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Subdiffusive Source Sensing by a Regional Detection Method
Motivated by the fact that the danger may increase if the source of pollution problem remains unknown, in this paper, we study the source sensing problem for subdiffusion processes governed by time fractional diffusion systems based on a limited number of sensor measurements. For this, we first give...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6721240/ https://www.ncbi.nlm.nih.gov/pubmed/31405156 http://dx.doi.org/10.3390/s19163504 |
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author | Song, Weijing Ge, Fudong Chen, YangQuan |
author_facet | Song, Weijing Ge, Fudong Chen, YangQuan |
author_sort | Song, Weijing |
collection | PubMed |
description | Motivated by the fact that the danger may increase if the source of pollution problem remains unknown, in this paper, we study the source sensing problem for subdiffusion processes governed by time fractional diffusion systems based on a limited number of sensor measurements. For this, we first give some preliminary notions such as source, detection and regional spy sensors, etc. Secondly, we investigate the characterizations of regional strategic sensors and regional spy sensors. A regional detection approach on how to solve the source sensing problem of the considered system is then presented by using the Hilbert uniqueness method (HUM). This is to identify the unknown source only in a subregion of the whole domain, which is easier to be implemented and could save a lot of energy resources. Numerical examples are finally included to test our results. |
format | Online Article Text |
id | pubmed-6721240 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-67212402019-09-10 Subdiffusive Source Sensing by a Regional Detection Method Song, Weijing Ge, Fudong Chen, YangQuan Sensors (Basel) Article Motivated by the fact that the danger may increase if the source of pollution problem remains unknown, in this paper, we study the source sensing problem for subdiffusion processes governed by time fractional diffusion systems based on a limited number of sensor measurements. For this, we first give some preliminary notions such as source, detection and regional spy sensors, etc. Secondly, we investigate the characterizations of regional strategic sensors and regional spy sensors. A regional detection approach on how to solve the source sensing problem of the considered system is then presented by using the Hilbert uniqueness method (HUM). This is to identify the unknown source only in a subregion of the whole domain, which is easier to be implemented and could save a lot of energy resources. Numerical examples are finally included to test our results. MDPI 2019-08-10 /pmc/articles/PMC6721240/ /pubmed/31405156 http://dx.doi.org/10.3390/s19163504 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Song, Weijing Ge, Fudong Chen, YangQuan Subdiffusive Source Sensing by a Regional Detection Method |
title | Subdiffusive Source Sensing by a Regional Detection Method |
title_full | Subdiffusive Source Sensing by a Regional Detection Method |
title_fullStr | Subdiffusive Source Sensing by a Regional Detection Method |
title_full_unstemmed | Subdiffusive Source Sensing by a Regional Detection Method |
title_short | Subdiffusive Source Sensing by a Regional Detection Method |
title_sort | subdiffusive source sensing by a regional detection method |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6721240/ https://www.ncbi.nlm.nih.gov/pubmed/31405156 http://dx.doi.org/10.3390/s19163504 |
work_keys_str_mv | AT songweijing subdiffusivesourcesensingbyaregionaldetectionmethod AT gefudong subdiffusivesourcesensingbyaregionaldetectionmethod AT chenyangquan subdiffusivesourcesensingbyaregionaldetectionmethod |