function para=training100b(para,output,input,qn,ep)
net2=zeros(9,1);
net3=zeros(10,1);

O2=zeros(9,1);
O3=zeros(10,1);
w12=para(1:9,1:100);
w23=para(10:19,101:109);
In=reshape(input,100,1);
net2=w12*In;
O2=sigmf(net2,[1 0]);
net3=w23*O2;
O3=sigmf(net3,[1,0]);

df3=O3.*(1-O3);
h3=-(output-O3).*df3;
dw23=-qn.*h3*O2';
w23=w23+dw23;

df2=O2.*(1-O2);
h2=w23'*h3.*df2;
dw12=-qn.*h2*In';
w12=w12+dw12;

para(1:9,1:100)=w12;
para(10:19,101:109)=w23;