Fixed/Preassigned-Time Synchronization of Fuzzy Memristive Fully Quaternion-Valued Neural Networks Based on Event-Triggered Control
Shichao Jia,
Cheng Hu and
Haijun Jiang ()
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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
Haijun Jiang: College of Mathematics and Statistics, Yili Normal University, Yining 835000, China
Mathematics, 2024, vol. 12, issue 9, 1-31
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.
Keywords: quaternion-valued fuzzy memristive neural network; fixed-time synchronization; dynamic event-triggered control; preassigned-time synchronization; non-separation approach (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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