neural_network_function_2d.matlab

x1=-1.0; x2=+1.0; y1=-1.5; y2=+4.5; 
nx=7; ny=9; 
step_x=(x2-x1)/(nx-1); step_y=(y2-y1)/(ny-1); 
step_min = min(step_x,step_y); 
[x,y]=meshgrid([x1:step_x:x2], [y1:step_y:y2]); 
z= x.^3 + 5.*x.^2.*y + x - y.^3; 
surf(x,y,z), title('PS. Press<enter>'); 
pause; 
xx=reshape(x,1,nx*ny); 
yy=reshape(y,1,nx*ny); 
zz= xx.^3 + 5.*xx.^2.*yy + xx - yy.^3; 
p=[xx; yy]; 
t=zz; 
goal = 0.0371; 
spread = 1.0*step_min; 
net = newrb(p,t, goal,spread); 
net.layers{1}.size 
smlt=sim(net,p); 
[zz' smlt'] 
smltr=reshape(smlt,ny,nx); 
surf(x,y,smltr), title('AS. Press<enter>');