clc
clear
%%?構造真實訓練樣本?60000個樣本?1*784維（28*28展開）
load?mnist_uint8;

train_x?=?double（train_x（1:60000:））?/?255;
%?真實樣本認為為標簽?[1?0]；?生成樣本為[0?1];
train_y?=?double（ones（size（train_x1）1））;
%?normalize
train_x?=?mapminmax（train_x?0?1）;

rand（‘state‘0）
%%?構造模擬訓練樣本?60000個樣本?1*100維
test_x?=?normrnd（01[60000100]）;?%?0-255的整數
test_x?=?mapminmax（test_x?0?1）;

test_y?=?double（zeros（size（test_x1）1））;
test_y_rel?=?double（ones（size（test_x1）1））;

%%
nn_G_t?=?nnsetup（[100?784]）;
nn_G_t.activation_function?=?‘sigm‘;
nn_G_t.output?=?‘sigm‘;

nn_D?=?nnsetup（[784?100?1]）;
nn_D.weightPenaltyL2?=?1e-4;??%??L2?weight?decay
nn.dropoutFraction?=?0.5;???%??Dropout?fraction?
nn.learningRate?=?0.01;????????????????%??Sigm?require?a?lower?learning?rate
nn_D.activation_function?=?‘sigm‘;
nn_D.output?=?‘sigm‘;
%?nn_D.weightPenaltyL2?=?1e-4;??%??L2?weight?decay

nn_G?=?nnsetup（[100?784?100?1]）;
nn_D.weightPenaltyL2?=?1e-4;??%??L2?weight?decay
nn.dropoutFraction?=?0.5;???%??Dropout?fraction?
nn.learningRate?=?0.01;????????????????%??Sigm?require?a?lower?learning?rate
nn_G.activation_function?=?‘