matlab newff,新版Matlab中神经网络训练函数Newff的使用方法.doc

新版Matlab中神经网络训练函数Newff的使用方法

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

PR x Q1 matrix of Q1 sample R-element input vectorsTSN x Q2 matrix of Q2 sample SN-element target vectorsSiSize of ith layer, for N-1 layers, default = [ ].(Output layer size SN is determined from T.)TFiTransfer function of ith layer. (Default = 'tansig' forhidden layers and 'purelin' for output layer.)BTFBackpropagation network training function (default = 'trainlm')BLFBackpropagation weight/bias learning function (default = 'learngdm')IPFRow cell array of input processing functions. (Default = {'fixunknowns','removeconstantrows','mapminmax'})OPFRow cell array of output processing functions. (Default = {'removeconstantrows','mapminmax'})DDFData 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')

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),[7,1],{'tansig','purelin'},'trainlm');

新版定义：net=newff(input,output,7,{'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),[49,10,1],{'tansig','tansig','tansig'},'traingdx');

新版定义：net=newff(input,output, [49,10], {'tansig','tansig','tansig'},'traingdx');

旧版newff使用方法在新版本中使用

提示：旧版本定义的newff虽也能在新版本中使用，但会有警告，警告如下：

Warning: NEWFF used in an obsolete way. > In obs_use at 18??In newff>crea