The autoencoder used in this work consists of several fully connected layers: an input layer, multiple hidden layers, a bottleneck layer with a single neuron, additional hidden layers, and an output layer. In each fully connected layer, the activation of a neuron is computed as a weighted sum of the activations from all neurons in the previous layer. This operation can be expressed as matrix multiplication, as shown in Equation ( ):