RBF network can model nonlinear time series with high precision;
RBF网络对非线性时间序列具有很高的建模精度；
RBF network on line recognition, single neuron PID control and control algorithm are introduced.
介绍了RBF网络在线辨识、单神经元PID控制器和控制算法。
RBF network with high generalization is a good classifier, especially for larger number of samples.
径向基网络作为分类器具有很高的推广性能，有利于大容量样本的分类。
A novel approach of nonlinear distortion compensation technique based on RBF network is proposed here.
提出了一种基于RBF神经网络的非线性失真补偿技术。
Two kinds of methods, BP network and RBF network, were used to model and predict for the Dynamic Error.
利用BP网络以及RBF网络两种方法分别进行动态误差的建模和预测。
This method uses the liability of self-study and self-adaptability of RBF network to turning parameters of system.
该方法利用RBF神经网络的自学习、自适应能力自调整系统的控制参数。
And damage situation of cable-stayed cable is simulated by using RBF network based on finite element model in ANSYS.
基于ANSYS有限元模型，采用RBF网络，模拟了斜拉索的损伤情况。
The paper presented an idea of applying information fusion technology based on RBF network in fault diagnosis of gas sensor.
文章提出了将基于RBF网络的信息融合技术应用于瓦斯传感器故障诊断的思想。
A new model of lake and reservoir eutrophication assessment can be established with RBF network of artificial neural network.
运用人工神经网络中的RBF网络算法，建立一种新的湖库水质富营养化程度评价模型。
Result of traditional RBF network may not be the best, if network structure is defined by empirical formula or the tester before training.
由于传统RBF神经网络在学习前需要通过经验公式或实验者人为确定网络结构，这样训练出的网络往往并非最优。
Aimed at the problems of document automatic classification, a classification method is proposed based on fuzzy vector space model and RBF network.
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。
The RBF network is trained by the real- time data of all kinds of correlative parameters. It is used to estimate the water drum level with high accuracy.
首先用影响汽包水位的各种相关参量的实测数据对RBF网络进行训练，然后用达到训练目标的RBF网络对汽包水位进行较高精度的估值；
A learning algorithm of subtractive clustering for RBF network is used to obtain the parameters of radial basis function so as to optimize network structure.
在RBF网络中采用了一种减聚类的学习算法来确定径向基函数的相应参数，使网络结构得到优化。
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.
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。
It has been demonstrated by the recognition experiment that the network has higher correct recognition rate and better adaptability to untrained targets than BP or RBF network.
试验表明，该网络的分类能力及对未训练目标的适应性优于BP网和RBF网。
RBF neural network has a strong clustering and fault-tolerant, and the training speed of RBF network is faster than the BP network, so RBF neural network is better on the whole.
RBF神经网络体现出较强的容错性和聚类性，且RBF网络的训练速度比BP网络快，整体而言效果更好。
The discrepancy between the output of the RBF network and the actual value of the sensor is compared with the predetermined threshold to detect the failures of drum level sensor;
通过高精度RBF网络逼近器输出和水位传感器实际输出之差与设定的阈值比较检测传感器故障；
The RBF network possesses the advantages of Kohonen and regression networks. A test was performed to prove the effectiveness of RBF to complement the incomplete spatial information.
利用径向基人工神经网络（RBF）同时具有自组织神经网络和回归网络的优点，可以对缺失数据进行预测。
Surface reconstruction for complex micro-landform is proposed using RBF network model in this paper and RBF network fit for curved surface reconstruction is accordingly established.
采用RBF网络模型进行复杂微地形曲面重构，建立了适应于曲面重构的RBF网络模型。
The application of the algorithm in multiuser detection problems demonstrates that the RBF network trained with the algorithm is concise in structure and has good anti-MAI performance.
将该方法用于多用户检测问题的实验结果表明，采用这种混合算法训练的RBF网络结构精简，具有很好的抗多址干扰的性能。
Through constructing the RBF network approximation facility, this paper proposes a novel fault diagnosis structure and method applying RBF network to the fault diagnosis of drum level sensor.
本文将基于RBF网络的信息融合技术应用于水位传感器的故障诊断，通过构建高精度RBF 网络逼近器，提出了一种新的故障诊断结构和诊断方法。
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).
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 structure and features of radial basis function (RBF) network are introduced.
介绍了径向基函数(RBF)神经网络的结构和特点。
A two-level learning method combining improved immune algorithm and least square method was proposed to design a radial basis function (RBF) network.
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。
Finally, the cylinder pressure is identified by using radial base function (RBF) network, which is featured with the powerful functional approach.
最后，利用径向基函数网络强大的函数逼近功能，识别内燃机气缸压力。
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.
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。
A nonlinear internal model control (IMC) strategy based on radial basis function (RBF) network models was proposed for bulk polymerization of styrene.
文中研究基于径向基(RBF)神经网络算法的内模控制策略在苯乙烯本体聚合反应相对分子质量分布控制领域的应用。
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.
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.
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。
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