IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v178y2024ics0960077923012432.html
   My bibliography  Save this article

Mean-square exponential input-to-state stability for stochastic neutral-type quaternion-valued neural networks via Itô’s formula of quaternion version

Author

Listed:
  • Zeng, Runtian
  • Song, Qiankun

Abstract

The input-to-state stability of stochastic quaternion-valued neural networks with neutral delays is explored in this study. Unlike previous researches, this study treats the neural network as a unified entity, rather than isolating and examining the real and imaginary components separately. Through the construction of a Lyapunov functional and the use of the Itô’s formula of quaternion version, a sufficient criterion for achieving mean-square exponential input-to-state stability is obtained for stochastic quaternion-valued neural networks with neutral delays. Three numerical instances are presented to validate the reliability of the obtained conditions.

Suggested Citation

  • Zeng, Runtian & Song, Qiankun, 2024. "Mean-square exponential input-to-state stability for stochastic neutral-type quaternion-valued neural networks via Itô’s formula of quaternion version," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    • Handle: RePEc:eee:chsofr:v:178:y:2024:i:c:s0960077923012432
    DOI: 10.1016/j.chaos.2023.114341
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077923012432
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2023.114341?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. Tong Wang & Yongsheng Ding & Lei Zhang & Kuangrong Hao, 2015. "Delay-dependent exponential state estimators for stochastic neural networks of neutral type with both discrete and distributed delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(4), pages 670-680, March.
    2. Balasubramaniam, P. & Lakshmanan, S. & Manivannan, A., 2012. "Robust stability analysis for Markovian jumping interval neural networks with discrete and distributed time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 45(4), pages 483-495.
    3. Manivannan, R. & Samidurai, R. & Cao, Jinde & Alsaedi, Ahmed & Alsaadi, Fuad E., 2018. "Stability analysis of interval time-varying delayed neural networks including neutral time-delay and leakage delay," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 433-445.
    4. Usa Humphries & Grienggrai Rajchakit & Pramet Kaewmesri & Pharunyou Chanthorn & Ramalingam Sriraman & Rajendran Samidurai & Chee Peng Lim, 2020. "Stochastic Memristive Quaternion-Valued Neural Networks with Time Delays: An Analysis on Mean Square Exponential Input-to-State Stability," Mathematics, MDPI, vol. 8(5), pages 1-26, May.
    5. Kwon, Yongchan & Won, Joong-Ho & Kim, Beom Joon & Paik, Myunghee Cho, 2020. "Uncertainty quantification using Bayesian neural networks in classification: Application to biomedical image segmentation," Computational Statistics & Data Analysis, Elsevier, vol. 142(C).
    Full references (including those not matched with items on IDEAS)

    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. Duan, Lian & Liu, Jinzhi & Huang, Chuangxia & Wang, Zengyun, 2022. "Finite-/fixed-time anti-synchronization of neural networks with leakage delays under discontinuous disturbances," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    2. Pengfei Guo & Yunong Zhang, 2022. "Tracking Control for Triple-Integrator and Quintuple-Integrator Systems with Single Input Using Zhang Neural Network with Time Delay Caused by Backward Finite-Divided Difference Formulas for Multiple-," Mathematics, MDPI, vol. 10(9), pages 1-27, April.
    3. Rajchakit, G. & Sriraman, R. & Lim, C.P. & Unyong, B., 2022. "Existence, uniqueness and global stability of Clifford-valued neutral-type neural networks with time delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 508-527.
    4. Chang, Wenting & Sang, Hong & Guo, Liangdong & Wu, Libing & Dimirovski, Georgi M., 2024. "Integrated L∞ anti-disturbance synchronization control for switched neural networks with unknown delays," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
    5. Wang, Fen & Chen, Yuanlong, 2021. "Mean square exponential stability for stochastic memristor-based neural networks with leakage delay," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    6. Du, Yuanhua & Liu, Xinzhi & Zhong, Shouming, 2016. "Robust reliable H∞ control for neural networks with mixed time delays," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 1-8.
    7. Zhang, Zhongjie & Yu, Tingting & Zhang, Xian, 2022. "Algebra criteria for global exponential stability of multiple time-varying delay Cohen–Grossberg neural networks," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    8. Francesco De Pretis & Jürgen Landes, 2021. "EA3: A softmax algorithm for evidence appraisal aggregation," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-23, June.
    9. Lihuan Guo & Wei Wang & Yenchun Jim Wu, 2023. "What Do Scholars Propose for Future COVID-19 Research in Academic Publications? A Topic Analysis Based on Autoencoder," SAGE Open, , vol. 13(2), pages 21582440231, June.
    10. Ganesan, Bhuvaneshwari & Annamalai, Manivannan, 2023. "Anti-synchronization analysis of chaotic neural networks using delay product type looped-Lyapunov functional," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    11. Iswarya, M. & Raja, R. & Cao, J. & Niezabitowski, M. & Alzabut, J. & Maharajan, C., 2022. "New results on exponential input-to-state stability analysis of memristor based complex-valued inertial neural networks with proportional and distributed delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 440-461.
    12. Sang, Hong & Zhao, Ying & Wang, Peng & Wang, Yuzhong & Yu, Shuanghe & Dimirovski, Georgi M., 2023. "Finite-time peak-to-peak analysis for switched generalized neural networks comprised of finite-time unstable subnetworks," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    13. Matthias Griebel & Dennis Segebarth & Nikolai Stein & Nina Schukraft & Philip Tovote & Robert Blum & Christoph M. Flath, 2023. "Deep learning-enabled segmentation of ambiguous bioimages with deepflash2," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    14. Amritanand Sebastian & Rahul Pendurthi & Azimkhan Kozhakhmetov & Nicholas Trainor & Joshua A. Robinson & Joan M. Redwing & Saptarshi Das, 2022. "Two-dimensional materials-based probabilistic synapses and reconfigurable neurons for measuring inference uncertainty using Bayesian neural networks," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

    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:178:y:2024:i:c:s0960077923012432. 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.