dc.contributor.author | Uyan, Hande | |
dc.contributor.author | Aslan, Abdullah Ozan | |
dc.contributor.author | Karateke, Seda | |
dc.contributor.author | Büyükyazıcı, İbrahim | |
dc.date.accessioned | 2024-12-02T06:07:38Z | |
dc.date.available | 2024-12-02T06:07:38Z | |
dc.date.issued | 2024 | en_US |
dc.identifier.citation | Uyan, H., Aslan, A. O., Karateke, S., & Büyükyazıcı, İ. (2024). Interpolation for neural-network operators activated with a generalized logistic-type function. Journal of Inequalities and Applications, 2024(1). https://doi.org/10.1186/s13660-024-03199-x | en_US |
dc.identifier.issn | 1029-242X | |
dc.identifier.uri | https://hdl.handle.net/20.500.12900/452 | |
dc.description.abstract | This paper defines a family of neural-network interpolation operators. The first derivative of generalized logistic-type functions is considered as a density function. Using the first-order uniform approximation theorem for continuous functions defined on the finite intervals, the interpolation properties of these operators are presented. A Kantorovich-type variant of the operators Fna,epsilon\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$F_{n}<^>{a,\varepsilon} $\end{document} is also introduced. The approximation of Kantorovich-type operators in LP\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$L_{P}$\end{document} spaces with 1 <= p <=infinity\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$1 \leq p\leq \infty $\end{document} is studied. Further, different combinations of the parameters of our generalized logistic-type activation function theta s,a\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\theta _{s, a}$\end{document} are examined to see which parameter values might give us a more efficient activation function. By choosing suitable parameters for the operator Fna,epsilon\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$F_{n}<^>{a,\varepsilon} $\end{document} and the Kantorovich variant of the operator Fna,epsilon\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$F_{n}<^>{a,\varepsilon} $\end{document}, the approximation of various function examples is studied. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | SPRINGER | en_US |
dc.relation.isversionof | 10.1186/s13660-024-03199-x | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Generalized logistic-type function | en_US |
dc.subject | Neural-Network (NN) operators | en_US |
dc.subject | Interpolation | en_US |
dc.subject | Uniform approximation | en_US |
dc.subject | Order of approximation | en_US |
dc.title | Interpolation for neural-network operators activated with a generalized logistic-type function | en_US |
dc.type | article | en_US |
dc.department | İstanbul Atlas Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Yazılım Mühendisliği Bölümü | en_US |
dc.contributor.institutionauthor | Karateke, Seda | |
dc.identifier.volume | 204 | en_US |
dc.relation.journal | JOURNAL OF INEQUALITIES AND APPLICATIONS | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |