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February 23, 2026Computational Mathematics and Mathematical Physics

Acceleration of Iterative Methods for Solving Linear Inverse Problems Based on Low-Rank Approximation

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Authors

BVB. I. ValiakhmetovDLD. V. LukyanenkoETE. E. Tyrtyshnikov

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Overview

An efficient method reduces iterations in solving linear inverse problems, suggesting significant computational savings.

Key Points

  • To develop an efficient preconditioner for accelerating solutions to linear algebraic equations in inverse problems.
  • Constructed a preconditioner based on low-rank approximation of the system matrix
  • Applied the method to systems of linear algebraic equations
  • Evaluated computational efficiency in the context of inverse problems
  • Reduced the number of iterations required for convergence in iterative methods
  • Demonstrated significant computational resource savings in processing experimental data
  • Enhanced accuracy in the reconstruction of measured quantities

Cite This Study

Valiakhmetov et al. (2026) studied this question.

synapsesocial.com/papers/699bee551c6c6bad5397ffechttps://doi.org/10.1134/s0965542525701696
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