Abstract
The present project aims to explore the theoretical foundations of artificial neural networks, using a rigorous pure mathematics approach to explain and formalize the fundamental theorems that support their success in modern applications. We propose a detailed analysis of important mathematical results, such as the Universal Approximation Theorem, examining its conditions, limitations, a…