In the previous work, a typical recurrent neural network termed Zhang neural network (ZNN) has been developed for various time-varying problems solving. Based on the previous work, by exploiting a special activation function (i.e., Li activation function), the resultant ZNN model is presented and investigated in this paper for online solution of time-varying linear matrix inequality (TVLMI). For such a Li-function activated ZNN (LFAZNN) model, theoretical results are provided to show its excellent computational performance on solving the TVLMI. That is, the presented LFAZNN model has the property of finite-time convergence. Comparative simulation results with two illustrative examples further substantiate the efficacy of the presented LFAZNN model for TVLMI solving.

中文翻译：

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时变线性矩阵不等式在线解的Li-功能激活的张神经网络

在先前的工作中，已经开发出一种称为张神经网络（ZNN）的典型递归神经网络，用于解决各种时变问题。在先前工作的基础上，通过利用特殊的激活函数（即Li激活函数），提出并研究了所得的ZNN模型，用于时变线性矩阵不等式（TVLMI）的在线求解。对于这种由Li函数激活的ZNN（LFAZNN）模型，提供了理论结果以显示其在解决TVLMI方面的出色计算性能。即，所提出的LFAZNN模型具有有限时间收敛的性质。带有两个说明性示例的比较模拟结果进一步证实了所提出的LFAZNN模型解决TVLMI的功效。