Mathematical model
$$
\begin{equation}
y = f\left(\sum_{i=1}^n w_ix_i + b_i\right) = f(u)
\tag{2}
\end{equation}
$$
In an FFNN of such neurons, the
inputs \( x_i \)
are the
outputs of the neurons in the preceding layer. Furthermore, a MLP is fully-connected,
which means that each neuron receives a weighted sum of the outputs of
all neurons in the previous layer.