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A trend extraction method based on logistic functions and envelopes
A method of step characteristic trend extraction based on logistic functions and envelopes (LFEs) is proposed in this paper. Compared with the existing trend extraction methods, the LFE method can determine the starting position of the step trend using a logistic function and extract the local trend...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8752829/ https://www.ncbi.nlm.nih.gov/pubmed/35017612 http://dx.doi.org/10.1038/s41598-021-04596-8 |
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author | Zhang, Jingjing Luo, Jinglin Zhang, Xuan |
author_facet | Zhang, Jingjing Luo, Jinglin Zhang, Xuan |
author_sort | Zhang, Jingjing |
collection | PubMed |
description | A method of step characteristic trend extraction based on logistic functions and envelopes (LFEs) is proposed in this paper. Compared with the existing trend extraction methods, the LFE method can determine the starting position of the step trend using a logistic function and extract the local trend using upper and lower envelopes. This method enhances the extraction accuracy and reduces the computation time. To verify the effectiveness of the LFE method, a simulated signal with a step trend feature was compared with the five-spot triple smoothing method, wavelet transform method and empirical mode decomposition-based method. All of these methods were applied to a real shock signal. The results demonstrate that the LFE method can reliably and accurately extract the trends with step characteristics based on less prior knowledge. Moreover, the proposed technique is suitable for industrial online applications. |
format | Online Article Text |
id | pubmed-8752829 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-87528292022-01-13 A trend extraction method based on logistic functions and envelopes Zhang, Jingjing Luo, Jinglin Zhang, Xuan Sci Rep Article A method of step characteristic trend extraction based on logistic functions and envelopes (LFEs) is proposed in this paper. Compared with the existing trend extraction methods, the LFE method can determine the starting position of the step trend using a logistic function and extract the local trend using upper and lower envelopes. This method enhances the extraction accuracy and reduces the computation time. To verify the effectiveness of the LFE method, a simulated signal with a step trend feature was compared with the five-spot triple smoothing method, wavelet transform method and empirical mode decomposition-based method. All of these methods were applied to a real shock signal. The results demonstrate that the LFE method can reliably and accurately extract the trends with step characteristics based on less prior knowledge. Moreover, the proposed technique is suitable for industrial online applications. Nature Publishing Group UK 2022-01-11 /pmc/articles/PMC8752829/ /pubmed/35017612 http://dx.doi.org/10.1038/s41598-021-04596-8 Text en © The Author(s) 2022 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 Zhang, Jingjing Luo, Jinglin Zhang, Xuan A trend extraction method based on logistic functions and envelopes |
title | A trend extraction method based on logistic functions and envelopes |
title_full | A trend extraction method based on logistic functions and envelopes |
title_fullStr | A trend extraction method based on logistic functions and envelopes |
title_full_unstemmed | A trend extraction method based on logistic functions and envelopes |
title_short | A trend extraction method based on logistic functions and envelopes |
title_sort | trend extraction method based on logistic functions and envelopes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8752829/ https://www.ncbi.nlm.nih.gov/pubmed/35017612 http://dx.doi.org/10.1038/s41598-021-04596-8 |
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