文本提出了一种基于模糊向量空间模型和径向基函数网络的分类方法。
A classification method based on fuzzy vector space model and radial basis function network is presented in this paper.
针对文本自动分类问题，提出了一种基于模糊向量空间模型和径向基函数网络的分类方法。
Aimed at the problems of document automatic classification, a classification method is proposed based on fuzzy vector space model and RBF network.
该文提出一个有效的基于径向基函数神经网络的模型和状态数据融合的汽轮发电机智能估计方法。
An efficient model based on radial basis function neural network and intelligent estimating method for data fusion of the turbine-generator is presented.
介绍了径向基函数(RBF)神经网络的结构和特点。
The structure and features of radial basis function (RBF) network are introduced.
提出了一种隐马尔可夫模型（HMM）和径向基函数神经网络（RBF）相结合的语音识别新方法。
Presents a new hybrid framework of hidden Markov models (HMM) and radial basis function (RBF) neural networks for speech recognition.
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.
径向基函数网络具有良好的推广能力和分类能力。
The radial basis function network (RBFN) has good extensible and classified (ability).
介绍了径向基函数网络的函数逼近原理和方法，提出了一种基于广义回归神经网络（GRNN）的传感器非线性误差校正方法。
The RBF network function approximation theory and method are introduced, and the method of nonlinear error correction of sensor is presented based on generalized regression neural network(GRNN).
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.
实验数据被用来训练径向基函数(RBF)神经网络，得出的神经网络结构和参数用于数据融合。
The experimental data are used to train a radial basis function (RBF) artificial neural network, and the construction and parameters of the network are obtained for data fusion.
以某水面舰艇为研究对象，利用径向基函数神经网络算法和标况下的水池实验数据，建立了基于航速、航向角和海情自适应变化的船舶横向运动非线性参数模型。
An intelligent model for a ship's horizontal motion, which can self-adapt with navigating speed, ocean condition and course, was established based on the Radial Basis Function (RBF) neural network.
针对PSD非线性对激光测平仪测量范围和测量精度的影响，采用一种新方法——径向基函数神经网络算法。
To eliminate the influence of nonlinear error of PSD on the measurement scale and accuracy of laser leveling tester, a new method of Radical Basis Function (RBF) neural network was used.
讨论了径向基函数中心的选取，构造了改进的RBF网络对训练样本和测试样本进行识别。
The choice of the center of radial basis function, constructing an improved RBF network and its application to recognize the trained samples and test samples were discussed.
该方法通过选择径向基函数中心、确定神经网络隐层神经元的数目和调整每一层的权值和阈值，对由于PSD非线性产生的误差进行修正。
The nonlinear error of PSD was modified by choosing the centre of RBF, ascertaining the number of neural cell of the neural network and adjusting the weight and the threshold of each hiberarchy.
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.
提出一种优化径向基函数神经网络来波方位(DOA)估计模型结构和参数的方法。
A novel algorithm for optimizing the structure and parameters of Direction of Arrival (DOA) estimation model based on radial basis function neural network is presented.
利用径向基函数神经网络和选择的特征值对缺陷进行分类。
Defects are classified by radial basis function (RBF) network and features selected.
在径向基函数神经网络中，隐层中心的数量和位置的选择是整个网络性能优劣的关键，直接影响网络的分类能力。
The choice of quantity and position of hidden layer radial basis functions is very important and directly affects the goodness of fit of overall network classification ability.
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.
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.
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