Solving Inverse Source Problems for linear PDEs using Sparse Sensor Measurements
File(s)
Accepted version
Author(s)
Murray-Bruce, J
Dragotti, PL
Type
Conference Paper
Abstract
Many physical phenomena across several applications can be described by partial differential equations (PDEs). In these applications, sensors collect sparse samples of the resulting phenomena with the aim of detecting its cause/source, using some intelligent data analysis tools on the samples. These problems are commonly referred to as inverse source problems. This work presents a novel framework for solving such inverse source problem for linear PDEs by drawing from certain recent results in modern sampling theory. Under the new framework, we study the well-known diffusion PDE and present numerical results that highlight the validity and robustness of the approach.
Editor(s)
Matthews, MB
Date Issued
2017-03-06
Date Acceptance
2016-11-06
Citation
Signals, Systems and Computers, 2016 50th Asilomar Conference on, 2017, pp.517-521
ISSN
1058-6393
Publisher
IEEE
Start Page
517
End Page
521
Journal / Book Title
Signals, Systems and Computers, 2016 50th Asilomar Conference on
Copyright Statement
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Commission of the European Communities
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000406057400090&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
277800
Source
50th Asilomar Conference on Signals, Systems, and Computers (ASILOMARSSC)
Subjects
Science & Technology
Technology
Computer Science, Information Systems
Engineering, Electrical & Electronic
Telecommunications
Computer Science
Engineering
LOCALIZED SOURCES
DIFFUSION FIELDS
SHANNON
Publication Status
Published
Start Date
2016-11-06
Finish Date
2016-11-09
Coverage Spatial
Pacific Grove, CA