Solving Inverse Source Problems for linear PDEs using Sparse Sensor Measurements

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Title: Solving Inverse Source Problems for linear PDEs using Sparse Sensor Measurements
Authors: Murray-Bruce, J
Dragotti, PL
Item 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.
Editors: Matthews, MB
Issue Date: 6-Mar-2017
Date of Acceptance: 6-Nov-2016
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/Funder: Commission of the European Communities
Funder's Grant Number: 277800
Conference Name: 50th Asilomar Conference on Signals, Systems, and Computers (ASILOMARSSC)
Keywords: Science & Technology
Computer Science, Information Systems
Engineering, Electrical & Electronic
Computer Science
Publication Status: Published
Start Date: 2016-11-06
Finish Date: 2016-11-09
Conference Place: Pacific Grove, CA
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering

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