Universal Approximation Theorem for Vector- and Hypercomplex-Valued Neural Networks

Marcos Eduardo Valle, Wington L. Vital, Guilherme Vieira

The universal approximation theorem states that a neural network with one hidden layer can approximate continuous functions on compact sets with any desired precision. This theorem…