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聚类算法:聚类分析是指事先不了解一批样品中的每一个样品的类别
基于k均值聚类学习算法的rbf神经网络实现-Clustering algorithm: cluster analysis is the prior knowledge of each batch of samples in the sample of category learning algorithm based on k means clustering of rbf neural network
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mtlab粒子群优化模糊RBF神经网络整定PID控制-mtlab Particle Swarm Optimization Fuzzy RBF neural network PID control tuning
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A project for function approximation by RBF neural network (with GUI).
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BP神经网络和RBF神经网络的仿真比较,附有程序代码。-BP neural network and RBF neural network simulation compared with a program code.
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matlab软件机器人神经网络控制的RBF网络逼近仿真-matlab neural network robot control software RBF network simulation approach
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BPnet.m、GRNNnet、RBFnet分别为BP神经网络、GRNN神经网络、RBF神经网络用于预报模型的代码,其中给出预报的精度指标:合格率、确定性系数、均方根误差-BPnet.m, GRNNnet, RBFnet were BP neural network, GRNN neural network, RBF neural network for forecasting model code, which gives the prediction accuracy indicators:
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Matlab神经网络工具箱函数涉及的网络模型有,感知机网络、线性神经网络、BP神经网络、径向基神经网络、自组织神经网络、学习向量量化神经网络、Elman神经网络、Hopfield神经网络、自适应滤波和控制系统网络等。-Matlab neural network toolbox function involving network model have a perceptron and linear neural network, BP neural network, RBF neural net
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用MATLAB实现了BP神经网络以及RBF神经网络,附带有测试的数据集。-Using MATLAB BP neural network and RBF neural network, comes with test data sets.
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利用RBF神经网络对非线性函数进行回归分析(The nonlinear function is regressed by RBF neural network)
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用RBF神经网络算法对非线性干扰进行估计,提高控制精度,并将其与普通滑模控制进行比较。(The RBF neural network algorithm is used to estimate the nonlinear disturbance, and the control accuracy is improved.)
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利用RBF和BP神经网络中的工具箱函数去做函数逼近,(Making use of RBF neural network to do function approximation)
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RBF 神经网络matlab 程序,应该对大家有所帮助(MATLAB program based on RBF neural network. It is very useful .)
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RBF神经网络,可实现对风速预测等时间序列的预测(RBF neural network which can be used to predict time list)
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RBF神经网络的训练 MATLAB源程序代码(RBF neural network training MATLAB source code)
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RBF神经网络的matlab实现,简单易懂(RBF neural network matlab implementation, easy to understand)
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遗传算法优化RBF神经网络逼近非线性函数,具有较好的效果(Genetic algorithm, optimization, RBF neural network, approximation)
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自己编写RBF神经网络程序,RBF神经网络隐层采用标准Gaussian径向基函数,输出层采用线性激活函数,其中数据中心、扩展常数和输出权值均用梯度法求解,它们的学习率均为0.001。其中隐节点数选为10,初始输出权值取[-0.1,0.1]内的随机值,初始数据中心取[-1,1]内的随机值,初始扩展常数取[0.1,0.3]内的随机值,输入采用[0 1]的随机阶跃输入(Write your own RBF neural network, RBF neural network hidden layer
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《RBF神经网络自适应控制的matlab仿真》刘金琨著 程序包("RBF neural network adaptive control matlab simulation" Liu Jinkun program package)
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RBF神经网络C++实现,使用Visual C++6.0打开,可直接编译运行。(RBF neural network C++ implementation, using Visual C++6.0 to open, can be directly compiled and run.)
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该文件是用RBF神经网络算法对图像进行处理的一个很好的借鉴的文章(The file is a good reference to the image processing with the RBF neural network algorithm.)
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