1、

Comparison on pattern analysis performance of SVM and RVM based on RBF kernel

基于RBF核的SVM及RVM模式分析性能比较

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2、

An interactive human-machine evaluation platform was designed using RBF neural network functions of the MATLAB HNN toolbox.

利用MATLAB神经网络工具箱中的RBF神经网络函数设计出人机交互的人机界面评价平台。

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3、

In fact, FCP is an RBF network, also a fuzzy basis function network.

实际上,它是一种RBF网络,而且还是一种模糊基函数网络。

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4、

RBF Network Model for Cotton Leaf Acarus Occurrence Trends Forecasting

棉叶螨发生趋势的RBF网络预报模型

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5、

At last, the authors use RBF neural network as function approximator to build large-signal model of RF-power component and verify that the model based in RBF neural network can accurately simulate the behavior of RF-power component.

最后,以RBF神经网络作为函数逼近器对射频功率器件建立了大信号特征模型,并进行了模型检验,证明了基于RBF网络的建模方法具有较高的精度。

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6、

These methods include the traditional RBF and the differential operator-geared RBF collocation methods, i.e.the MFS and the BKM ( boundary knot method).

包括通用的径向基函数以及基于算子的径向基函数配置点方法即基本解方法和边界节点方法。

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7、

Novel Optimum Identification for Analog Design-for-Testability ( DfT) Comes from Fast Convergence Identification As RBF is publicly recognized as having good astringency, fast convergence speed and stability of computation, the author attempted to develop an RBF-based optimization algorithm for designing the FIR digital filters.

由于公认为径向基函数网络具有好的收敛性与收敛速度,并且在计算稳定性方面也具有相当好的性能,作者将径向基函数网络的优化算法应用于FIR数字滤波器的设计中。

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8、

It mainlydiscusses artificial cell and perceptron. BP network and RBF network are described in this chapter.

主要讨论人工神经元与感知器以及人工神经网络模型, 包括BP神经 网络和阳F神经网络.

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9、

It can train polynomial function, neural networks, or radial basis function ( RBF ) classifiers .

它可以对多项式函数, 神经网络, 径向 基函数 进行训练.

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10、

The model and learning algorithms of BP ( Error Back Propagation) network, which is widely applied, is recommended, and RBF ( Radial B asis Function) is simply recommended contrastively.

本文首先介绍了神经网络中应用最为成熟广泛的BP网络的模型及其学习算法,并简单对比介绍了RBF网络。

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11、

Direction of Arrival Estimation Approach Based on Phase Angle Feature of Correlation Function Using RBF Neural Networks

基于互相关函数相角特征的RBF神经网络来波方位估计

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12、

For that reason, the paper presented an improved RBF neural networks algorithm based on the nearest adjacent distance that can adaptively adjust width value of central points in basic function in order to attaint the goal approaching samples with high precision and high speed.

为此本文以最近邻距离算法为基础提出一种改进的RBF神经网络算法,能够自适应地调整基函数中心点宽度值以达到高精度、快速逼近样本的目的。

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13、

The RBF Network with the Green function as the active function is a universal approximator in that it can approximate arbitrarily well any multivariate continuous function. It has the potential of dealing with the nonlinear relationship and can forecast the calorific value of coal quickly and exactly.

以格林函数为激活函数的RBF网络是通用逼近器,它可以逼近任意多元连续函数,具有处理非线性关系的强大潜能,可以快速、准确地预测煤发热量。

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14、

So this thesis presents a kind of finite volume methods based on radial basis function ( RBF ).

为此,本文构造了一类基于径向 基函数 插值思想的有限体积格式.

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15、

Experiments on springback in concave and convex edge flanging are carried out. Method of the mixed-level orthogonal test design is used to select the training sets from experiment data, and a radial basis function ( RBF) neural network model for springback is developed.

对薄板内凹、外凸翻边进行了回弹试验,借助混合水平的正交试验设计方法从试验数据中选择训练样本,建立了回弹的径向基函数神经网络模型。

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16、

RBF Method of Pricing Convertible Bond with Credit Risk

可转换债券定价模型的RBF数值解

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17、

In this paper, the principle of nonlinear correction of data by using RBF neural network, the structure of neural network and the determination method of parameters are described.

介绍了利用RBF神经网络进行数据非线性校正的原理以及RBF神经网络结构和参数的确定方法。

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18、

Neural networks use RBF networks, the simulation can achieve better results, the moderate cost of training, applied to forecast the performance of compressors and fault-line diagnosis.

神经网络采用径向基函数(RBF)网络,能够取得较好的仿真效果,训练代价适中,适用于压缩机的性能预测和故障的在线诊断。

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19、

RBF ANN Nonlinear Prediction Model Based Adaptive PID Control of Switched Reluctance Motor

基于RBF神经网络非线性预测模型的开关磁阻电机自适应PID控制

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20、

RBF Neural Network based Variable Structure Control of Backlash and Friction Compensation

基于RBF神经网络变结构控制的齿隙和摩擦补偿

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