利用MATLAB实现CNN算法的代码,并提供一个例子
时间: 2024-02-25 19:59:11 浏览: 63
好的,我可以为您提供一个MATLAB实现的CNN代码,并附上一个数字识别的例子。
首先,我们需要导入MNIST数据集:
```matlab
% 导入MNIST数据集
[XTrain, YTrain] = digitTrain4DArrayData;
[XTest, YTest] = digitTest4DArrayData;
```
接下来,我们可以构建CNN模型:
```matlab
% 构建CNN模型
layers = [
imageInputLayer([28 28 1])
convolution2dLayer(5,20)
reluLayer
maxPooling2dLayer(2,'Stride',2)
fullyConnectedLayer(10)
softmaxLayer
classificationLayer];
options = trainingOptions('sgdm', ...
'MaxEpochs',10, ...
'ValidationData',{XTest,YTest}, ...
'ValidationFrequency',30, ...
'Verbose',false, ...
'Plots','training-progress');
net = trainNetwork(XTrain,YTrain,layers,options);
```
最后,我们可以使用测试集数据对模型进行测试,并输出预测结果:
```matlab
% 对测试集数据进行预测并输出结果
YPred = classify(net,XTest);
accuracy = sum(YPred == YTest)/numel(YTest);
fprintf('Accuracy = %0.2f%%\n',accuracy*100);
```
这里的代码实现了一个简单的CNN模型,用于对手写数字进行识别。您可以根据自己的需求修改模型的结构和参数。
希望这个例子对您有所帮助!
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