基函数

在反演计算中，射线轨迹点处的慢度可用三次多项式基函数予以计算。

In inversion , the slowness at points on ray path can be calculated by using three order polynomial primary function .

基函数在计算机辅助几何设计中起着基础和决定性的作用，本文探讨了有理B（？）

In the Computer Aided Geometric Design basic functions have a basic and determining action .

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

在识别过程中，采用径基函数（Radialbasisfunction，简写为RBF）神经网络。

In the processing of recognition , respectively adopt Radial Basis Function ( RBF ) Neural Network .

电力电子线路的故障诊断&利用CAI实现二级基函数字典法

Faults diagnosis of power electronic circuit ── realized tow-grade-basis-function dictionary method with CAI

Gottlieb[18]提出的C1谱方法，需要重新构造基函数，推导过程相当复杂。

Gottlieb [ l8 ] . They reconstructed base function for the C_1 spectral element method , which results in a complex process .

它们具有二次均匀B样条基函数的性质，且用它们生成的分段多项式曲线具有与分段二次均匀B样条曲线相同的结构和几何性质。

The piecewise polynomial curves generated by the above-mentioned functions possess the same structure and geometry properties as piecewise quadratic uniform B-spline curve .

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 .

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 .

基于Volterra基函数网络的自适应逆控制方法

Adaptive Inverse Control Based on Volterra Polynomial Basis Function Neural Networks

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 .

基于Chebyshev基函数模糊神经网络的快速辨识方法

Fast Identification Method of Fuzzy Neural Networks Based on Chebyshev Basis Function

一种权值直接确定及结构自适应的Chebyshev基函数神经网络

Weights-directly-determined and Structure-adaptively-tuned Neural Network Based on Chebyshev Basis Functions

先将未知的电流密度分成有旋和无旋两部分，并分别采用Loop基函数和Tree基函数进行展开，展开后的未知数的个数与传统的矩量法相等。

We represent the unknown currents in terms of its solenoidal and irrotational components and use Loop / Tree basis function as the expansion function , respectively .

采用B样条函数作为模糊隶属函数，利用神经网络实现模糊推理，提出一种模糊B样条基函数神经网络，并将其用于交流伺服系统的控制。

A fuzzy B-spline function neural network is proposed to control AC servo system by using B-spline function as fuzzy membership function and using neural network to realize fuzzy interfernce .

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 .

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 .

对三次B－样条基函数进行分析，给出三次B－样条曲线非整体性的一些特点，以及在工程曲线设计中的具体应用。

Based on an analysis of the basic function of cubic B-spline , tbe author discusses the non-integral property of cubic B-spline ; and its application to the design of Curves in engineering .

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 .

结果表明，点匹配法比galerkin法有较好的精确性，基函数取幂函数比取三角函数时效果更好。

For specific example , the numerical solution of point-matching method is more accurate the that of galerkin method .

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 .

相比之下，C0谱方法构造非常简单，直接使用传统的谱方法基函数，仍然能够达到超几何收敛。

In contrast , construction for our C_0 spectral element method is much simpler . As a matter of fact , conventional spectral basis functions can be used directly , and still maintaining geometric convergence rate .

样条微分求积法是一种新型的数值计算方法，其与传统微分求法的主要区别在于：它是基于B样条函数来构造基函数，进而获得权系数。

The Spline-based Differential Quadrature ( SDQ ) is a newly developed numerical method . The main distinction of the SDQ lies in the determination of weighting coefficients on the basis of cardinal B-spline interpolation functions .

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 .