新版Matlab中神经网络训练函数Newff的使用方法..docVIP

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 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 forhidden 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 networks 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),[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),[49,14,4],{tansig,tansig,tansig},traingdx); 新版定义：net=newff(input,output, [49,14], {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 newffcreate_network at 127??In newff at 102? ?? ?? ? See hel