Adaptive Event-Triggered Lag Outer Synchronization for Coupled Neural Networks With Multistate or Multiderivative Couplings

IF 10.5 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2025-01-10 DOI:10.1109/TCYB.2024.3519171
Jin-Liang Wang;Yan-Ran Zhu;Jian-Qiao Wang;Shun-Yan Ren;Tingwen Huang
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Abstract

Multistate coupled coupled neural networks (MSCCNN) and multiderivative coupled coupled neural networks (MDCCNN) are introduced in this article, and the lag outer synchronization for these two networks are tackled. First, a lag outer synchronization criterion for MSCCNN is derived using a node-based adaptive event-triggered control scheme, and the fact that the Zeno behavior does not exist is also proved. Moreover, the edge-based adaptive event-triggered control method is also utilized to address the lag outer synchronization for MSCCNN, and the existence of Zeno behavior is ruled out. In addition, two lag outer synchronization criteria for MDCCNN are given on the basis of the node- and edge-based adaptive event-triggered control strategies, and the nonexistence of Zeno behavior is also established. Finally, two examples are provided to demonstrate the feasibility of the proposed control schemes.
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多状态或多导数耦合神经网络的自适应事件触发滞后外同步
介绍了多态耦合神经网络(MSCCNN)和多导数耦合神经网络(MDCCNN),并讨论了这两种网络的滞后外同步问题。首先,采用基于节点的自适应事件触发控制方案推导了MSCCNN的滞后外同步准则,并证明了Zeno行为不存在的事实。此外,采用基于边缘的自适应事件触发控制方法解决了MSCCNN的滞后外同步问题,排除了芝诺行为的存在。此外,在基于节点和边缘的自适应事件触发控制策略的基础上,给出了MDCCNN的滞后外同步准则,并建立了Zeno行为的不存在性。最后,通过实例验证了所提控制方案的可行性。
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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