Determining Joint Periodicities in Multi-Time Data with Sampling Uncertainties
Svedberg, David ; Elvander, Filip LU and Jakobsson, Andreas LU
(2022)
47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2022-May.
p.5737-5741
- Abstract
In this work, we introduce a novel approach for determining a joint sparse spectrum from several non-uniformly sampled data sets, where each data set is assumed to have its own, and only partially known, sampling times. The problem originates in paleoclimatology, where each data point derives from a separate ice core measurement, resulting in that even though all measurements reflect the same periodicities, the sampling times and phases differ among the data sets, with the sampling times being only approximately known. The proposed estimator exploits all available data using a sparse reconstruction framework allowing for a reliable and robust estimation of the underlying periodicities. The performance of the method is illustrated using... (More)
In this work, we introduce a novel approach for determining a joint sparse spectrum from several non-uniformly sampled data sets, where each data set is assumed to have its own, and only partially known, sampling times. The problem originates in paleoclimatology, where each data point derives from a separate ice core measurement, resulting in that even though all measurements reflect the same periodicities, the sampling times and phases differ among the data sets, with the sampling times being only approximately known. The proposed estimator exploits all available data using a sparse reconstruction framework allowing for a reliable and robust estimation of the underlying periodicities. The performance of the method is illustrated using both simulated and measured ice core data sets.
(Less)
- author
- Svedberg, David
; Elvander, Filip
LU
and Jakobsson, Andreas
LU
- organization
- publishing date
- 2022
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Irregular Sampling, Misspecified Modelling, Multi-time, Paleoclimatology
- host publication
- 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
- series title
- ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
- volume
- 2022-May
- pages
- 5 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
- conference location
- Virtual, Online, Singapore
- conference dates
- 2022-05-23 - 2022-05-27
- external identifiers
-
- scopus:85131240640
- ISSN
- 1520-6149
- ISBN
- 9781665405409
- DOI
- 10.1109/ICASSP43922.2022.9747184
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2022 IEEE
- id
- e0afadc6-50b7-4fd1-a880-964fdcda8b79
- date added to LUP
- 2022-12-29 13:58:36
- date last changed
- 2023-11-21 15:00:34
@inproceedings{e0afadc6-50b7-4fd1-a880-964fdcda8b79,
abstract = {{<p>In this work, we introduce a novel approach for determining a joint sparse spectrum from several non-uniformly sampled data sets, where each data set is assumed to have its own, and only partially known, sampling times. The problem originates in paleoclimatology, where each data point derives from a separate ice core measurement, resulting in that even though all measurements reflect the same periodicities, the sampling times and phases differ among the data sets, with the sampling times being only approximately known. The proposed estimator exploits all available data using a sparse reconstruction framework allowing for a reliable and robust estimation of the underlying periodicities. The performance of the method is illustrated using both simulated and measured ice core data sets.</p>}},
author = {{Svedberg, David and Elvander, Filip and Jakobsson, Andreas}},
booktitle = {{2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings}},
isbn = {{9781665405409}},
issn = {{1520-6149}},
keywords = {{Irregular Sampling; Misspecified Modelling; Multi-time; Paleoclimatology}},
language = {{eng}},
pages = {{5737--5741}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings}},
title = {{Determining Joint Periodicities in Multi-Time Data with Sampling Uncertainties}},
url = {{http://dx.doi.org/10.1109/ICASSP43922.2022.9747184}},
doi = {{10.1109/ICASSP43922.2022.9747184}},
volume = {{2022-May}},
year = {{2022}},
}