QUASI-PROJECTIVE SYNCHRONIZATION ANALYSIS FOR DELAYED STOCHASTIC QUATERNION-VALUED NEURAL NETWORKS VIA STATE-FEEDBACK CONTROL STRATEGY

Zhouhong Li; Xiaofang Meng; Kaipeng Hu; Yu Fei

doi:10.11948/20230399

2024 Volume 14 Issue 4

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Zhouhong Li, Xiaofang Meng, Kaipeng Hu, Yu Fei. QUASI-PROJECTIVE SYNCHRONIZATION ANALYSIS FOR DELAYED STOCHASTIC QUATERNION-VALUED NEURAL NETWORKS VIA STATE-FEEDBACK CONTROL STRATEGY[J]. Journal of Applied Analysis & Computation, 2024, 14(4): 2411-2430. doi: 10.11948/20230399

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Zhouhong Li, Xiaofang Meng, Kaipeng Hu, Yu Fei. QUASI-PROJECTIVE SYNCHRONIZATION ANALYSIS FOR DELAYED STOCHASTIC QUATERNION-VALUED NEURAL NETWORKS VIA STATE-FEEDBACK CONTROL STRATEGY[J]. Journal of Applied Analysis & Computation, 2024, 14(4): 2411-2430. doi: 10.11948/20230399

QUASI-PROJECTIVE SYNCHRONIZATION ANALYSIS FOR DELAYED STOCHASTIC QUATERNION-VALUED NEURAL NETWORKS VIA STATE-FEEDBACK CONTROL STRATEGY

1.
School of Statistics and Mathematics, Yunnan University of Finance and Economics, 650221 Kunming, Yunnan, China
2.
Department of Mathematics, Yuxi Normal University, 653100 Yuxi, Yunnan, China

Author Bio: Email: zhouhli@yeah.net, lzh@yxnu.edu.cn(Z. Li); Email: xfmeng@ynufe.edu.cn(X. Meng); Email: hukaipeng@ynufe.edu.cn(K. Hu)
Corresponding author: Email: feiyu@ynufe.edu.cn(Y. Fei)
Fund Project: The authors were supported by the Yunnan Fundamental Research Projects under Grant 202201AU070170, and the Science Research Fund Projects of Yunnan University of Finance and Economics under Grant 2023D40, and the Yunnan Province XingDian Talent Support Program (YNWR-YLXZ-2018-020), and the Key Laboratory of Complex Dynamics System and Application Analysis of Department of Education of Yunnan Province

Abstract

Abstract

In this paper, we explore the complete synchronization and quasi-projective synchronization in a class of stochastic delayed quaternion-valued neural networks, utilizing a state-feedback control scheme. The studied neural networks into real-valued networks are short of known decomposing, by designing a very general nonlinear controller, according to the quaternion form It? formula with a number of inequality techniques in the configuration of quaternion domain, we obtained a quasi-projective synchronization criterion for drive-response networks. Moreover, we estimate the error margin for quasi-projective synchronization. At last, the theoretical results are confirmed by a numerical simulation.
- Stochastic neural network /
- quaternion /
- quasi-projective synchronization /
- time delays
MSC: 34C27, 34D06, 92B20

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References

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