The model USES an improved nearest-neighbor clustering algorithm to select the RBF center, and a recursive least square algorithm to train weights of the RBF neural network.

该模型首先采用改进的最近邻聚类算法确定径向基函数中心，接着应用递推最小二乘法训练网络的权值。

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The system identifier based on RBF neural network which applies nearest neighbor clustering algorithm realizes the identification of the inverse dynamic system model.

辨识器采用RBF神经网络结构和最近邻聚类算法，实现了对系统逆动力学模型的动态辨识。

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The system identifier based on RBF neural network which applies nearest neighbor clustering algorithm realizes the identification of the inverse dynamic system model.

辨识器采用RBF神经网络结构和最近邻聚类算法，实现了对系统逆动力学模型的动态辨识。

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