Abstract This work investigates the finite-time event-triggered approach for recurrent neural networks with leakage term and its application. Here, decentralized event-triggered framework is recommended where event is checked at every sensor nodes related to local information for available triggering and the updated control is done whenever a centralized event is triggered. By handling the Lyapunov-Krasovskii functional (LKF) method together with novel inequality techniques like Wirtinger single and double integral inequality (WSI,WDI) technique, delay productive term (DPT), and a few adequate conditions are acquired to ensure the finite-time stability (FTS) analysis for the considered system, which is expressed with respect to linear matrix inequalities (LMIs). At last, numerical simulations are provided to indicate the efficiency of the expected results, two of them examples were supported by genuine use of the benchmark issue that correlate with sensible concerns under finite-time execution.

中文翻译：

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带泄漏项的递归神经网络的有限时间事件触发方法及其应用

摘要 这项工作研究了具有泄漏项的递归神经网络的有限时间事件触发方法及其应用。在这里，建议使用分散式事件触发框架，其中在与本地信息相关的每个传感器节点上检查事件以获取可用触发，并且每当触发集中式事件时都会完成更新的控制。通过处理 Lyapunov-Krasovskii 泛函 (LKF) 方法以及 Wirtinger 单双积分不等式 (WSI,WDI) 技术、延迟生产项 (DPT) 等新颖的不等式技术，并获得了一些充分条件以确保有限时间所考虑系统的稳定性 (FTS) 分析，其表示为线性矩阵不等式 (LMI)。最后，