Inverse source identification for Poisson equation

Leevan LING; Y. C. Hon; M. Yamamoto

doi:10.1080/17415970500126500

Inverse source identification for Poisson equation

Leevan LING^*, Y. C. Hon, M. Yamamoto

^*Corresponding author for this work

Department of Mathematics

Research output: Contribution to journal › Article › peer-review

38 Citations (Scopus)

Abstract

A numerical method for identifying the unknown point sources for a two-dimensional Poisson problem from Dirichlet boundary data is proposed. Under an assumption that the total number and estimate positions of the point sources are known, the exact positions and corresponding strengths of the distinct point sources can be identified from scattered (noisy) observed Dirichlet boundary data. Numerical verification indicated that the method is efficient and robust.

Original language	English
Pages (from-to)	433-447
Number of pages	15
Journal	Inverse Problems in Science and Engineering
Volume	13
Issue number	4
DOIs	https://doi.org/10.1080/17415970500126500
Publication status	Published - Aug 2005

Scopus Subject Areas

Engineering(all)
Computer Science Applications
Applied Mathematics

User-Defined Keywords

Inverse problem
Point mass model
Poisson equation
Sources identification

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10.1080/17415970500126500

Cite this

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title = "Inverse source identification for Poisson equation",

abstract = "A numerical method for identifying the unknown point sources for a two-dimensional Poisson problem from Dirichlet boundary data is proposed. Under an assumption that the total number and estimate positions of the point sources are known, the exact positions and corresponding strengths of the distinct point sources can be identified from scattered (noisy) observed Dirichlet boundary data. Numerical verification indicated that the method is efficient and robust.",

keywords = "Inverse problem, Point mass model, Poisson equation, Sources identification",

author = "Leevan LING and Hon, {Y. C.} and M. Yamamoto",

note = "Funding Information: The first author was supported partially by a Postdoctoral Fellowship from the Japan Society for the Promotion of Science. The work of the second author mentioned in this article was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. CityU 1185/03E). The third author was supported partially by Grant 15340027 from the Japan Society for the Promotion of Science and Grant 15340015 from the Ministry of Education, Cultures, Sports and Technology.",

year = "2005",

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doi = "10.1080/17415970500126500",

language = "English",

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T1 - Inverse source identification for Poisson equation

AU - LING, Leevan

AU - Hon, Y. C.

AU - Yamamoto, M.

N1 - Funding Information: The first author was supported partially by a Postdoctoral Fellowship from the Japan Society for the Promotion of Science. The work of the second author mentioned in this article was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. CityU 1185/03E). The third author was supported partially by Grant 15340027 from the Japan Society for the Promotion of Science and Grant 15340015 from the Ministry of Education, Cultures, Sports and Technology.

PY - 2005/8

Y1 - 2005/8

N2 - A numerical method for identifying the unknown point sources for a two-dimensional Poisson problem from Dirichlet boundary data is proposed. Under an assumption that the total number and estimate positions of the point sources are known, the exact positions and corresponding strengths of the distinct point sources can be identified from scattered (noisy) observed Dirichlet boundary data. Numerical verification indicated that the method is efficient and robust.

AB - A numerical method for identifying the unknown point sources for a two-dimensional Poisson problem from Dirichlet boundary data is proposed. Under an assumption that the total number and estimate positions of the point sources are known, the exact positions and corresponding strengths of the distinct point sources can be identified from scattered (noisy) observed Dirichlet boundary data. Numerical verification indicated that the method is efficient and robust.

KW - Inverse problem

KW - Point mass model

KW - Poisson equation

KW - Sources identification

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DO - 10.1080/17415970500126500

M3 - Article

AN - SCOPUS:20744443008

SN - 1741-5977

VL - 13

SP - 433

EP - 447

JO - Inverse Problems in Science and Engineering

JF - Inverse Problems in Science and Engineering

IS - 4

ER -

Inverse source identification for Poisson equation

Abstract

Scopus Subject Areas

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