matlab實作CNN代碼test_example_CNN_MNIST.m注釋版

function test_example_CNN

addpath(‘CNN/’);

load mnist_uint8;

train_x = double(reshape(train_x’,28,28,60000))/255;%訓練集使用minist資料，将圖像進行歸一化，圖像大小28*28，總共60000張圖像，除以255是将圖像的像素值規約到0-1的範圍内

test_x = double(reshape(test_x’,28,28,10000))/255;%将測試圖像進行歸一化

train_y = double(train_y’);%強制類型轉換，轉換為double型，訓練标簽大小為10*60000，因為資料集為手寫體數字，總共有10類，60000張圖像

test_y = double(test_y’);%測試集标簽，大小為10*10000，共有10000張圖像為測試集

%% ex1 Train a 6c-2s-12c-2s Convolutional neural network

%will run 1 epoch in about 200 second and get around 11% error.

%With 100 epochs you’ll get around 1.2% error

rand(‘state’,0)

cnn.layers = {

struct(‘type’, ‘i’) %input layer

struct(‘type’, ‘c’, ‘outputmaps’, 6, ‘kernelsize’, 5) %convolution layer,outputmaps卷積核個數6,kenelsize卷積核大小5*5

struct(‘type’, ‘s’, ‘scale’, 2) %sub sampling laye