能·生成一个DenseNet网络的matlab代码吗

当然可以，以下是一个基于DenseNet的Matlab代码示例：

inputSize = [32 32 3];
numClasses = 10;

layers = [
    imageInputLayer(inputSize)

    convolution2dLayer(3,16,'Padding','same')
    batchNormalizationLayer
    reluLayer

    densenetBlock(2,16)
    additionLayer(2)
    reluLayer

    convolutionalUnit(32)
    densenetBlock(4,32)
    additionLayer(2)
    reluLayer

    convolutionalUnit(64)
    densenetBlock(8,64)
    additionLayer(2)
    reluLayer

    convolutionalUnit(128)
    densenetBlock(16,128)
    additionLayer(2)
    reluLayer

    fullyConnectedLayer(numClasses)
    softmaxLayer
    classificationLayer];

options = trainingOptions('sgdm', ...
    'InitialLearnRate',0.001, ...
    'MaxEpochs',20, ...
    'MiniBatchSize',128, ...
    'Plots','training-progress');

net = trainNetwork(trainimds,layers,options);

这个示例代码使用了一个四层的DenseNet结构用于图像分类任务。你可以根据你的具体需求调整网络结构和训练参数。