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Research on Recurrence Plot Feature Quantization Method Based on Image Texture Analysis
The nonlinear time-series analysis method, based on the recurrence plot theory, has received great attention from researchers and has been successfully used in multiple fields. However, traditional recurrence plots that use Heaviside step functions to determine the recursive behavior of a point in t...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9377861/ https://www.ncbi.nlm.nih.gov/pubmed/35978591 http://dx.doi.org/10.1155/2022/2495024 |
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author | Li, Yan Li, Zhan |
author_facet | Li, Yan Li, Zhan |
author_sort | Li, Yan |
collection | PubMed |
description | The nonlinear time-series analysis method, based on the recurrence plot theory, has received great attention from researchers and has been successfully used in multiple fields. However, traditional recurrence plots that use Heaviside step functions to determine the recursive behavior of a point in the phase space have two problems: (1) Heaviside step functions produce a rigid boundary, resulting in information loss; and (2) the selection of the critical distance, ε, is crucial; if the selection is inappropriate, it will result in a low-dimensional dynamics error, and as of now, there exists no unified method for selecting this parameter. With regard to the problems described above, the novelty of this article lies in the following: (1) when determining the state-phase point recursiveness, a Gaussian function is used to replace the Heaviside function, thereby solving the rigidity and binary value problems of the recursive analysis results caused by the Heaviside step function; and (2) texture analysis is performed on a recurrence plot, new ways of studying complex system dynamics features are proposed, and a system of complex system dynamic-like measurement methods is built. |
format | Online Article Text |
id | pubmed-9377861 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-93778612022-08-16 Research on Recurrence Plot Feature Quantization Method Based on Image Texture Analysis Li, Yan Li, Zhan J Environ Public Health Research Article The nonlinear time-series analysis method, based on the recurrence plot theory, has received great attention from researchers and has been successfully used in multiple fields. However, traditional recurrence plots that use Heaviside step functions to determine the recursive behavior of a point in the phase space have two problems: (1) Heaviside step functions produce a rigid boundary, resulting in information loss; and (2) the selection of the critical distance, ε, is crucial; if the selection is inappropriate, it will result in a low-dimensional dynamics error, and as of now, there exists no unified method for selecting this parameter. With regard to the problems described above, the novelty of this article lies in the following: (1) when determining the state-phase point recursiveness, a Gaussian function is used to replace the Heaviside function, thereby solving the rigidity and binary value problems of the recursive analysis results caused by the Heaviside step function; and (2) texture analysis is performed on a recurrence plot, new ways of studying complex system dynamics features are proposed, and a system of complex system dynamic-like measurement methods is built. Hindawi 2022-08-08 /pmc/articles/PMC9377861/ /pubmed/35978591 http://dx.doi.org/10.1155/2022/2495024 Text en Copyright © 2022 Yan Li and Zhan Li. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Li, Yan Li, Zhan Research on Recurrence Plot Feature Quantization Method Based on Image Texture Analysis |
title | Research on Recurrence Plot Feature Quantization Method Based on Image Texture Analysis |
title_full | Research on Recurrence Plot Feature Quantization Method Based on Image Texture Analysis |
title_fullStr | Research on Recurrence Plot Feature Quantization Method Based on Image Texture Analysis |
title_full_unstemmed | Research on Recurrence Plot Feature Quantization Method Based on Image Texture Analysis |
title_short | Research on Recurrence Plot Feature Quantization Method Based on Image Texture Analysis |
title_sort | research on recurrence plot feature quantization method based on image texture analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9377861/ https://www.ncbi.nlm.nih.gov/pubmed/35978591 http://dx.doi.org/10.1155/2022/2495024 |
work_keys_str_mv | AT liyan researchonrecurrenceplotfeaturequantizationmethodbasedonimagetextureanalysis AT lizhan researchonrecurrenceplotfeaturequantizationmethodbasedonimagetextureanalysis |