xianxingwangluo.m

根据神经网络的相关原理

P=[1 1.5 1.2 -.3; -1 2 3 -.5;2 1 -1.6 .9];;
T=[0.5 3 -2.2 1.4;1.1 -1.2 1.7 -.4;3 .2 -1.8 -0.4;-1 .1 -1 .6];
net=newlin(minmax(P),4,0,0.01);%1个输出,延迟为0,学习速度为0.01
net=init(net);
net.trainParam.epochs=2000;
net.trainParam.goal=0.0001;
net=train(net,P,T);
y=sim(net,P)
w=net.iw{1}
b=net.b{1}
x=y-T
for i=1:4
    error(i)=norm(x(:,i));
end
error