Journal of Computational and Applied Mathematics2022,Vol.40316.DOI:10.1016/j.cam.2021.113824

Discrete-time noise-tolerant Z-type model for online solving nonlinear time-varying equations in the presence of noises

Jin, Long Sun, Zhongbo Liu, Yongbai Wang, Gang Lian, Yufeng Liu, Keping
Journal of Computational and Applied Mathematics2022,Vol.40316.DOI:10.1016/j.cam.2021.113824

Discrete-time noise-tolerant Z-type model for online solving nonlinear time-varying equations in the presence of noises

Jin, Long 1Sun, Zhongbo 2Liu, Yongbai 2Wang, Gang 2Lian, Yufeng 2Liu, Keping2
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作者信息

  • 1. Lanzhou Univ
  • 2. Changchun Univ Technol
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Abstract

Nonlinear time-varying equation problems (NTVEPs), a core mathematical problem in engineering applications and scientific computing fields, have been widely researched in recent years. In this paper, the zeroing-dynamic design formula and continuous time Z-type model are revisited for solving NTVEPs. Then, a modified Z-type design formula is developed to address NTVEPs in the presence of noises. Specifically, a novel class of discrete-time noise-tolerant Z-type model with psi(tau)(chi(Tau), Tau) known (DTNTZTM-K) and discrete-time noise-tolerant Z-type model with psi(tau) (chi(Tau), Tau) unknown (DTNTZTMU) models are first proposed and investigated for online solving NTVEPs with different measurement noises. Furthermore, general-type DTNTZTM-K and DTNTZTM-U models (termed as GDTNTZTM-K and GDTNTZTM-U models) with different activation function are proposed to verify the robustness and superiority. In addition, theoretical analyses demonstrate that the presented DTNTZTM-K and DTNTZTM-U models are 0-stable, consistent and convergent. Besides, it further indicates that different activation functions can be utilized to accelerate the convergent speed of a class of general discrete-time noise-tolerant Z-type models, which demonstrates their high efficiency and robustness. Ultimately, numerical results show the efficacy and superiority of the proposed DTNTZTM-K, DTNTZTM-U, GDTNTZTM-K and GDTNTZTM-U models for noise-polluted NTVEPs compared with classical methods. (c) 2021 Elsevier B.V. All rights reserved.

Key words

Discrete-time noise-tolerant Z-type model/Theoretical analysis/Nonlinear time-varying equations/Steady-state residual error/Zeroing dynamic/RECURRENT NEURAL-NETWORK/COMPUTATION/DYNAMICS

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出版年

2022
Journal of Computational and Applied Mathematics

Journal of Computational and Applied Mathematics

EISCI
ISSN:0377-0427
被引量3
参考文献量41
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