Cluster synchronization means that all multiagents are divided into different clusters according to the equations or roles of nodes in a complex network, and by designing an appropriate algorithm, each cluster can achieve synchronization to a certain value or an isolated node. However, the synchronization values between different clusters are different. With a feedback controller based on the calculation of the control input value and a trigger condition leading to the updating instants, this article introduces the trigger mechanism and designs a new data sampling strategy to achieve cluster synchronization of the coupled neural networks (CNNs), which reduces the number of updates of the controller, thereby reducing unnecessary waste of limited resources. In addition, an example proposes a synchronization algorithm and gives iterative procedures to calculate the trigger instants and prove the validity of the theoretical results.

中文翻译：

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通过事件触发钉扎控制的耦合神经网络与 Levy 噪声的集群同步


集群同步是指根据复杂网络中节点的方程或角色将所有多智能体划分为不同的集群，通过设计适当的算法，每个集群可以实现对某个值或某个孤立节点的同步。但不同集群之间的同步值是不同的。本文采用基于控制输入值计算的反馈控制器和导致更新时刻的触发条件，引入触发机制并设计一种新的数据采样策略来实现耦合神经网络（CNN）的集群同步，该策略减少了控制器的更新次数，从而减少了有限资源的不必要的浪费。此外，通过算例提出了一种同步算法，并给出了计算触发时刻的迭代过程，证明了理论结果的有效性。