Voronovskaya Type Asymptotic Expansions for Smooth Symmetrized and Perturbed Hyperbolic Tangent Ordinary and Fractional Neural Network Approximations over Infinite Domains

In this article we research the univariate smooth approximation ordinary and fractional under differentiation of functions.The approximators here are neural network operators activated by the symmetrized and perturbed hyperbolic tangent function.All domains here are of the whole real line.The neural network operators here are of quasi-interpolation type: the basic ones, the Kantorovich type ones, and of the quadrature type.We give Voronovskaya type asymptotic expansions.

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Publication Details

Journal
Neural Parallel and Scientific Computations
Published
2025-01-09
DOI
https://doi.org/10.46719/npsc2025.33.01
Citations
3
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
7.44
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article

Voronovskaya Type Asymptotic Expansions for Smooth Symmetrized and Perturbed Hyperbolic Tangent Ordinary and Fractional Neural Network Approximations over Infinite Domains

George A. Anastassiou
3 citations
Neural Parallel and Scientific Computations
Neural Networks and Applications
7.44
article

Voronovskaya Type Asymptotic Expansions for Smooth Symmetrized and Perturbed Hyperbolic Tangent Ordinary and Fractional Neural Network Approximations over Infinite Domains

George A. Anastassiou
article en
3 citations

Abstract

In this article we research the univariate smooth approximation ordinary and fractional under differentiation of functions.The approximators here are neural network operators activated by the symmetrized and perturbed hyperbolic tangent function.All domains here are of the whole real line.The neural network operators here are of quasi-interpolation type: the basic ones, the Kantorovich type ones, and of the quadrature type.We give Voronovskaya type asymptotic expansions.

Neural Parallel and Scientific ComputationsVol. 33(1)
University of Memphis (US)
Openalex Percentile: Top 4%
Neural Networks and Applications
7.44
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