A complex-valued time varying zeroing neural network model for synchronization of complex chaotic systems

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成果类型：

期刊论文

作者：

Jin, Jie*;Fang, Jing;Chen, Chaoyang;Li, Zhijing;Yu, Fei

通讯作者：

Jin, Jie;Fang, J;Jin, J

作者机构：

[Fang, Jing; Jin, Jie; Chen, Chaoyang] Hunan Univ Sci & Technol, Sanya Inst, Sanya 572024, Hainan, Peoples R China.

[Fang, Jing; Jin, Jie; Chen, Chaoyang; Jin, J; Li, Zhijing; Fang, J] Hunan Univ Sci & Technol, Sch Informat & Elect Engn, Xiangtan 411201, Hunan, Peoples R China.

[Jin, Jie; Jin, J] Changsha Med Univ, Sch Informat Engn, Changsha 410219, Hunan, Peoples R China.

[Yu, Fei] Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha 410114, Hunan, Peoples R China.

通讯机构：

[Jin, J ] C

[Jin, J; Fang, J ] H

Hunan Univ Sci & Technol, Sch Informat & Elect Engn, Xiangtan 411201, Hunan, Peoples R China.

Changsha Med Univ, Sch Informat Engn, Changsha 410219, Hunan, Peoples R China.

语种：

英文

关键词：

Zeroing neural network;Complex chaotic system synchronization;Fixed-time convergence;Robustness;Field programmable gate array

期刊：

Nonlinear Dynamics

ISSN：

0924-090X

年：

2025

卷：

113

期：

页码：

5471-5491

DOI：

10.1007/s11071-024-10528-8

基金类别：

This work was supported by National Natural Science Foundation of China under Grant 62273141, in part by the Natural Science Foundation of Hunan Province under Grant 2023JJ40286.

机构署名：

本校为其他机构

院系归属：

计算机与通信工程学院

摘要：

Zeroing neural network (ZNN) is an effective tool for solving the synchronization problem of chaotic systems and has received widespread attention. However, previous ZNN models only focused on the synchronization problem of real chaotic systems, failing to tackle the synchronization problem of complex chaotic systems. Based on this, this paper proposes a novel complex-valued time varying zeroing neural network (CVTVZNN) model. This paper rigorously derives the fixed-time convergence and external noise suppression ability of the CVTVZNN model in solving the synchronization problem of complex ch...

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A complex-valued time varying zeroing neural network model for synchronization of complex chaotic systems

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