In this paper, the l2-l∞ state estimation problem is addressed for a class of delayed artificial neural networks under high-rate communication channels with Round-Robin (RR) protocol. To estimate the state of the artificial neural networks, numerous sensors are deployed to measure the artificial neural networks. The sensors communicate with the remote state estimator through a shared high-rate communication channel. In the high-rate communication channel, the RR protocol is utilized to schedule the transmission sequence of the numerous sensors. The aim of this paper is to design an estimator such that, under the high-rate communication channel and the RR protocol, the exponential stability of the estimation error dynamics as well as the l2-l∞ performance constraint are ensured. First, sufficient conditions are given which guarantee the existence of the desired l2-l∞ state estimator. Then, the estimator gains are obtained by solving two sets of matrix inequalities. Finally, numerical examples are provided to verify the effectiveness of the developed l2-l∞ state estimation scheme.

中文翻译：

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基于循环协议的高速率通信信道下时滞人工神经网络的l2-l∞状态估计。

本文针对一类具有循环通信协议的高速通信信道下的时滞人工神经网络的l2-l∞状态估计问题进行了研究。为了估计人工神经网络的状态，部署了许多传感器来测量人工神经网络。传感器通过共享的高速通信通道与远程状态估计器通信。在高速率通信信道中，RR协议用于调度众多传感器的传输顺序。本文的目的是设计一种估计器，以便在高速通信信道和RR协议下，确保估计误差动态的指数稳定性以及l2-l∞性能约束。第一，给出了足够的条件以保证存在所需的l2-l∞状态估计器。然后，通过求解两组矩阵不等式获得估计器增益。最后，通过数值算例验证了所开发的l2-l∞状态估计方案的有效性。