Spatiotemporal Sampling Trade-off for Inverse Diffusion Source Problems
File(s)SampTA2017_MBD.pdf (445.79 KB)
Accepted version
Author(s)
Murray-Bruce, John
Dragotti, Pier Luigi
Type
Conference Paper
Abstract
We consider the spatiotemporal sampling of diffusion fields induced by M point sources, and study the associated inverse problem of recovering the initial parameters of the unknown sources. In particular, we focus on characterising qualitatively the error of the obtained source estimates. To achieve this, we obtain an expression with which we can trade the sensor density for performance accuracy. In other words, by evaluating the optimal sampling instant for a given sensor density-and using the corresponding field samples at that instant-we can expect to obtain an improvement in the estimation performance when compared to an arbitrary sampling instant. Finally, several numerical simulations are presented, to support the theoretical results obtained.
Date Issued
2017-09-04
Date Acceptance
2017-07-03
Citation
2017 INTERNATIONAL CONFERENCE ON SAMPLING THEORY AND APPLICATIONS (SAMPTA), 2017, pp.55-59
Publisher
IEEE
Start Page
55
End Page
59
Journal / Book Title
2017 INTERNATIONAL CONFERENCE ON SAMPLING THEORY AND APPLICATIONS (SAMPTA)
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.
Source
12th International Conference on Sampling Theory and Applications (SAMPTA)
Subjects
Science & Technology
Technology
Computer Science, Theory & Methods
Engineering, Electrical & Electronic
Computer Science
Engineering
LOCALIZED SOURCES
FIELDS
Publication Status
Published
Start Date
2017-07-03
Finish Date
2017-07-07
Coverage Spatial
Tallinn, ESTONIA