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Numerical integration of bivariate fractal interpolation functions on rectangular domains
This paper primarily focuses on the derivation of fractal numerical integration for the data sets corresponding to two variable signals defined over a rectangular region. Evaluating numerical integration results through the fractal method helps achieve accurate results with minimum computation effor...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240492/ https://www.ncbi.nlm.nih.gov/pubmed/37359183 http://dx.doi.org/10.1140/epjs/s11734-023-00864-y |
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author | Aparna, M. P. Paramanathan, P. |
author_facet | Aparna, M. P. Paramanathan, P. |
author_sort | Aparna, M. P. |
collection | PubMed |
description | This paper primarily focuses on the derivation of fractal numerical integration for the data sets corresponding to two variable signals defined over a rectangular region. Evaluating numerical integration results through the fractal method helps achieve accurate results with minimum computation effort. The formulation of the fractal numerical integration is achieved by considering the recursive relation satisfied by the bivariate fractal interpolation functions for the given data set. The points in the data set have been used to evaluate the coefficients of the iterated function systems. The derivation of these coefficients considering the index of the subrectangles, and the integration formula has been proposed using these coefficients. The bivariate fractal interpolation functions constructed using these coefficients are then correlated with the bilinear interpolation functions. Also, this paper derives a formula for the freely chosen vertical scaling factor that has been used in reducing the approximation error. The obtained formula of the vertical scaling factor is then used in establishing the convergence of the proposed method of integration to the traditional double integration technique through a collection of lemmas and theorems. Finally, the paper concludes with an illustration of the proposed method of integration and the analysis of the numerical integral results obtained for the data sets corresponding to four benchmark functions. |
format | Online Article Text |
id | pubmed-10240492 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-102404922023-06-06 Numerical integration of bivariate fractal interpolation functions on rectangular domains Aparna, M. P. Paramanathan, P. Eur Phys J Spec Top Regular Article This paper primarily focuses on the derivation of fractal numerical integration for the data sets corresponding to two variable signals defined over a rectangular region. Evaluating numerical integration results through the fractal method helps achieve accurate results with minimum computation effort. The formulation of the fractal numerical integration is achieved by considering the recursive relation satisfied by the bivariate fractal interpolation functions for the given data set. The points in the data set have been used to evaluate the coefficients of the iterated function systems. The derivation of these coefficients considering the index of the subrectangles, and the integration formula has been proposed using these coefficients. The bivariate fractal interpolation functions constructed using these coefficients are then correlated with the bilinear interpolation functions. Also, this paper derives a formula for the freely chosen vertical scaling factor that has been used in reducing the approximation error. The obtained formula of the vertical scaling factor is then used in establishing the convergence of the proposed method of integration to the traditional double integration technique through a collection of lemmas and theorems. Finally, the paper concludes with an illustration of the proposed method of integration and the analysis of the numerical integral results obtained for the data sets corresponding to four benchmark functions. Springer Berlin Heidelberg 2023-06-05 /pmc/articles/PMC10240492/ /pubmed/37359183 http://dx.doi.org/10.1140/epjs/s11734-023-00864-y Text en © The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Regular Article Aparna, M. P. Paramanathan, P. Numerical integration of bivariate fractal interpolation functions on rectangular domains |
title | Numerical integration of bivariate fractal interpolation functions on rectangular domains |
title_full | Numerical integration of bivariate fractal interpolation functions on rectangular domains |
title_fullStr | Numerical integration of bivariate fractal interpolation functions on rectangular domains |
title_full_unstemmed | Numerical integration of bivariate fractal interpolation functions on rectangular domains |
title_short | Numerical integration of bivariate fractal interpolation functions on rectangular domains |
title_sort | numerical integration of bivariate fractal interpolation functions on rectangular domains |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240492/ https://www.ncbi.nlm.nih.gov/pubmed/37359183 http://dx.doi.org/10.1140/epjs/s11734-023-00864-y |
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