sufficient conditions to guarantee the convergence properties of the proposed algorithms are analyzed in detail. Varying the parameters of these algorithms in each iteration, the corresponding adaptive iteration algorithms are also provided, and the adaptive parameters can be explicitly obtained by the minimum residual technique. Several numerical examples are implemented to illustrate the effectiveness of the proposed algorithms.

Original languageEnglish
Pages (from-to)34734-34752
Number of pages19
JournalAIMS Mathematics
Volume9
Issue number12
DOIs
StatePublished - 2024

Keywords

  • gradient-based iteration
  • minimum residual technique
  • momentum term
  • precondition technique
  • Sylvester matrix equation

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