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)