function [y,a,weights]=train_CMAC_NLMS(InpPat,TarPat,n_fun,weights,Inter,num_knot,n_fun_over,disp_matrix,gener,iter,neta);

[m,n]=size(InpPat);
for j=1:iter
   for i=1:m
      [a(i,:),ender]=out_basis(InpPat(i,:),n_fun,Inter,num_knot,n_fun_over,disp_matrix,gener);
      y(i)=a(i,[ender])*weights([ender]);
      e(i)=TarPat(i)-y(i);
      den=norm(a(i,[ender]))^2;
		for k=1:gener
         weights(ender(k))=weights(ender(k))+neta*e(i)*a(ender(k))'/den;
      end   
   end
   norm(e)
end