This article emphasizes the finite‐time state estimation problem for delayed complex dynamical networks with random parameters. In order to reduce the amount of transmission process, an aperiodic sampled‐data event‐triggered mechanism is introduced to determine whether the measurement output should be released at certain time points which incorporate an appropriate triggering condition and sampling moments. Furthermore, a concept of finite‐time boundedness in the pth moment is proposed to access the performance of state estimator. The objective of this article is to design an event‐triggered state estimator to estimate the states of nodes such that, in the presence of time delays, uncertainties, and randomly changing coupling weights, the estimation error system is finite‐time bounded in the pth moment related to a given constant. Some sufficient conditions in form of linear matrix inequalities and algebraic inequalities are established to guarantee finite‐time boundedness. Finally, a numerical example is presented to show the effectiveness of the theoretical results.

中文翻译：

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事件触发方法用于随机参数时滞复杂动力网络的有限时间状态估计

本文重点介绍了带有随机参数的时滞复杂动力网络的有限时间状态估计问题。为了减少传输过程的数量，引入了非周期性的采样数据事件触发机制，以确定是否应在某些时间点释放测量输出，其中应结合适当的触发条件和采样时刻。此外，提出了p时刻的有限时间有界性的概念，以获取状态估计器的性能。本文的目的是设计一个事件触发的状态估计器，以估计节点的状态，以便在存在时间延迟，不确定性和随机变化的耦合权重的情况下，估计误差系统在p中是有限时限的时刻与给定常数有关。建立了一些线性矩阵不等式和代数不等式的充分条件，以保证有限时间的有界性。最后，通过数值例子说明了理论结果的有效性。