Analysis of the backpropagation algorithm using linear algebra

Multilayer perceptrons (MLPs) are feed-forward artificial neural networks with high theoretical basis. The most popular algorithm to train MLPs is the backpropagation algorithm, which can be seen as a consistent nonparametric least squares regression estimator. This algorithm is reformulated in this paper using linear algebra, providing theoretical basis for further studies.