搜索资源列表
RBF-nn
- 4输入层,3隐层,2输出层的RBF神经网络分类器 附有测试和训练样本-four input layer, hidden layer 3, the output layer 2 RBF neural network classifiers with testing and training samples
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
RBFxunlian
- rbf训练用于模式识别,分类,故障类别的诊断,收敛快-rbf training for pattern recognition, classification, fault type of diagnosis, fast convergence
GAP-RBF
- 模糊神经网络逼近与分类,模糊规则提取,快速增长与删减网络。-Fuzzy neural network approximation and classification, fuzzy rule extraction, with the deletion of the rapid growth of the network.
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.
rbf
- RBF神经网络用于分类与回归,文件说明: 1、NeuralNetwork_RBF_Classification.m - 分类 2、NeuralNetwork_RBF_Regression.m - 回归-RBF neural network for classification and regression, the document notes: 1, NeuralNetwork_RBF_Classification.m- Category 2, NeuralNetwork_RBF_Re
RBF
- 采用神经网络实现分类器的训练,训练出来的网络分类结果好.-It is a good code to realize the network.
NeuralNetwork_RBF_Classification
- RBF神经网络的一个样本分类的例子,很简单,懂Matlab基础的就能看明白。-RBF neural network classification of a sample of examples of very simple, based on Matlab understand能看明白.
NeuralNetwork_RBF
- RBF人工神经网络的分类和回归方法的仿真实例!-RBF artificial neural network classification and regression methods of simulation!
rbf
- rbf神经网络用于机械故障的诊断,模式识别,分类等-rbf neural networks for machine fault diagnosis, pattern recognition, classification, etc.
fenlei
- rbf神经网络用于分类识别,故障诊断,模式识别,自己编写的-rbf neural network for classification and recognition, fault diagnosis, pattern recognition, have written
RBFNeuralNetwork
- RBF神经网络优化的粒子群优化的预测文献,可以-RBF Neural Network Optimized by Particle Swarm Optimization for Forecasting
RBF
- RBF神经网络用于分类与回归的两个小程序,需要的-NeuralNetwork_RBF for Classification and Regression
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
rbfyaochenghu
- 径向基函数(RBF)神经网络在分类中的应用-Radial Basis Function (RBF) neural network classification
rbf
- 七个径向基人工神经网络的源程序,包括模式分类,以及预测-Seven radial basis artificial neural network source, including pattern classification, and prediction
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
- 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
- RBF神经网络用于三分类 完整matlab算法 可运行(RBF neural network for three classification Complete matlab algorithm Executable)
rbf
- 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。 简单说明一下为什么RBF网络学习收敛得比较快。当网络的一个或多个可调参数(权值或阈值)对任何一个输出都有影响时,这样的网络称为全局逼近网络。由于对于每次输入,网络上的每一个权值都要调整,从而导致全局逼近网络的学习速度很慢。BP网络就是一个典型的例子。(RBF network