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New Models for Solving Time-Varying LU Decomposition by Using ZNN Method and ZeaD Formulas

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  • Liangjie Ming
  • Yunong Zhang
  • Jinjin Guo
  • Xiao Liu
  • Zhonghua Li
  • Nan-Jing Huang

Abstract

In this paper, by employing the Zhang neural network (ZNN) method, an effective continuous-time LU decomposition (CTLUD) model is firstly proposed, analyzed, and investigated for solving the time-varying LU decomposition problem. Then, for the convenience of digital hardware realization, this paper proposes three discrete-time models by using Euler, 4-instant Zhang et al. discretization (ZeaD), and 8-instant ZeaD formulas to discretize the proposed CTLUD model, respectively. Furthermore, the proposed models are used to perform the LU decomposition of three time-varying matrices with different dimensions. Results indicate that the proposed models are effective for solving the time-varying LU decomposition problem, and the 8-instant ZeaD LU decomposition model has the highest precision among the three discrete-time models.

Suggested Citation

  • Liangjie Ming & Yunong Zhang & Jinjin Guo & Xiao Liu & Zhonghua Li & Nan-Jing Huang, 2021. "New Models for Solving Time-Varying LU Decomposition by Using ZNN Method and ZeaD Formulas," Journal of Mathematics, Hindawi, vol. 2021, pages 1-13, April.
    • Handle: RePEc:hin:jjmath:6627298
    DOI: 10.1155/2021/6627298
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