搜索资源列表
rbf_Kmeans
- 一个基于K均值聚类的ＲＢＦ神经网络，注释写的很明白，有不明白的地方可以发邮件问我。-a K-means clustering based on the RBF neural network, notes written very well, did not understand the local mail can ask me.
Seven-RBF_NN--code
- 七个RBF神经网络的源代码:基于梯度法、OLS 、聚类、k均值聚类、函数逼近的RBF 网设计算法，及预测模型 -Seven RBF neural network source code: gradient-based method, OLS, clustering, k-means clustering, function approximation of the RBF network design algorithms, and predictive models
k-rbf
- 程序是基于K均值聚类的RBF代码，很好的一个例子。-K means clustering procedure is based on the RBF code, a good example.
rbf_Kmeans
- Matlab环境下实现的RBF神经网络K均值聚类算法-Matlab environment to achieve the RBF neural network K-means clustering algorithm
RBF_sourcecode
- RBF学习方法，包括了：k-means、梯度、OLS三种方法。-RBF learning methods, including: k-means, gradient, OLS three types.
mykmeans
- matlab code for k-means for neural net RBF
rbf_Kmeans
- 基于k均值聚类方法的rbf网络源程序，有需要的就下载吧，-K means clustering method based on rbf network source, there is need to download it,
sf1847
- 数据挖掘建模工具，轻易实现BP神经网络、RBF神经网络、灰色系统、决策树、决策表、贝叶斯、懒惰算法、支持向量机、K均值聚类、Apriori关联规则、HotSpot关联规则、回归分析、指数平滑、季节移动平均及组合等算法建模。-Data mining modeling tools, easy to achieve BP neural network, RBF neural network, gray system, decision tree, decision table, Bayesian, l
k-means-clustering-of-rbf-
- 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
KLS_RBF
- 基于k均值算法聚类和径向基网络的神经网络程序-rbf program based on k-means and ls
KLS_RBF1
- 有归一化的基于k均值聚类和LS的matlab程序，神经网络算法-rbf based on k-means and ls，with standard
K-means
- k均值聚类算法,初始随机给定k个簇中心，根据邻近原则，把待分类的样本点分到各个簇。-k-means clustering algorithm,which is applied in RBF neural network.
RBF-k-means
- 自己编写的RBF聚类程序，采用K均值聚类算法，希望对大家游泳！-Based on RBF neural network program code K-means clustering！
RBF-k
- RBF-k均值聚类算法的matlab程序和样本数据，可用于RBF-k均值聚类算法的仿真。-RBF-k-means clustering algorithm matlab program and sample data, can be used to simulate the RBF-k-means clustering algorithm.
RBF
- 使用k均值聚类的方法生成一个rbf网络，各种参数与网络各层输出的调节非常灵活-construct a rbf neural network using k-means clustering
RBF_K-means
- 考虑Hermit多项式的逼近问题 ，用k-means训练RBF网络-Consider Hermit polynomial approximation problem with k-means training RBF network
fenlei
- K均值聚类分析，可实现2/3/4类的分类，适用于初学者，为实现5/6类的分类提供想法(k-means clustering analysis)
RBF-k均值聚类
- RBF（径向基神经网络）网络是一种重要的神经网络，RBF网络的训练分为两步，第一步是通过聚类算法得到初始的权值，第二步是根据训练数据训练网络的权值。RBF权值的初始聚类方法较为复杂，比较简单的有K均值聚类，复杂的有遗传聚类，蚁群聚类等，这个RBF网络的程序是基于K均值聚类的RBF代码。(RBF (radial basis function network) is an important neural network. The training of RBF network is divided
Untitled2
- k—means函数，RBF网络能够逼近任意的非线性函数，可以处理系统内的难以解析的规律性，具有良好的泛化能力，并有很快的学习收敛速度，已成功应用于非线性函数逼近、时间序列分析、数据分类、模式识别、信息处理、图像处理、系统建模、控制和故障诊断等。(k-means function, RBF network can approximate any non-linear function, can deal with difficult-to-resolve regularity in the sys
PSO-rbf-kmeans
- pso rbf k-means simulik with matlab(programme d'un pso en hybride avec un rbf)