Designing optimal sampling schemes for multi-dimensional data
(2017) 51st Asilomar Conferenec on Signals, Systems, and Computers (ASILOMAR 2017) p.850-852- Abstract
- In this work, we propose a method for determining an optimal, non-uniform, sampling scheme for multi-dimensional signals by solving a convex optimization problem reminiscent of the sensor selection problem. The optimal sampling scheme is determined given a suitable estimation bound on the parameters of interest, as well as incorporating any imprecise a priori knowledge of the locations of the parameters. Numerical examples illustrate the efficiency of the proposed scheme.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/b3160c2b-a0e8-464d-8efb-a115de5b65cb
- author
- Swärd, Johan
LU
; Elvander, Filip
LU
and Jakobsson, Andreas
LU
- organization
- publishing date
- 2017
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2017 51st Asilomar Conference on Signals, Systems, and Computers
- pages
- 3 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 51st Asilomar Conferenec on Signals, Systems, and Computers (ASILOMAR 2017)
- conference location
- Pacific Grove, United States
- conference dates
- 2017-10-29 - 2017-11-01
- external identifiers
-
- scopus:85050969825
- ISBN
- 978-1-5386-1823-3
- DOI
- 10.1109/ACSSC.2017.8335468
- language
- English
- LU publication?
- yes
- id
- b3160c2b-a0e8-464d-8efb-a115de5b65cb
- date added to LUP
- 2018-04-25 11:24:47
- date last changed
- 2022-01-31 03:07:29
@inproceedings{b3160c2b-a0e8-464d-8efb-a115de5b65cb, abstract = {{In this work, we propose a method for determining an optimal, non-uniform, sampling scheme for multi-dimensional signals by solving a convex optimization problem reminiscent of the sensor selection problem. The optimal sampling scheme is determined given a suitable estimation bound on the parameters of interest, as well as incorporating any imprecise a priori knowledge of the locations of the parameters. Numerical examples illustrate the efficiency of the proposed scheme.}}, author = {{Swärd, Johan and Elvander, Filip and Jakobsson, Andreas}}, booktitle = {{2017 51st Asilomar Conference on Signals, Systems, and Computers}}, isbn = {{978-1-5386-1823-3}}, language = {{eng}}, pages = {{850--852}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Designing optimal sampling schemes for multi-dimensional data}}, url = {{http://dx.doi.org/10.1109/ACSSC.2017.8335468}}, doi = {{10.1109/ACSSC.2017.8335468}}, year = {{2017}}, }