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authorericmarin <maarin.eric@gmail.com>2026-06-23 15:26:01 +0200
committerericmarin <maarin.eric@gmail.com>2026-06-26 16:47:32 +0200
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using official template + fixing language errorsthesis
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A neural network is a computational model inspired by biological neural networks. It consists of
connected nodes called neurons, introduced in its early form by Rosenblatt~\cite{rosenblatt1958perceptron}.
-The \textit{Multi-Layer Perceptrons} is an architecture composed of sequential layers, trained using
+The \textit{Multi-Layer Perceptron} is an architecture composed of sequential layers, trained using
backpropagation as popularized by Rumelhart et al.~\cite{rumelhart1986learning}.
\subsection{Neuron}
@@ -57,7 +57,7 @@ The output $y$ is defined as:
\subsection{Multi-Layer Perceptron}
A \textit{Multi-Layer Perceptron} (MLP), illustrated in \textbf{\Cref{fig:mlp}}, is a type of neural network organized
-in fully connected layers of neurons: an input layer, one or more hidden layers and an output layer.
+in fully connected layers of neurons: an input layer, one or more hidden layers, and an output layer.
An MLP is \textit{feedforward}, meaning that the flow of information is strictly propagated from the input to
the outputs.
\begin{figure}[H]