A family of varying-parameter finite-time zeroing neural networks for solving time-varying Sylvester equation and its application

被引：28

作者：

Gerontitis, Dimitrios ^{[1
]}

Behera, Ratikanta ^{[2
]}

Tzekis, Panagiotis ^{[1
]}

Stanimirovic, Predrag ^{[3
]}

机构：

[1] Int Hellen Univ, Dept Informat & Elect Engn, Thessaloniki, Greece

[2] Univ Cent Florida, Dept Math, Orlando, FL 32826 USA

[3] Univ Nis, Fac Sci & Math, Visegradska 33, Nish 18000, Serbia

来源：

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS | 2022年 / 403卷

关键词：

Recurrent neural network; Sylvester equation; Zeroing neural network (ZNN); Varying-parameter finite-time zeroing neural network (VPFTZNN); ITERATIVE ALGORITHM; DESIGN FORMULA; CONVERGENCE;

D O I：

10.1016/j.cam.2021.113826

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

A family of varying-parameter finite-time zeroing neural networks (VPFTZNN) is introduced for solving the time-varying Sylvester equation (TVSE). The convergence speed of the proposed VPFTZNN family is analysed and compared with the traditional zeroing neural network (ZNN) and the finite-time zeroing neural network (FTZNN). The behaviour of the proposed neural networks under various activation functions is proved theoretically and verified experimentally. In addition, the stability and noise resistance of the proposed VPFTZNN family are discussed. Further, the proposed VPFTZNN models are applied in the computation of current flows in an electrical network. (c) 2021 Elsevier B.V. All rights reserved.

引用

页数：20

共 48 条

[41] Multiple ψ-Type Stability of Cohen-Grossberg Neural Networks With Both Time-Varying Discrete Delays and Distributed Delays [J].

Zhang, Fanghai ;

Zeng, Zhigang .

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 30 (02) :566-579

[42] Multiple ψ-Type Stability and Its Robustness for Recurrent Neural Networks With Time-Varying Delays [J].

Zhang, Fanghai ;

Zeng, Zhigang .

IEEE TRANSACTIONS ON CYBERNETICS, 2019, 49 (05) :1803-1815

[43]

Zhang Y, 2015, ZHANG FUNCTIONS AND VARIOUS MODELS, P1, DOI 10.1007/978-3-662-47334-4

[44] Self-splitting competitive learning: A new on-line clustering paradigm [J].

Zhang, YJ ;

Liu, ZQ .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2002, 13 (02) :369-380

[45] From Davidenko Method to Zhang Dynamics for Nonlinear Equation Systems Solving [J].

Zhang, Yunong ;

Zhang, Yinyan ;

Chen, Dechao ;

Xiao, Zhengli ;

Yan, Xiaogang .

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2017, 47 (11) :2817-2830

[46] Discrete-time ZD, GD and NI for solving nonlinear time-varying equations [J].

Zhang, Yunong ;

Li, Zhen ;

Guo, Dongsheng ;

Ke, Zhende ;

Chen, Pei .

NUMERICAL ALGORITHMS, 2013, 64 (04) :721-740

[47] A Varying-Gain Recurrent Neural Network and Its Application to Solving Online Time-Varying Matrix Equation [J].

Zhang, Zhijun ;

Deng, Xianzhi ;

Qu, Xilong ;

Liao, Bolin ;

Kong, Ling-Dong ;

Li, Lulan .

IEEE ACCESS, 2018, 6 :77940-77952

[48] Weighted least squares solutions to general coupled Sylvester matrix equations [J].

Zhou, Bin ;

Li, Zhao-Yan ;

Duan, Guang-Ren ;

Wang, Yong .

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2009, 224 (02) :759-776

← 1 2 3 4 5 →