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A new FXTZNN model for solving TVCS equation and application to pseudo-inverse of a matrix

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  • Miao, Peng
  • Zheng, Yuhua
  • Li, Shuai

Abstract

In order to obtain a smaller upper bound of convergence time (UBCT), a new fixed-time stability (FXTS) criterion is given. On this basis, a fixed-time zeroing neural network (ZNN) model is designed to solve time-varying complex Sylvester (TVCS) equation and the method is used to find pseudo-inverse of a matrix. A new positive definite and radially unbounded function with an exponential term is designed to achieve FXTS of the nonlinear dynamical system. To do so, the UBCT is obtained by taking logarithms, so that it is smaller than others under the same conditions. While, the proposed FXTS criterion is proven and the UBCT independent of initial point is estimated. Then, a fixed-time ZNN (FXTZNN) model is designed to solve TVCS equation and its FXTS is proven. In addition, a noise interference term is added into the proposed ZNN model, its noise-tolerant is analyzed and the steady-state error is given. Lastly, two numerical illustrative examples and an application example show the superiority and effectiveness of our methods.

Suggested Citation

  • Miao, Peng & Zheng, Yuhua & Li, Shuai, 2024. "A new FXTZNN model for solving TVCS equation and application to pseudo-inverse of a matrix," Applied Mathematics and Computation, Elsevier, vol. 465(C).
    • Handle: RePEc:eee:apmaco:v:465:y:2024:i:c:s0096300323005787
    DOI: 10.1016/j.amc.2023.128409
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    References listed on IDEAS

    as
    1. Wang, Guancheng & Li, Qinrou & Liu, Shaoqing & Xiao, Hua & Zhang, Bob, 2022. "New zeroing neural network with finite-time convergence for dynamic complex-value linear equation and its applications," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    2. Zhu, Jingcan & Jin, Jie & Chen, Weijie & Gong, Jianqiang, 2022. "A combined power activation function based convergent factor-variable ZNN model for solving dynamic matrix inversion," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 197(C), pages 291-307.
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