bp.m

用于信号检测

x=[-10,-5,-3,0,1,2,3,-4,-2,1.5,2.5;-0.01,-0.005,-0.002,0,0.002,0.005,0.01,-0.03,0.001,0.004,0.007];%输入样本
t=[0,0,0,1,1,1,1,0.1,0.3,1,1;0,0,0.3,0,0,0,0,0.15,0.2,0,0;0,0.7,0.6,0,0,0,0,0.65,0.4,0,0;0,0.3,0.1,0,0,0,0,0.1,0.1,0,0;1,0,0,0,0,0,0,0,0,0,0];%输出样本
hidelayer=49;%设置网络隐含层神经元的个数
lr=0.01;%设置网络的学习率
net=newff(minmax(x),[hidelayer,5],{'tansig','purelin'},'traingdm','learngdm');%建立BP网络
net.trainParam.goal=0.002;%设置网络输出误差最小值
net.trainParam.epochs=30000;%设置最大迭代次数
net.trainParam.lr=lr;
[net,tr]=train(net,x,t);%tr为训练步数与性能
figure(1);
plot(tr.epoch,tr.perf);%性能曲线
xlabel('训练时间epoch');
ylabel('均方差mse');
hold on;
y=sim(net,x);