径向基函数
- 网络radial basis function;RBF;RBFS
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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 .
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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
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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
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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
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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 .
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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
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径向基函数(RBF)网络在入侵检测中的应用
Application of RBF Network in Intrusion Detection
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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 .
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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 .
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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 .
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一种新颖的径向基函数(RBF)网络学习算法
An Original RBF Network Learning Algorithm
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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 .
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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
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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 .
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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 .
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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 .
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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 .
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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 .
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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 .
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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 .
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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 .
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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 .
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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 .
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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 .
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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 .
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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 .
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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 .
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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 .
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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 .
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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 .