Rômulo Damasclin Chaves dos Santos

Non-Linear Interactions in Neural Network Operators: New Theorems on Symmetry-Preserving Transformations

2025 · arXiv (Cornell University)

This paper advances the study of multivariate function approximation using neural network operators activated by symmetrized and perturbed hyperbolic tangent functions. We propose new non-linear operators that preserve dynamic symmetries within Euclidean spaces, extending current …