Multilayer perceptrons (MLPs), or feedforward neural networks, are one of the most commonly used DL models. It aims to learn a nonlinear functional mapping 𝒚 = 𝑓 𝜃 (𝒙) which maps an input vector 𝒙 to an output representation 𝒚. Here 𝜃 represents the parameters of the neural network. A MLP with 𝐿 layers are displayed in Figure below, where the network consists of an input layer, an output layer, and 𝐿 -2 hidden layers.