Dynamical Analysis of Fractional-Order Quaternion-Valued Neural Networks with Leakage and Communication Delays

This paper investigates the stability and Hopf bifurcation problems of fractional-order quaternion-valued neural networks (FOQVNNs) with leakage delay and communication delay. Utilizing the Hamilton rule of quaternions, the fractional-order quaternion-valued time-delay neural network model is transformed into an equivalent fractional-order real-valued time-delay neural network system. Then, employing the stability theory and bifurcation theory of fractional-order dynamical systems, novel sufficient criteria are derived to ensure system stability and to induce Hopf bifurcation, respectively, using the leakage delay and the communication delay as bifurcation parameters. Furthermore, the influences of both delay types on the bifurcation behavior of FOQVNNs are analyzed in depth. To verify the correctness of the theoretical results, bifurcation diagrams and simulation results generated using MATLAB are presented. The theoretical results established in this paper provide a significant theoretical basis for the analysis and design of FOQVNNs.

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Publication Details

Journal
Fractal and Fractional
Published
2025-08-25
DOI
https://doi.org/10.3390/fractalfract9090559
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Dynamical Analysis of Fractional-Order Quaternion-Valued Neural Networks with Leakage and Communication Delays

Tianzeng Li, Xiaofeng Tan, Yu Wang, Qiankun Wang
Fractal and Fractional
Neural Networks and Applications
article

Dynamical Analysis of Fractional-Order Quaternion-Valued Neural Networks with Leakage and Communication Delays

Tianzeng Li, Xiaofeng Tan, Yu Wang, Qiankun Wang
article en

Abstract

This paper investigates the stability and Hopf bifurcation problems of fractional-order quaternion-valued neural networks (FOQVNNs) with leakage delay and communication delay. Utilizing the Hamilton rule of quaternions, the fractional-order quaternion-valued time-delay neural network model is transformed into an equivalent fractional-order real-valued time-delay neural network system. Then, employing the stability theory and bifurcation theory of fractional-order dynamical systems, novel sufficient criteria are derived to ensure system stability and to induce Hopf bifurcation, respectively, using the leakage delay and the communication delay as bifurcation parameters. Furthermore, the influences of both delay types on the bifurcation behavior of FOQVNNs are analyzed in depth. To verify the correctness of the theoretical results, bifurcation diagrams and simulation results generated using MATLAB are presented. The theoretical results established in this paper provide a significant theoretical basis for the analysis and design of FOQVNNs.

Fractal and FractionalVol. 9(9)
Hainan Normal University (CN), Sichuan University of Science and Engineering (CN)
Hainan Normal University, Sichuan University of Science and Engineering, Sichuan University
Openalex Percentile: Top 88%
Neural Networks and Applications
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Dynamical Analysis of Fractional-Order Quaternion-Valued Neural Networks with Leakage and Communication Delays — Tianzeng Li, Xiaofeng Tan, et al. · Fractal and Fractional (2025) | TGRS Research Map | TGRS