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标题: 新版Matlab中神经网络训练函数Newff的详细讲解 [打印本页]

作者: 百年孤独 时间: 2013-7-20 11:58
标题: 新版Matlab中神经网络训练函数Newff的详细讲解

新版Matlab中神经网络训练函数Newff的详细讲解

一、介绍新版newff
Syntax
·       net = newff(P,T,[S1 S2...S(N-l)],{TF1 TF2...TFNl}, BTF,BLF,PF,IPF,OPF,DDF)
Description
newff(P,T,[S1 S2...S(N-l)],{TF1 TF2...TFNl}, BTF,BLF,PF,IPF,OPF,DDF) takes several arguments

P
R x Q1 matrix of Q1 sample R-element input vectors
T
SN x Q2 matrix of Q2 sample SN-element target vectors
Si
Size of ith layer, for N-1 layers, default = [ ].
(Output layer size SN is determined from T.)
TFi
Transfer function of ith layer. (Default = 'tansig' for
hidden layers and 'purelin' for output layer.)
BTF
Backpropagation network training function (default = 'trainlm')
BLF
Backpropagation weight/bias learning function (default = 'learngdm')
IPF
Row cell array of input processing functions. (Default = {'fixunknowns','removeconstantrows','mapminmax'})
OPF
Row cell array of output processing functions. (Default = {'removeconstantrows','mapminmax'})
DDF
Data divison function (default = 'dividerand')

Examples
Here is a problem consisting of inputs P and targets T to be solved with a network.
·       P = [0 1 2 3 4 5 6 7 8 9 10];T = [0 1 2 3 4 3 2 1 2 3 4];
Here a network is created with one hidden layer of five neurons.
·       net = newff(P,T,5);
The network is simulated and its output plotted against the targets.
·       Y = sim(net,P);plot(P,T,P,Y,'o')
The network is trained for 50 epochs. Again the network's output is plotted.
·       net.trainParam.epochs = 50;net = train(net,P,T);Y = sim(net,P);
plot(P,T,P,Y,'o')

二、新版newff与旧版newff调用语法对比
Example1
比如输入input（6*1000），输出output为（4*1000），那么
旧版定义：net=newff(minmax(input),[14,4],{'tansig','purelin'},'trainlm');
新版定义：net=newff(input,output,14,{'tansig','purelin'},'trainlm');
Example2
比如输入input（6*1000），输出output为（4*1000），那么
旧版定义：net=newff(minmax(input),[49,10,4],{'tansig','tansig','tansig'},'traingdx');
新版定义：net=newff(input,output, [49,10], {'tansig','tansig','tansig'},'traingdx');
更详细请看word文档

新版Matlab中神经网络训练函数Newff的使用方法.doc (175 KB, 下载次数: 28)

作者: liziyan 时间: 2013-7-20 13:27
牛人啊！！！

作者: 西交峨眉 时间: 2017-4-25 22:05
谢谢，正好不知道怎么用

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