in a CNN like in the example "Create Simple Deep Learning Network for Classification"
there are hidden layer built by the function convolution2dLayer. If in the first convolution layer the filter depth is for example 8, then we have 8 feature maps in the first layer. So I wounder how the perceptrons in the second layer are connected to the the perceptron of the first layer if the second layer has equal number of features (here in the example 8), more or less features? Could I adjust the connection within the parameter of the function convolution2dLayer?