Predefined‐Time Synchronization of Coupled Competitive Neural Networks

ABSTRACT The aim of this paper is to study the predefined‐time synchronization of coupled competitive neural networks (NNs) as well as the impacts of time‐varying delays on the predefined‐time synchronization performance. First, the models for drive and response systems of coupled competitive NNs with and without coupling delays are established for the first time in this work. After that, the predefined‐time synchronization of the proposed network models is investigated, and some new predefined‐time synchronization conditions for the considered drive and response systems are derived by designing novel bilayer controllers and using some inequality techniques. It is worth mentioning that the desired convergence time can be adjusted by presetting the parameters in the controllers in advance. Moreover, the synchronization is achieved in the predefined time regardless of the initial value of the coupled competitive NNs. At last, the proposed synchronization conditions are validated through two examples.

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Publication Details

Journal
International Journal of Adaptive Control and Signal Processing
Published
2025-01-09
DOI
https://doi.org/10.1002/acs.3961
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73

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article

Predefined‐Time Synchronization of Coupled Competitive Neural Networks

Tse Chiu Wong, Limei Su, Yanli Huang, Yaxin Gao
1 citations
International Journal of Adaptive Control and Signal Processing
Advanced Memory and Neural Computing
0.73
article

Predefined‐Time Synchronization of Coupled Competitive Neural Networks

Tse Chiu Wong, Limei Su, Yanli Huang, Yaxin Gao
article en
1 citations

Abstract

ABSTRACT The aim of this paper is to study the predefined‐time synchronization of coupled competitive neural networks (NNs) as well as the impacts of time‐varying delays on the predefined‐time synchronization performance. First, the models for drive and response systems of coupled competitive NNs with and without coupling delays are established for the first time in this work. After that, the predefined‐time synchronization of the proposed network models is investigated, and some new predefined‐time synchronization conditions for the considered drive and response systems are derived by designing novel bilayer controllers and using some inequality techniques. It is worth mentioning that the desired convergence time can be adjusted by presetting the parameters in the controllers in advance. Moreover, the synchronization is achieved in the predefined time regardless of the initial value of the coupled competitive NNs. At last, the proposed synchronization conditions are validated through two examples.

International Journal of Adaptive Control and Signal ProcessingVol. 39(3)
University of Strathclyde (GB), Tiangong University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 32%
Advanced Memory and Neural Computing
0.73
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Predefined‐Time Synchronization of Coupled Competitive Neural Networks — Tse Chiu Wong, Limei Su, et al. · International Journal of Adaptive Control and Signal Processing (2025) | TGRS Research Map | TGRS