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Two optimized novel potential formulas and numerical algorithms for [Formula: see text] cobweb and fan resistor networks
The research of resistive network will become the basis of many fields. At present, many exact potential formulas of some complex resistor networks have been obtained. Computer numerical simulation is the trend of computing, but written calculation will limit the time and scale. In this paper, the p...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10390589/ https://www.ncbi.nlm.nih.gov/pubmed/37524723 http://dx.doi.org/10.1038/s41598-023-39478-8 |
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author | Zhao, Wenjie Zheng, Yanpeng Jiang, Xiaoyu Jiang, Zhaolin |
author_facet | Zhao, Wenjie Zheng, Yanpeng Jiang, Xiaoyu Jiang, Zhaolin |
author_sort | Zhao, Wenjie |
collection | PubMed |
description | The research of resistive network will become the basis of many fields. At present, many exact potential formulas of some complex resistor networks have been obtained. Computer numerical simulation is the trend of computing, but written calculation will limit the time and scale. In this paper, the potential formulas of a [Formula: see text] scale cobweb resistor network and fan resistor network are optimized. Chebyshev polynomial of the second class and the absolute value function are used to express the novel potential formulas of the resistor network, and described in detail the derivation process of the explicit formula. Considering the influence of parameters on the potential formulas, several idiosyncratic potential formulas are proposed, and the corresponding three-dimensional dynamic images are drawn. Two numerical algorithms of the computing potential are presented by using the mathematical model and DST-VI. Finally, the efficiency of calculating potential by different methods are compared. The advantages of new potential formulas and numerical algorithms by the calculation efficiency of the three methods are shown. The optimized potential formulas and the presented numerical algorithms provide a powerful tool for the field of science and engineering. |
format | Online Article Text |
id | pubmed-10390589 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103905892023-08-02 Two optimized novel potential formulas and numerical algorithms for [Formula: see text] cobweb and fan resistor networks Zhao, Wenjie Zheng, Yanpeng Jiang, Xiaoyu Jiang, Zhaolin Sci Rep Article The research of resistive network will become the basis of many fields. At present, many exact potential formulas of some complex resistor networks have been obtained. Computer numerical simulation is the trend of computing, but written calculation will limit the time and scale. In this paper, the potential formulas of a [Formula: see text] scale cobweb resistor network and fan resistor network are optimized. Chebyshev polynomial of the second class and the absolute value function are used to express the novel potential formulas of the resistor network, and described in detail the derivation process of the explicit formula. Considering the influence of parameters on the potential formulas, several idiosyncratic potential formulas are proposed, and the corresponding three-dimensional dynamic images are drawn. Two numerical algorithms of the computing potential are presented by using the mathematical model and DST-VI. Finally, the efficiency of calculating potential by different methods are compared. The advantages of new potential formulas and numerical algorithms by the calculation efficiency of the three methods are shown. The optimized potential formulas and the presented numerical algorithms provide a powerful tool for the field of science and engineering. Nature Publishing Group UK 2023-07-31 /pmc/articles/PMC10390589/ /pubmed/37524723 http://dx.doi.org/10.1038/s41598-023-39478-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Zhao, Wenjie Zheng, Yanpeng Jiang, Xiaoyu Jiang, Zhaolin Two optimized novel potential formulas and numerical algorithms for [Formula: see text] cobweb and fan resistor networks |
title | Two optimized novel potential formulas and numerical algorithms for [Formula: see text] cobweb and fan resistor networks |
title_full | Two optimized novel potential formulas and numerical algorithms for [Formula: see text] cobweb and fan resistor networks |
title_fullStr | Two optimized novel potential formulas and numerical algorithms for [Formula: see text] cobweb and fan resistor networks |
title_full_unstemmed | Two optimized novel potential formulas and numerical algorithms for [Formula: see text] cobweb and fan resistor networks |
title_short | Two optimized novel potential formulas and numerical algorithms for [Formula: see text] cobweb and fan resistor networks |
title_sort | two optimized novel potential formulas and numerical algorithms for [formula: see text] cobweb and fan resistor networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10390589/ https://www.ncbi.nlm.nih.gov/pubmed/37524723 http://dx.doi.org/10.1038/s41598-023-39478-8 |
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