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Multistability analysis of quaternion-valued neural networks with cosine activation functions

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  • Yu, Siyi
  • Li, Hua
  • Chen, Xiaofeng
  • Lin, Dongyuan

Abstract

It is significant to design a system with high storage capacity for associative memory and pattern recognition. To address this issue, this paper first proposes a quaternion-valued neural network (QVNN) model with multiple equilibrium points in which the cosine function is used as the activation function of QVNN. Then, based on the Brouwer fixed point theorem and the geometric properties of the activation function, sufficient conditions for QVNN to have unique equilibrium points, finite equilibrium points, and countable infinite equilibrium points are obtained, respectively. Furthermore, sufficient conditions for the exponential stability of equilibrium points are derived, and the attraction basins of the stable equilibrium points are given. Finally, two numerical examples are given to confirm the validity of the proposed theoretical results.

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  • Yu, Siyi & Li, Hua & Chen, Xiaofeng & Lin, Dongyuan, 2023. "Multistability analysis of quaternion-valued neural networks with cosine activation functions," Applied Mathematics and Computation, Elsevier, vol. 445(C).
    • Handle: RePEc:eee:apmaco:v:445:y:2023:i:c:s0096300323000188
    DOI: 10.1016/j.amc.2023.127849
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    References listed on IDEAS

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    1. Tan, Manchun & Liu, Yunfeng & Xu, Desheng, 2019. "Multistability analysis of delayed quaternion-valued neural networks with nonmonotonic piecewise nonlinear activation functions," Applied Mathematics and Computation, Elsevier, vol. 341(C), pages 229-255.
    2. Chaochuan Jia & Ting Yang & Chuanjiang Wang & Binghui Fan & Fugui He, 2019. "A new fast filtering algorithm for a 3D point cloud based on RGB-D information," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-21, August.
    3. Shao, Hanyong & Li, Huanhuan & Zhu, Chuanjie, 2017. "New stability results for delayed neural networks," Applied Mathematics and Computation, Elsevier, vol. 311(C), pages 324-334.
    4. Wang, Huamin & Wei, Guoliang & Wen, Shiping & Huang, Tingwen, 2021. "Impulsive disturbance on stability analysis of delayed quaternion-valued neural networks," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    5. Nie, Xiaobing & Liang, Jinling & Cao, Jinde, 2019. "Multistability analysis of competitive neural networks with Gaussian-wavelet-type activation functions and unbounded time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 356(C), pages 449-468.
    6. Udhayakumar, K. & Rakkiyappan, R. & Li, Xiaodi & Cao, Jinde, 2021. "Mutiple ψ-type stability of fractional-order quaternion-valued neural networks," Applied Mathematics and Computation, Elsevier, vol. 401(C).
    7. Chen, Xiaofeng & Zhao, Zhenjiang & Song, Qiankun & Hu, Jin, 2017. "Multistability of complex-valued neural networks with time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 294(C), pages 18-35.
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    Cited by:

    1. Jibin Yang & Xiaohui Xu & Quan Xu & Haolin Yang & Mengge Yu, 2024. "Stability and Synchronization of Delayed Quaternion-Valued Neural Networks under Multi-Disturbances," Mathematics, MDPI, vol. 12(6), pages 1-26, March.

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