gusucode.com > 《MATLAB神经网络超级学习手册》随书光盘源码程序 > code/13/Untitled.m

    clear all
clc


net=network

net.numInputs=2;
net.numLayers=3;
net.biasConnect=[1 0 1]';
net.inputConnect=[1 0;1 1;0 0];
net.layerConnect=[0 0 0;0 0 0;1 1 1];
net.outputConnect=[0 1 1];
net.targetConnect=[0 0 1];

net.inputs{1}.range=[0 2;0 2];
net.inputs{2}.range=[-2 2;-2 2; -2 2; -2 2; -2 2];


% net.inputs{1}
% net.inputs{2}
% 
% 
% 
% net.layers{1}



net.layers{1}.size=4;
net.layers{1}.initFcn='initnw';
net.layers{1}.transferFcn='tansig';
net.layers{2}.size=3;
net.layers{2}.initFcn='initnw';
net.layers{2}.transferFcn='logsig';
net.layers{3}.size=1;
net.layers{3}.initFcn='initnw';
% net.layers{3}.transferFcn='logsig';
% 
% net.layers{1}
% net.layers{2}
% net.layers{3}



% net.outputs{1}
% net.outputs{2}
% net.outputs{3}



% net.targets{1}
% net.targets{2}
% net.targets{3}



% net.biases{1}
% net.biases{2}
% net.biases{3}
% 
% 
% 
% net.inputWeights{1,1}
% net.inputWeights{1,2}
% net.inputWeights{2,1}
% net.inputWeights{2,2}
% net.inputWeights{3,1}
% net.inputWeights{3,2}



net.inputWeights{2,1}.delays=[0 1];
net.inputWeights{2,2}.delays=1;
% net.inputWeights{3,3}.delays=1;

% net.layerWeights{1,1}
% net.layerWeights{1,2}
% net.layerWeights{1,3}
% net.layerWeights{2,1}
% net.layerWeights{2,2}
% net.layerWeights{2,3}
% net.layerWeights{3,1}
% net.layerWeights{3,2}
% net.layerWeights{3,3}
% 
% 
% 
% 
% net.layerWeights{1,1}
% net.layerWeights{1,2}
% net.layerWeights{1,3}
% net.layerWeights{2,1}
% net.layerWeights{2,2}
% net.layerWeights{2,3}
% net.layerWeights{3,1}
% net.layerWeights{3,2}
% net.layerWeights{3,3}



net.layerWeights{3,3}.delays=1;



net.initFcn='initlay';
net.performFcn='mse';
net.trainFcn='trainlm';



% net.IW;
% net.LW;
% net.b;



net=init(net);

p={[0;0] [2;0.5];[2;-2;1;0;1] [-1;-1;1;0;1]};
t={1 -1};
net=train(net,p,t)