function [out,re_in,re_out]=wnn_implementation(sig_in)

%% implementating the function of wavelet neural network

global node_in node_media node_out  alfa belta w u o layer_j shift_k; 

temp=zeros(1,(2*layer_j+1)*(2*shift_k+1));
% out=zeros(1,node_out);

i=0;

for j=-layer_j:1:layer_j
    for k=-shift_k:1:shift_k
        i=i+1;
        temp(i)=wavelet_function(sig_in*u(i,:)',j,k);
        re_in(i)=sig_in*u(i,:)';
        re_out(i)=temp(i);
    end
end

o=temp*w';
out=o;

for h=1:node_out
    if o(h)>0.5
        out(h)=1;
    elseif o(h)<0.5
        out(h)=0;
    end
end

% o                  % % 顯示每次執行完后網絡的實際輸出值,以便找出錯誤、所在   

return;