Description: RBF network approximation, RBF-modeling, RBF network training and testing procedures
- [RBF-nn] - four input layer, hidden layer 3, the ou
- [rbf] - rbf neural network matlab procedures, co
- [NeuralNetwork_RBF_Regression] - rbf neural networks for regression matla
- [11] - Examples of neural network sets. Procedu
- [RBFFunction] - RBF network for function approximation i
- [RBF] - Based on many years of teaching experien
- [ga-RBF] - Based on genetic algorithm rbf radial ba
- [rbf] - RBF MATLAB
- [rbf] - rbf neural networks for machine fault di
- [RBF_sourcecode] - RBF learning methods, including: k-means
File list (Check if you may need any files):
NN_RBF
......\BP-RBF-建模
......\...........\BP
......\...........\..\BP.m
......\...........\..\BP建模.m
......\...........\..\BP预测.m
......\...........\MLR建模.m
......\...........\MLR预测.m
......\...........\RBF
......\...........\...\11.m
......\...........\...\22.m
......\...........\...\33.m
......\...........\...\RBF建模.m
......\...........\...\RBF预测.m
......\...........\...\建模.m
......\...........\...\建模1.m
......\...........\主元处理.m
......\...........\原始数据集.m
......\...........\大曲原始数据.m
......\...........\大曲归一化.m
......\...........\大曲预处理后数据.m
......\...........\建模数据集.m
......\...........\数据
......\...........\....\PCA降维.m
......\...........\....\主元处理.m
......\...........\....\原始数据集.m
......\...........\....\建模数据集.m
......\...........\....\归一化后的数据集.m
......\...........\....\归一后建模数据集.m
......\...........\....\归一后校验数据集.m
......\...........\....\数据标准化处理.m
......\...........\....\数据标准化处理（建模）.m
......\...........\....\数据标准化处理（测试）.m
......\...........\....\校验数据集.m
......\...........\....\预处理后的数据.m
......\...........\校验数据集.m
......\...........\线性回归法.m
......\bp_ga
......\.....\cross_over.m
......\.....\fitness.m
......\.....\main.m
......\.....\mutation.m
......\.....\select.m
......\bp算法
......\......\gabpEval.m
......\......\gadecod.m
......\......\nninit.m
......\gabp.m
......\kmeans算法
......\..........\kmeans.m
......\..........\kmeans_evaluation1.m
......\..........\kmeans_evaluation2.m
......\..........\kmeans_evaluation3.m
......\..........\kmeans_evaluation4.m
......\..........\kmeans_scan.m
......\matlab常用函数.doc
......\nnet
......\....\mcc.enc
......\....\nncontrol
......\....\.........\ballrepel0.mdl
......\....\.........\calcjjdjj.m
......\....\.........\Contents.m
......\....\.........\csrchbac.m
......\....\.........\csrchbre.m
......\....\.........\csrchcha.m
......\....\.........\csrchgol.m
......\....\.........\csrchhyb.m
......\....\.........\cstr.mdl
......\....\.........\dnetinv.m
......\....\.........\dyduvar.m
......\....\.........\mrefrobotarm.mdl
......\....\.........\mrefrobotarm2.mdl
......\....\.........\narmamaglev.mdl
......\....\.........\netinv.m
......\....\.........\nncontrolutil.m
......\....\.........\predball.mdl
......\....\.........\predcstr.mdl
......\....\.........\predopt.m
......\....\.........\private
......\....\.........\.......\calcgradxmodref.m
......\....\.........\.......\calcgxmodref.m
......\....\.........\.......\calcperf2.m
......\....\.........\.......\nndataexport.m
......\....\.........\.......\nndataexporthelp.m
......\....\.........\.......\nndataimport.m
......\....\.........\.......\nndataimporthelp.m
......\....\.........\.......\nnexport.m
......\....\.........\.......\nnexporthelp.m
......\....\.........\.......\nnident.m
......\....\.........\.......\nnidenthelp.m
......\....\.........\.......\nnimport.m
......\....\.........\.......\nnimporthelp.m
......\....\.........\.......\nnmodref.m
......\....\.........\.......\nnmodrefhelp.m
......\....\.........\.......\nnpredict.m
......\....\.........\.......\nnpredicthelp.m
......\....\.........\ptest3sim2.mdl
......\....\.........\robotarm.mdl
......\....\.........\robotref.mdl
......\....\.........\sfunxy2.m
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