define cnn decoder layers in matlab

main.m
        1. Transposed convolutional layer - this upsamples the input feature maps.
        ```
        transposedConvLayer(numFilters, filterSize, 'Name', name)
        ```
        where numFilters is the number of filters, filterSize is the size of the filter, and name is the name of the layer.

        2. ReLU - this applies rectified linear units to the feature maps.
        ```
        reluLayer('Name', name)
        ```
        where name is the name of the layer.

        3. Batch normalization - this normalizes the output of the previous layer.
        ```
        batchNormalizationLayer('Name', name)
        ```
        where name is the name of the layer.

        4. Concatenation - this concatenates the output of the decoder layer with the output of the corresponding encoder layer.
        ```
        concatenationLayer(1, 'Name', name)
        ```
        where name is the name of the layer.

        The decoder layers can be defined using these layers in the required order to form a CNN decoder network.
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