搜索资源列表
rbfnn3
- 用matlab写的三个径向基神经网络程序，分别为基于聚类的RBF，基于梯度法的RBF ，基于OLS 的RBF神经网络-using Matlab wrote three RBFNN procedures were based on the clustering of RBF, Based on the RBF gradient method, based on the OLS RBFNN
tdrbf
- (转载)在网上找的用梯度下降算法开发的rbf神经网络曲线拟和程序。 -(reproduced) on the Internet to find the gradient descent algorithm development of the neural network rbf curve fitting and procedures.
RBFtiduqwww
- *** ***梯度RBF神经网络-*** *** *** *** *** *** *** *** gradient RBF
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
RBF_s
- 径向基神经网络,使用的算法梯度下降法,比较清晰,适合于初学神经网络的用户-RBF neural network, using gradient descent algorithm, more clarity, suitable for novice users of neural network
RBF
- 基于梯度法编写的RBF神经网络程序，实现对输入数据的逼近-Gradient method based on the preparation process of the RBF neural network to achieve the approximation of the input data
PSOGARBF
- 基本粒子群优化算法 遗传算法，基于聚类，梯度，最小二乘法的RBF网络程序等5个代码-Elementary particle swarm optimization algorithm genetic algorithm, based on clustering, gradient, least-squares method of RBF network program such as 5 code
RBFtidu
- 这是一个用RBF神经网络用梯度算法实现的一个函数逼近源代码-This is a use of RBF neural network algorithm with gradient function approximation of a source code
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.
RBF_2
- 此程序是神经网络中基于梯度的径向基函数算法，在MATLAB中实现。用一个2－n－1结构的RBF网对SISO系统进行建模，网络的两个输入为u(k-1)和y(k-1)，输出为 y(k)。令y(0)=0，按飞线性系统产生200个样本，其中前100个样本用于训练，后100个样本用于测试。-This procedure is based on the gradient neural network radial basis function algorithm is implemented in MATL
RBF_Gradient.m
- rbf梯度法网络来做预测，过程很适合初学者懂的。很详细，很容易的！-RBF gradient method to predict the network, the process is very suitable for beginners understand. Very detailed, easy!
BJM
- 采用梯度下降法确定RBF神经网络基函数的中心，煤气炉数据辨识的仿真研究-Using gradient descent method to determine the center of the RBF neural network basis function, the identification of the gas furnace data simulation study
RBF_OLS
- 利用RBF神经网络通过剪枝算法实现特征选择，训练时采用正交最小二乘方法-RBF feature selection algorithm with gradient decending method
RBF_Gradient
- 该程序组是基于梯度下降算法的RBF网络实现过程，包含了RBF隐含层神经元等参数的具体确定步骤。-this is the RBF network with gradient method
RBF
- 径向基神经网络（RBF网络）的三种学习算法实现：随机选取中心法、自组织选取中心和梯度训练算法-Three radial basis function neural network (RBF) learning algorithm: randomly selected center method, self-organizing selection center and gradient training algorithm
rbf
- rbf逼近的程序，采用梯度下降法进行逼近，效果不错-RBF approximation sin (x), using the gradient descent method
RBF
- 使用k-mean确定RBF网络隐层中心点，后使用改进的梯度下降算法实现径向基神经网络的c++源程序，开发环境vs2010，可直接加载到自己的项目中。-Determined using k-mean RBF hidden layer center, the use of the improved gradient descent algorithm RBF neural network c++ source code, development environment vs2010
tidu-zuixiaoercheng-RBF-rar
- 这是一个梯度算法和最小二乘算法优化RBF神经网络的算法，可以用来对PVC生产中VCM的转化率进行预测，简单实用-This is a gradient algorithm and least squares algorithm of RBF neural network are optimized algorithm, can be used to predict the conversion of the PVC production of VCM, simple and practical
rbf
- 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
RBF自适应
- 基于梯度下降法RBF自适应神经网络控制(RBF adaptive neural network control based on gradient descent method)