Sieć neuronowa 3w

clear off
nntwarn  off
format compact

P=-1:.1:-.5;
T=[-.9602, -.5770, -.0729, .3771, .6405, .6600];
[R,Q]=size(P);
S1=13;
S2=7;
[S3,Q]=size(T);
[W1,B1]=nwtan(S1,R);
[W2,B2]=nwtan(S2,S1);
[W3,B3]=rands(S3,S2);
disp_freq=100;
max_epoch=20000;
err_goal=0.01;
lr=0.01;
error=[];
A1=tansig(W1*P,B1);
A2=tansig(W2*A1,B2);
A3=purelin(W3*A2,B3);
E=T-A3;
SSE=sumsqr(E);

for epoch=1:max_epoch
if SSE<err_goal
     epoch=epoch-1;
     break
 end
  D3=deltalin(A3,E);
  D2=deltatan(A2,D3,W3);
  D1=deltatan(A1,D2,W2);
 [dW1,dB1]=learnbp(P,D1,lr);
 [dW2,dB2]=learnbp(A1,D2,lr);
 [dW3,dB3]=learnbp(A2,D3,lr);
 W1=W1+dW1; B1=B1+dB1;
 W2=W2+dW2; B2=B2+dB2;
 W3=W3+dW3; B3=B3+dB3;
 A1=tansig(W1*P,B1);
 A2=tansig(W2*A1,B2);
 A3=purelin(W3*A2,B3);
 E=T-A3;
 SSE=sumsqr(E);
 error=[error SSE];


if(rem(epoch,disp_freq)==0)
    epoch
    SSE
    plot(P,T,'r',P,A3,'g')
    pause(1e-50)
end
end

 epoch
 SSE