create fully connected layer matlab in matlab

To create a fully connected layer in MATLAB, you can use the fullyConnectedLayer function from the Deep Learning Toolbox. Here is an example of how to create a fully connected layer in MATLAB:

main.m
numClasses = 10;
hiddenSize = 100;

layers = [
    imageInputLayer([28 28 1])
    convolution2dLayer(5,20)
    reluLayer
    maxPooling2dLayer(2,'Stride',2)
    fullyConnectedLayer(hiddenSize)
    reluLayer
    fullyConnectedLayer(numClasses)
    softmaxLayer
    classificationLayer];

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In this example, we are creating a neural network with an input layer of size 28-by-28-by-1 for grayscale input images. The first layer is a 2D convolutional layer with 20 filters of size 5-by-5. This layer is followed by a rectified linear unit (ReLU) layer and a max pooling layer.

The next layer is a fully connected layer with hiddenSize neurons, followed by another ReLU layer. Finally, we add another fully connected layer with numClasses neurons, a softmax layer, and a classification layer.

You can customize the size of the fully connected layer and the number of neurons in the layer to fit your specific machine learning problem.