该文将径向基函数网络引入地震数据处理中，实现了函数逼近法地震数据的插值处理，在实际地震数据处理中取得了较好的应用效果。
This paper introduces the radial basis function (RBF) network in the seismic data processing, and realizes the inserting data in seismic data processing with function approximation method.
本文将径向基函数(RBF)神经网络应用到航空发动机故障诊断中。
In this paper, an RBF neural network approach is applied to aeroengine gas path fault diagnosis.
并对该特征向量进行对数归一化，将归一化的特征向量作为径向基函数（RBF）神经网络的输入，在此基础上进行识别，达到较好的识别效果。
The normalized vector is used as the input of RBF NN, and target recognition is performed based on this, which leads to a satisfactory recognition result.
为此，提出将径向基函数神经网络应用于大坝安全综合评价。
Therefore, the radial basis function neural network is proposed to apply to comprehensive evaluation of dam safety.
运用径向基函数网络方法将三维离散数据拟合成曲面，实现了三维数据可视化。
This article presents surface fitting by use of radial basis function network approach dealing with 3d discrete data, and visualization of 3d data is achieved.
将神经网络应用于光纤传感器的光强补偿，提出了一种基于径向基函数神经网络的光强补偿方法。
Applying neural network to intensity compensation of optical fiber sensors, a method based on radial basis function network is proposed.
将神经网络应用于光纤传感器的光强补偿，提出了一种基于径向基函数神经网络的光强补偿方法。
Applying neural network to intensity compensation of optical fiber sensors, a method based on radial basis function network is proposed.
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