www.gusucode.com > 有监督的 CNN 网络完成对MNIST 数字的识别 > 有监督的 CNN 网络完成对MNIST 数字的识别/CNN—卷积神经网络数字识别/back_subsample.m

     function out = back_subsample(e, ratio) 
% back_subsample传播误差通过子样品层
%
%语法：
%
% out = back_subsample(e,ratio)
%
%描述
%输入:
% e -错误的映射
%比例——膨胀率
%
%输出:
%——传播误差图,大小比例*大小(e)
        switch ratio
            case 4
                out = 0;
                for k=1:4
                    for l=1:4
                        out(1+(k-1):4:size(e,1)*4,1+(l-1):4:size(e,2)*4) = e;
                    end
                end
              %  out = out.*0.0625;


            case 2
                out(1:2:size(e,1)*2,1:2:size(e,2)*2)=e;
                out(1:2:size(e,1)*2,2:2:size(e,2)*2)=e;
                out(2:2:size(e,1)*2,1:2:size(e,2)*2)=e;
                out(2:2:size(e,1)*2,2:2:size(e,2)*2)=e;
               % out=out.*0.25;
            case 1
                out = e;
            otherwise disp('Unsupported ratio');
        end

   
    end