IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v175y2023ip2s0960077923009621.html
   My bibliography  Save this article

Stability analysis of pseudo almost periodic solutions for octonion-valued recurrent neural networks with proportional delay

Author

Listed:
  • Gao, Jin
  • Dai, Lihua
  • Jiang, Hongying

Abstract

Considering the effect of the proportional delay, this paper deals with a class of octonion-valued recurrent neural networks with proportional delay. We do not need to decompose the octonion-valued recurrent neural networks into real-valued neural networks because the multiplication of octonion algebras does not satisfy the associativity and commutativity. We obtain several sufficient conditions for the existence and local exponential stability of pseudo almost periodic solutions for octonion-valued recurrent neural networks with proportional delay by using the Banach fixed point theorem, the non-decomposition method, and the Lyapunov function method. Finally, one example will be given to verify the obtained theoretical results.

Suggested Citation

  • Gao, Jin & Dai, Lihua & Jiang, Hongying, 2023. "Stability analysis of pseudo almost periodic solutions for octonion-valued recurrent neural networks with proportional delay," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).
  • Handle: RePEc:eee:chsofr:v:175:y:2023:i:p2:s0960077923009621
    DOI: 10.1016/j.chaos.2023.114061
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077923009621
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2023.114061?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Huang, Chuangxia & Su, Renli & Cao, Jinde & Xiao, Songlin, 2020. "Asymptotically stable high-order neutral cellular neural networks with proportional delays and D operators," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 171(C), pages 127-135.
    2. Weide Liu & Jianliang Huang & Qinghe Yao, 2021. "Stability Analysis of Pseudo-Almost Periodic Solution for a Class of Cellular Neural Network with D Operator and Time-Varying Delays," Mathematics, MDPI, vol. 9(16), pages 1-24, August.
    3. Huang, Chuangxia & Liu, Bingwen & Qian, Chaofan & Cao, Jinde, 2021. "Stability on positive pseudo almost periodic solutions of HPDCNNs incorporating D operator," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 1150-1163.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Baluni, Sapna & Sehgal, Ishani & Yadav, Vijay K. & Das, Subir, 2024. "Exponential synchronization of a class of quaternion-valued neural network with time-varying delays: A Matrix Measure Approach," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shen, Shiping & Meng, Xiaofang, 2023. "Finite-time stability of almost periodic solutions of Clifford-valued RNNs with time-varying delays and D operator on time scales," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    2. Chang, Shuang & Wang, Yantao & Zhang, Xian & Wang, Xin, 2023. "A new method to study global exponential stability of inertial neural networks with multiple time-varying transmission delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 211(C), pages 329-340.
    3. Chen, Yonghui & Zhang, Xian & Xue, Yu, 2022. "Global exponential synchronization of high-order quaternion Hopfield neural networks with unbounded distributed delays and time-varying discrete delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 193(C), pages 173-189.
    4. Huang, Chuangxia & Liu, Bingwen & Qian, Chaofan & Cao, Jinde, 2021. "Stability on positive pseudo almost periodic solutions of HPDCNNs incorporating D operator," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 1150-1163.
    5. Arunagirinathan, S. & Lee, T.H., 2024. "Generalized delay-dependent reciprocally convex inequality on stability for neural networks with time-varying delay," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 217(C), pages 109-120.
    6. Wang, Junlan & Wang, Xin & Wang, Yantao & Zhang, Xian, 2021. "Non-reduced order method to global h-stability criteria for proportional delay high-order inertial neural networks," Applied Mathematics and Computation, Elsevier, vol. 407(C).
    7. Chao Wang & Yinfang Song & Fengjiao Zhang & Yuxiao Zhao, 2023. "Exponential Stability of a Class of Neutral Inertial Neural Networks with Multi-Proportional Delays and Leakage Delays," Mathematics, MDPI, vol. 11(12), pages 1-14, June.
    8. Karnan, A. & Nagamani, G., 2022. "Non-fragile state estimation for memristive cellular neural networks with proportional delay," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 193(C), pages 217-231.
    9. Li, Yongkun & Wang, Xiaohui, 2021. "Almost periodic solutions in distribution of Clifford-valued stochastic recurrent neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    10. Deng, Yunke & Huang, Chuangxia & Cao, Jinde, 2021. "New results on dynamics of neutral type HCNNs with proportional delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 187(C), pages 51-59.
    11. Syed Ali, M. & Narayanan, G. & Saroha, Sumit & Priya, Bandana & Thakur, Ganesh Kumar, 2021. "Finite-time stability analysis of fractional-order memristive fuzzy cellular neural networks with time delay and leakage term," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 185(C), pages 468-485.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:175:y:2023:i:p2:s0960077923009621. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.