This paper is concerned with the nonfragile state estimation for a kind of delayed fractional-order neural network under the event-triggered mechanism (ETM). To reduce the bandwidth occupation of the communication network, the ETM is employed in the sensor-to-estimator channel. Moreover, in order to reflect the reality, the transmission delay is taken into account in the model establishment. Sufficient criteria are supplied to make sure that the augmented system is asymptotically stable by using the fractional-order Lyapunov indirect approach and the linear matrix inequality method. In the end, the theoretical result is shown by means of two numerical examples.

中文翻译：

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事件触发机制下分数阶神经网络的非脆弱估计器设计

本文涉及一种基于事件触发机制（ETM）的时滞分数阶神经网络的非脆弱状态估计。为了减少通信网络的带宽占用，在传感器到估计器的通道中使用了ETM。此外，为了反映现实，在模型建立中考虑了传输延迟。通过使用分数阶Lyapunov间接方法和线性矩阵不等式方法，提供了足够的标准来确保扩展系统是渐近稳定的。最后，通过两个数值例子说明了理论结果。