对径向基函数神经网络在数据分类中的应用进行了研究。
The application of radial basic function neural network in the data classification is studied.
本文研究了多层感知器、径向基函数网络、学习向量量化网络和自组织特征映射网络等四种神经网络在回转窑火焰图像分割中的应用。
In this paper, four neural networks, i. e. multi layer perception, radial basis function, learning vector quantization and self organizing feature mapping, are used to segment the flame image.
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.
以某厂羟胺反应器的氢离子浓度控制为例，介绍了径向基函数（RBF）神经网络在强非线性对象预测控制中的应用及仿真研究结果。
The application of RBF neural network in hardy nonlinear system and the result of simulation is introduced. An example of pH control in hydroxylamine reactor is described.
采用一种基于免疫算法和最小二乘法的两级学习方法设计径向基函数（RBF）网络，并将其应用于雷达天线扫描方式识别系统。
A hybrid RBF training method based on immune algorithm and least square method is proposed and applied in radar antenna scanning-style recognition system.
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.
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.
径向基函数(RBF)神经网络由于其结构简单、收敛速度快、无局部极小等特点使其在控制中的应用有着独特的优势。
Radial basis function (RBF) network have unique advantages in control applications due to its features of simple topological structure, quick convergence speed and no local minima.
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.
论文给出了改进型径向基网络应用示例，验证了改进型径向基网络的函数实现功能和模式分类功能。
A novel pattern recognition method based on wavelet packet analysis and radial basis function network is presented in this paper.
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。
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。
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.
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