bp1.asv

bp神经网络识别数字

net=newff([-1 2; 0 5],[3,1],{'tansig','purelin'},'traingd');
net.trainParam.show = 50; 
net.trainParam.lr = 0.05; 
net.trainParam.epochs = 300; 
net.trainParam.goal = 1e-5; 
p = [-1 -1 2 2;0 5 0 5]; 
t = [-1 -1 1 1]; 
net=train(net,p,t); 
TRAINGD, Epoch 10/300, MSE 1.59423/1e-05, Gradient 
2.76799/ 1e-10
TRAINGD, Epoch 50/300, MSE 0.00236382/1e-05, Gradient 
0.0495292/1e-10 
TRAINGD, Epoch 100/300, MSE 0.000435947/1e-05, Gradient 
0.0161202/1e-10 TRAINGD, Epoch 150/300, MSE 8.68462e-05/1e-05, Gradient 
0.00769588/1e-10 TRAINGD, Epoch 200/300, MSE 1.45042e-05/1e-05, Gradient 
0.00325667/1e-10 TRAINGD,Epoch 211/300, MSE 9.64816e-06/1e-05, Gradient 
0.00266775/1e-10 TRAINGD,Performance goal met. 
a = sim(net,p)