文件名称:BP-curve-in-MATLAB
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该压缩包包含神经网络在MATLAB里的应用：
1、非线性函数拟合
2、RBF网络-非线性函数回归
3、粒子群算法非线性极值寻优
4、神经网络极值寻优
5、神经网络建模自变量降维
6、BP网络-非线性函数回归-The archive contains neural network in MATLAB: 1, non-linear function fitting 2, RBF network- 3 nonlinear function regression, nonlinear algorithm particle swarm optimization four extremes, extremes of neural network optimization 5, nerve network modeling arguments dimensionality reduction 6, BP network- nonlinear function regression
1、非线性函数拟合
2、RBF网络-非线性函数回归
3、粒子群算法非线性极值寻优
4、神经网络极值寻优
5、神经网络建模自变量降维
6、BP网络-非线性函数回归-The archive contains neural network in MATLAB: 1, non-linear function fitting 2, RBF network- 3 nonlinear function regression, nonlinear algorithm particle swarm optimization four extremes, extremes of neural network optimization 5, nerve network modeling arguments dimensionality reduction 6, BP network- nonlinear function regression
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下载文件列表
神经网络在MATLAB的应用（非线性及降维）
......................................\BP神经网络的非线性系统建模-非线性函数拟合
......................................\.........................................\BP.m
......................................\.........................................\BP_Hidden.m
......................................\.........................................\data.mat
......................................\RBF网络的回归-非线性函数回归的实现
......................................\..................................\chapter7_1.m
......................................\..................................\chapter7_2.m
......................................\..................................\运行提示.txt
......................................\神经网络遗传算法函数极值寻优-非线性函数极值
......................................\...........................................\BP.m
......................................\...........................................\Code.m
......................................\...........................................\Cross.m
......................................\...........................................\data.m
......................................\...........................................\data.mat
......................................\...........................................\fun.m
......................................\...........................................\Genetic.m
......................................\...........................................\Mutation.m
......................................\...........................................\net.mat
......................................\...........................................\Select.m
......................................\...........................................\test.asv
......................................\...........................................\test.m
......................................\粒子群算法的寻优算法-非线性函数极值寻优
......................................\.......................................\fun.m
......................................\.......................................\PSO.m
......................................\.......................................\PSOMutation.m
......................................\遗传算法优化BP神经网络-非线性函数拟合
......................................\.....................................\BP.m
......................................\.....................................\Code.m
......................................\.....................................\Cross.m
......................................\.....................................\data.mat
......................................\.....................................\Decode.m
......................................\.....................................\fun.m
......................................\.....................................\Genetic.m
......................................\.....................................\Mutation.m
......................................\.....................................\Select.m
......................................\.....................................\test.m
......................................\遗传算法的优化计算——建模自变量降维
......................................\....................................\data.mat
......................................\....................................\de_code.m
......................................\....................................\fitness.m
......................................\....................................\gabpEval.m
......................................\....................................\gadecod.m
......................................\....................................\main.m