bpxtbianshi.m

这是用bp神经网络实现二维系统辨识功能的源程序

w10ij=[0.001 0.001 0.002;0.001 0.001 0.02;0.01 0 0.001;0.001 0.001 0.002;0.001 0 0.002;0.0011 0.001 0.001];
w11ij=[-0.1 -0.02 0.11;-0.21 0.10 -0.19;-0.14 0.15 -0.16;0.14 -0.13 0.17;-0.13 0.12 0.21;-0.16 -0.23 0.13];
w20j=[0.01;0.02;0.1;0.2;0.1;0.1];w21j=[0.18;0.9;0.9;0.7;0.8;0.9];
q0j=[0.5 0.8 0.4 0.6 0.1 0.2];q1j=[-0.1 0.02 0.12 0.14 -0.02 0.02];
q2j=0;p0=0.2;k1=1;p1=0.2; w23j=[0;0;0;0;0;0];w22j=0;w=0;w0=0;
xj=[0.5 0.3 0.2];
ya=[0 0 0];yp=0;yy=0;m1=0;yam=0;yp1=0;qw=0;yo=[0 0 0];ya1=0;error=0.0001;
n=1;q=0;e1=0;e0=0;e2=0;e3=0;e4=0;yo=0;ya=0;yb=0;y0=0;y1=0;
y2=0;y3=0;u=0;u1=0;u2=0;k1=1;kn=28;e3=.055;
a1=0.036;a2=0.036;a3=0.08;w0=1;dj2=0.01;
for m=1:36
for n=1:36
 q=pi*0.05*m;p=pi*0.02*n;
  yn=cos(2*q+2*p)*sin(2*p);yzs=0.1*yn;yp=yn;
  for k=1:6
  for i=1:6
      x1=[w11ij(i,1)*xj(:,1)]+[w11ij(i,2)*xj(:,2)]+[w11ij(i,3)*xj(:,3)];
      x=x1+q1j(:,i); o=tanh(x); o1j(i)=o;
  end
  for i=1:6
      yb=yb+w21j(i,:)*o1j(:,i);end
      yi=yb+p1;y=tanh(yi);
  e0=e1;e1=e2;e2=[(yp-y).^2]/2;
  for i=1:6
      d1=[1-o1j(:,i)]*dj2*w23j(i,:); do=o1j(:,i)*d1;
      q3j(:,i)=q1j(i);
  for j=1:3
      dw=w11ij(i,j)-w10ij(i,j);
  if e2<0.05,  a1=0;a2=0;a3=0; else, a1=0.02;a2=0.05;a3=0.0005;
  end;
  w12ij=w11ij(i,j)+a1*do*xj(j)+a2*dw+a3*w; w13ij(i,j)=w12ij;end
end
  w10ij=w11ij; w11ij=w13ij; q0j=q1j; q1j=q3j;
  w=yp-y; w0=w; w=0.36*w0+(yp-y);
  if e2<0.004,w=0.78*w;end
  for i=1:6
      d2j=y*(1-y)*(yp-y);
      dw=w21j(i,:)-w20j(i,:);
      w22j=w21j(i,:)+0.132*d2j*o1j(i)+0.26*dw;+0.0016*w;
      w23j(i,:)=w22j;
  end
  w20j=w21j;w21j=w23j;
  ph=p1-p0;p2=p1+0.3*(yp-y)+0.102*ph;p0=p1;p1=p2;
  if e2<=0.005 break; else end
end
ypp(m,n)=yn;
yom(m,n)=y;
e3(m,n)=e2;
end
m2=m
end
w11ij=w13ij
w21j=w23j

subplot(2,2,1);
mesh(ypp)
xlabel('m'),ylabel('n'),zlabel('ypp');
subplot(2,2,2);mesh(yom)
xlabel('m'),ylabel('n'),zlabel('yom');
subplot(2,1,2);mesh(e3)
  xlabel('m'),ylabel('n'),zlabel('e3');