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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的使用方法.doc
本帖最后由 小小2008鸟 于 2013-1-15 21:42 编辑
新版Matlab中神经网络训练函数Newff的详细讲解
一、 介绍新版newffSyntax· net = newff],{TF1 TF2...TFNl}, BTF,BLF,PF,IPF,OPF,DDF)
Descriptionnewff],{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 = [ ].
TFiTransfer function of ith layer. (Default = 'tansig' for
hidden layers and 'purelin' for output layer.)BTFBackpropagation network training function BLFBackpropagation weight/bias learning function IPFRow cell array of input processing functions. OPFRow cell array of output processing functions. DDFData divison function
ExamplesHere 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;The network is simulated and its output plotted against the targets.· Y = sim;plotThe network is trained for 50 epochs. Again the network's output is plotted.· net.trainParam.epochs = 50;net = train;Y = sim;
plot
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,[14,4],{'tansig','purelin'},'trainlm');新版定义:net=newff;
Example2比如输入input(6*1000),输出output为(4*1000),那么旧版定义:net=newff,[49,10,4],{'tansig','tansig','tansig'},'traingdx');新版定义:net=newff;
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