matlab-(含教程)CNN卷积神经网络训练和测试matlab仿真

clc; clear; close all; warning off; addpath(genpath(pwd)); X1=rand(100,2048); X2=20*rand(100,2048); %%%生成两类幅值不同的随机序列,作为两类待分类样本 Xtrain1=[X1;X2]; for i=1:1:200 for j=1:1:2048 Xtrain(1,j,1,i)=Xtrain1(i,j);%%输入数据维度转化 end end y1=zeros(100,1); y2=ones(100,1); ytrain=[y1;y2]; ytrain=categorical(ytrain);%%函数包要求标签类型是categorical %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% layers = [ ... imageInputLayer([1 2048 1])%%2D-CNN convolution2dLayer([1,2],4) reluLayer maxPooling2dLayer([1 2],'Stride',2) convolution2dLayer([1,2],4) reluLayer maxPooling2dLayer([1 2],'Stride',2) fullyConnectedLayer(2) softmaxLayer classificationLayer]; options = trainingOptions('sgdm', ... 'MaxEpochs',100,... 'InitialLearnRate',1e-4, ...%%训练参数 'Verbose',false, ... 'Plots','training-progress'); net = trainNetwork(Xtrain,ytrain,layers,options);%网络训练 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% X10=rand(100,2048); X20=20*rand(100,2048); Xtest1=[X10;X20]; for ii=1:1:200 for jj=1:1:2048 Xtest(1,jj,1,ii)=Xtest1(ii,jj);%%输入数据维度转化 end end y10=zeros(100,1); y20=ones(100,1); ytest1=[y10;y20]; ytest=categorical(ytest1);%%函数包要求标签类型是categorical YPred = classify(net,Xtest);%%网络测试 YPred1 =double(YPred);%%转化为可显示的标签 accuracy = sum(YPred == ytest)/numel(ytest)