Symmetrized Neural Network Operators in Fractional Calculus: Caputo Derivatives, Asymptotic Analysis, and the Voronovskaya–Santos–Sales Theorem

Symmetrized Neural Network Operators in Fractional Calculus: Caputo Derivatives, Asymptotic Analysis, and the Voronovskaya–Santos–Sales Theorem

This work presents a comprehensive mathematical framework for symmetrized neural network operators operating under the paradigm of fractional calculus. By introducing a perturbed hyperbolic tangent activation, we construct a family of localized, symmetric, and positive kernel-like densities, which f...

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Bibliographic Details
Main Authors: Rômulo Damasclin Chaves dos Santos, Jorge Henrique de Oliveira Sales, Gislan Silveira Santos
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Axioms
Subjects:
neural network operators
fractional differentiation
asymptotic analysis
Caputo derivatives
Voronovskaya-type expansions
Online Access:https://www.mdpi.com/2075-1680/14/7/510
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