径向基函数

结果表明，用径向基函数网络可以达到较高的预测精度，且网络稳定、结果唯一。如果能不断地积累并选择训练数据，网络的预测准确性将进一步提高。

The result indicated that the RBF neural network model was considered to be with the high-precision , stable-structure and sole-result . And it was found that the more the training data , the higher the precision of the model .

基于径向基函数（RBF）的安徽省GDP增长模拟与预测

Simulation and prediction of Anhui 's economic Growth Index ( GDP ) based on RBF neural networks

基于径向基函数的3D散乱数据插值多尺度方法

A Multi-scale Approach to 3D Scattered Data Interpolation Based on Radial Basis Function

一种基于径向基函数网络的OFDM信道估计及跟踪方法

A radial basis function network-based channel estimation and tracking method for OFDM systems

扬压力径向基函数神经网络模型的精度和运算速度都高于BP神经网络模型。

Both the precision and calculation speed of the Radial basis function model are better than those of BP model .

基于白术FTIR的径向基函数神经网络鉴别研究

Identification of Rhizoma Atractylodes Based on FTIR Spectra and Radial Basis Function Network

径向基函数（RBF）网络在入侵检测中的应用

Application of RBF Network in Intrusion Detection

作者提出一种应用径向基函数网络（RBF）的云检测方法。

Application of radial basis function ( RBF ) networks to cloud detection is investigated .

点模型的隐式化采用散乱点径向基函数（RBF）变分插值，采用该算法可由多个点模型构造复杂的点模型。

Using the algorithm , complex point model can be constructed from several point models .

将经过筛选和处理过的特征作为输入向量，输入到径向基函数网络（RBF）。

Chosen and processed features input Radial Basis Function ( RBF ) nets as input vectors .

一种新颖的径向基函数（RBF）网络学习算法

An Original RBF Network Learning Algorithm

对于半主动悬架，设计了滑模控制器，并通过径向基函数神经网络（RBF）对其进行了优化。

For semi active suspension , a sliding model controller is designed and refined by RBF network .

基于视觉原理和Weber定律的径向基函数回归建模

RBF Regression Modeling Based on Visual System Theory and Weber Law

对径向基函数（RBF）神经网络在数据分类中的应用进行了研究。

The application of radial basic function ( RBF ) neural network in the data classification is studied .

对于传统BP算法存在的收敛速度慢和易陷入局部极小值问题，人们提出了径向基函数网络。

People put forward radial basis function networks considering the conventional BP algorithm problems of slow convergence speed and easily getting into local dinky value .

借助神经网络方法处理非线性问题的优势，采用径向基函数（RBF）来构造多层前馈BP神经网络。

With the advantage of neural network in nonlinear problem , a radial basis function is used to improve conventional BP network .

研究了基于自适应径向基函数（RBF）网络的故障诊断方法。

A self-adapting fault diagnosis method based on radial basis function ( RBF ) networks is studied in the thesis .

据此建立了基于径向基函数（RBF）预测模型，对实际网络数据流进行预测。

A radial basic function ( RBF ) neutral network model is constructed to forecast the Internet traffic data flows .

为建立准确的渣油裂解装置经验模型，采用了一种特殊的径向基函数网络&通用回归神经网络（GeneralRegressionNeuralNetwork，GRNN）。

A special radial basis function network ( RBFN ), general regression neural network ( GRNN ), was used to build a precise empirical model for cracker .

经过与线性核函数及Sig-moid核函数的对比，选用基于径向基函数（RBF）作为核函数，在分析预测误差和模型参数关系的基础上，选择了合适的参数；

By analyzing the relationship between the error margin of prediction and the model parameters , the proper parameters were chosen .

本文以径向基函数神经网络为基础，研究了相应的DOA估计的改进算法。

Based on radial basis function neural network ( RBFNN ), certain improved algorithm for DOA estimation is proposed .

研究一种利用径向基函数（RBF）神经网络识别冠心病心电信号模式的方法。

A method of pattern recognition for coronary heart disease ′ s ECG signals based on a RBF neural network was researched .

针对现有径向基函数（RBF）神经网络训练算法存在的问题，给出了RBF神经网络的一种在线训练算法，对这种在线训练算法所涉及到的各个方面进行了全面的分析。

A novel online training algorithm for RBF neural network is presented . Some problems related to the algorithm are discussed in detail .

通过引入径向基函数（RBF）网络替代多层感知器网络，较好地克服了这些缺点。

In this work , MLP is substituted by a radial basis function ( RBF ) network , which solves these problems successfully .

论文提出了一种基于径向基函数（Radialbasisfunction）神经网络在线辨识的开关磁阻电机（SRM）单神经元PID自适应控制新方法。

This paper presents an novel approach of single neuron adaptive control for switched reluctance motors ( SRM ) based on radial basis function ( RBF ) neural network on-line identification .

径向基函数（RBF）神经网络因其结构简单而被广泛地用于非线性函数近似和数据分类。

Due to its structural simplicity , the radial basis function ( RBF ) neural network has been widely used for approximation and classification .

着重介绍了线性神经网络及RBF径向基函数神经网络在时延预测中的表现及适用场合。

The emphasis is placed on the representations and applicable situations of linear neural network and radial basis function neural network in time-delay prediction .

本文对经典的RBF网络给出了严格的算法分析和应用实例，验证了径向基函数选择方法。

With the foundation of RBF net , this paper analyzes radial basis function algorithm and gives the radial basis function network choosing method .

结合改进的免疫算法和最小二乘法，提出了一种设计径向基函数（RBF）网络的两级学习方法。

A two-level learning method combining improved immune algorithm and least square method was proposed to design a radial basis function ( RBF ) network .

针对电液伺服系统存在未知干扰力及参数时变等问题，提出一种新型的模糊径向基函数（简称RBF）神经网络的在线控制方法。

An online control strategy based on fuzzy radial basis function network is proposed for the tracking control problem of the electro-hydraulic position servo system .