搜索资源列表
RBF_OLS
- 此程序是神经网络中径向基函数的OLS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 program is the radial basis function neural network of OLS algorithm is implemented in MATLAB. With a 2-n
RBF
- 完全用C++实现的RBF(径向基函数)算法,可以用于实际工作和学习中-Entirely in C++ implementation of the RBF (Radial Basis Function) algorithm, can be used for practical work and learning
rbf4
- 这是一个径向基函数神经网络,通过RBF网络的学习算法来逼近一个二维函数,并利用LMS算法来进行权值调整。-This is a radial basis function neural network, RBF network learning algorithm adopted to approximate a two-dimensional function, and use of LMS algorithm for weight adjustment.
rbf
- 基于聚类的径向基神经网络算法,matlab实现-Cluster-based radial basis function neural network algorithm, matlab implementation
RBF
- matlab格式源代码。功能:径向基神经网络算法源码和应用于时间序列模型建立和预测问题。-matlab source code format. Function: RBF neural network algorithm source code and applies to time-series model and prediction of the problem.
rbf
- 使用rbf神经网络进行函数拟合,在函数拟合上有很好的效果-Using rbf neural network for function fitting
rbf
- 神经网络的RBF神经网络实现,用于函数拟合的实现-RBF neural network Neural networks for the realization of function fitting
rbf
- 由于本人近阶段在研究神经网络方面的,所以把有关方面的共享给大家。 这段是用rbf函数逼近的源码。可直接编译运行-Due to recent phase I study of neural networks, so the parties to share to everyone. This is the source function approximation rbf. Direct the compiler to run
GGAP-RBF
- 模糊神经网络实现函数逼近与分类,实现模糊规则的提取。-Fuzzy neural network function approximation and classification, to achieve the extraction of fuzzy rules.
GA-RBF
- 1.利用GA算法优化RBFNN的各种权值; 2.利用RBFNN进行函数跟踪; 3.比较测试未用GA优化的和使用GA优化的RBFNN的结果。-1.Use GA algorithm to optimize a variety of weights in RBFNN 2. Use RBFNN to realize tracking function 3. Compare and test the results of using GA and not using GA.
RBF
- 径向基函数神经网络(RBF)的MATLAB程序,比较详细,希望对学习RBF的人有帮助-Radial basis function neural network (RBF) of the MATLAB program, a more detailed study RBF people who want to help
rbf
- 径向基函数网络用于船用柴油机智能诊断的研究-Radial basis function network for intelligent diagnosis of marine diesel engine
RBF网络的回归-非线性函数回归的实现
- 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)
rbf
- 实现径向基神经网络的matlab预测,较好的完成了神经网络的预测控制性能。(Matlab prediction of radial basis function neural networks)
radial basis function network
- RBF神经网络的matlab实现,简单易懂(RBF neural network matlab implementation, easy to understand)
RBF遗传优化
- 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。(RBF network can approximate any nonlinear function, regularity can handle within the system to parse, has good generalization ability and
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-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
RBF神经网络逼近非线性函数
- 利用径向基神经网络逼近非线性函数,MATLAB编程实现,给出训练误差(Radial basis function neural network is used to approximate nonlinear functions. MATLAB programming is implemented to give training error.)
RBF
- 径向基函数神经网络,基本算例.........(radial basis function)
