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<p>In this paper, we consider the total least squares solution of time-varying linear systems with time-varying right-hand side vectors. The neural network model termed as the neural network model for solving time-varying total least squares problems (NNTVTLS) and its discrete form of the neural network model for solving time-varying total least squares problems (DNNTVTLS) are provided to solve this problem. The analyses of convergence and robustness demonstrate that the proposed DNNTVTLS model exhibits global convergence and superior noise immunity. Numerical experiments further verify the superiority and effectiveness of the DNNTVTLS model in solving time-varying linear equations, taking into account the presence of noise.</p>

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Neural networks for total least squares solution of the time-varying linear systems

  • 期刊论文

  • 发表日期：

    2025年1月7日

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  • Xuezhong Wang,
  • Jiali Shan,
  • Yimin Wei

摘要

In this paper, we consider the total least squares solution of time-varying linear systems with time-varying right-hand side vectors. The neural network model termed as the neural network model for solving time-varying total least squares problems (NNTVTLS) and its discrete form of the neural network model for solving time-varying total least squares problems (DNNTVTLS) are provided to solve this problem. The analyses of convergence and robustness demonstrate that the proposed DNNTVTLS model exhibits global convergence and superior noise immunity. Numerical experiments further verify the superiority and effectiveness of the DNNTVTLS model in solving time-varying linear equations, taking into account the presence of noise.