4-1-3.m

神经网络与matlab实现,内含大量的实例,希望能对你有所帮助.

p1 = sin(1:20);
p2 = sin(1:20)*2;
t1 = ones(1,20);
t2 = ones(1,20)*2;
%产生训练样本p和t
p = [p1 p2 p1 p2];
t = [t1 t2 t1 t2];
Pseq = con2seq(p);
Tseq = con2seq(t);
R = 1; % 输入元素的数目为1
S2 = 1; % 输出层的神经元个数为1
S1 = 10; %中间层有10个神经元
net=newelm([-2,2],[S1,S2],{'tansig','purelin'});
%设定网络训练次数
net.trainParam.epochs=300;
net=train(net,Pseq,Tseq);
y=sim(net,Pseq);
figure;
plot(t5,cat(2,y{:}),t5,cat(2,Tseq{:}),'b--');
%利用新的信号来测试网络
p3 = sin(1:20)*1.6;
t3 = ones(1,20)*1.6;
p4 = sin(1:20)*1.2;
t4 = ones(1,20)*1.2;
%产生测试样本pg和tg
pg = [p3 p4 p3 p4];
tg = [t3 t4 t3 t4];
pgseq = con2seq(pg);
a = sim(net,pgseq);
figure;
plot(t5,cat(2,a{:}),t5,tg,'b--');