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Fixed/Preassigned-Time Synchronization of Fuzzy Memristive Fully Quaternion-Valued Neural Networks Based on Event-Triggered Control

Author

Listed:
  • Shichao Jia

    (College of Mathematics and System Sciences, Xinjiang University, Urumqi 830017, China)

  • Cheng Hu

    (College of Mathematics and System Sciences, Xinjiang University, Urumqi 830017, China
    Xinjiang Key Laboratory of Applied Mathematics, Urumqi 830017, China)

  • Haijun Jiang

    (College of Mathematics and Statistics, Yili Normal University, Yining 835000, China)

Abstract

In this paper, the fixed-time and preassigned-time synchronization issues of fully quaternion-valued fuzzy memristive neural networks are studied based on the dynamic event-triggered control mechanism. Initially, the fuzzy rules are defined within the quaternion domain and the relevant properties are established through rigorous analysis. Subsequently, to conserve resources and enhance the efficiency of the controller, a kind of dynamic event-triggered control mechanism is introduced for the fuzzy memristive neural networks. Based on the non-separation analysis, fixed-time and preassigned-time synchronization criteria are presented and the Zeno phenomenon under the event-triggered mechanism is excluded successfully. Finally, the effectiveness of the theoretical results is verified through numerical simulations.

Suggested Citation

  • Shichao Jia & Cheng Hu & Haijun Jiang, 2024. "Fixed/Preassigned-Time Synchronization of Fuzzy Memristive Fully Quaternion-Valued Neural Networks Based on Event-Triggered Control," Mathematics, MDPI, vol. 12(9), pages 1-31, April.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:9:p:1276-:d:1381129
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