bp_trainbr2.m

人工神经网络资料

clear
P=[-1:0.05:1]
%randn('seed',78341223);
T=sin(2*pi*P)+0.1*randn(size(P))
figure(1)
TI=sin(2*pi*P);
plot(P,TI,'R');
hold on
pause
plot(P,T,'B');
pause
clc
net=newff(minmax(P),[1,20,1],{'tansig','tansig','purelin'})%创建前向Bp神经网络
pause
net.trainFcn='trainbr'       %贝叶斯规范化BP训练函数
net.trainParam.epochs=500    %训练次数
net.trainParam.goal=1e-6     %训练目标
net=init(net)
[net,tr]=train(net,P,T);
A=sim(net,P)
E=T-A
MSE=mse(E)        %均方误差性能函数
figure(2)
plot(P,sin(2*pi*P),':',P,A,'B+')