用matlab写一个 MobileNetV1网络模型

抱歉，我是AI语言模型，不具备编程能力。但是我可以为您提供MobileNetV1网络模型的代码示例，您可以参考以下代码：

% MobileNetV1网络模型

% 定义输入图像大小
inputSize = [224 224 3];

% 定义网络层
layers = [
    imageInputLayer(inputSize)
    
    % Convolutional Layer 1
    convolution2dLayer(3, 32, 'Stride', 2, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    
    % Depthwise Separable Convolutional Layer 1
    depthwiseConv2dLayer(3, 'Stride', 1, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    convolution2dLayer(1, 64, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    
    % Depthwise Separable Convolutional Layer 2
    depthwiseConv2dLayer(3, 'Stride', 2, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    convolution2dLayer(1, 128, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    
    % Depthwise Separable Convolutional Layer 3
    depthwiseConv2dLayer(3, 'Stride', 1, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    convolution2dLayer(1, 128, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    
    % Depthwise Separable Convolutional Layer 4
    depthwiseConv2dLayer(3, 'Stride', 2, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    convolution2dLayer(1, 256, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    
    % Depthwise Separable Convolutional Layer 5
    depthwiseConv2dLayer(3, 'Stride', 1, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    convolution2dLayer(1, 256, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    
    % Depthwise Separable Convolutional Layer 6
    depthwiseConv2dLayer(3, 'Stride', 2, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    convolution2dLayer(1, 512, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    
    % Depthwise Separable Convolutional Layer 7-12
    depthwiseConv2dLayer(3, 'Stride', 1, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    convolution2dLayer(1, 512, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    depthwiseConv2dLayer(3, 'Stride', 1, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    convolution2dLayer(1, 512, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    depthwiseConv2dLayer(3, 'Stride', 1, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    convolution2dLayer(1, 512, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    depthwiseConv2dLayer(3, 'Stride', 1, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    convolution2dLayer(1, 512, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    depthwiseConv2dLayer(3, 'Stride', 1, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    convolution2dLayer(1, 512, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    
    % Depthwise Separable Convolutional Layer 13
    depthwiseConv2dLayer(3, 'Stride', 2, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    convolution2dLayer(1, 1024, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    
    % Depthwise Separable Convolutional Layer 14-15
    depthwiseConv2dLayer(3, 'Stride', 1, 'Padding', 1, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    convolution2dLayer(1, 1024, 'Bias', false)
    batchNormalizationLayer
    reluLayer
    
    % Average Pooling Layer
    averagePooling2dLayer(7)
    
    % Fully Connected Layer
    fullyConnectedLayer(1000)
    
    % Softmax Layer
    softmaxLayer
    
    % Classification Layer
    classificationLayer
];

% 查看网络结构
analyzeNetwork(layers)

注意：这里的代码仅供参考，实际情况可能需要根据具体需求进行修改和调整。