Mismatched Estimation of Polynomially Damped Signals
(2019) 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 In 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings p.246-250- Abstract
In this work, we consider the problem of estimating the parameters of polynomially damped sinusoidal signals, commonly encountered in, for instance, spectroscopy. Generally, finding the parameter values of such signals constitutes a high-dimensional problem, often further complicated by not knowing the number of signal components or their specific signal structures. In order to alleviate the computational burden, we herein propose a mismatched estimation procedure using simplified, approximate signal models. Despite the approximation, we show that such a procedure is expected to yield predictable results, allowing for statistically and computationally efficient estimates of the signal parameters.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/c2a90100-146f-40da-bfc2-7ce6d2875534
- author
- Elvander, Filip LU ; Sward, Johan LU and Jakobsson, Andreas LU
- organization
- publishing date
- 2019
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- computational efficiency, Lorentzian and Voigt line shapes, Mismatched estimation, NMR spectroscopy
- host publication
- 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings
- series title
- 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings
- article number
- 9022668
- pages
- 5 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019
- conference location
- Le Gosier, Guadeloupe
- conference dates
- 2019-12-15 - 2019-12-18
- external identifiers
-
- scopus:85082381726
- ISBN
- 9781728155494
- DOI
- 10.1109/CAMSAP45676.2019.9022668
- language
- English
- LU publication?
- yes
- id
- c2a90100-146f-40da-bfc2-7ce6d2875534
- date added to LUP
- 2020-04-14 13:12:15
- date last changed
- 2022-04-18 21:45:44
@inproceedings{c2a90100-146f-40da-bfc2-7ce6d2875534, abstract = {{<p>In this work, we consider the problem of estimating the parameters of polynomially damped sinusoidal signals, commonly encountered in, for instance, spectroscopy. Generally, finding the parameter values of such signals constitutes a high-dimensional problem, often further complicated by not knowing the number of signal components or their specific signal structures. In order to alleviate the computational burden, we herein propose a mismatched estimation procedure using simplified, approximate signal models. Despite the approximation, we show that such a procedure is expected to yield predictable results, allowing for statistically and computationally efficient estimates of the signal parameters.</p>}}, author = {{Elvander, Filip and Sward, Johan and Jakobsson, Andreas}}, booktitle = {{2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings}}, isbn = {{9781728155494}}, keywords = {{computational efficiency; Lorentzian and Voigt line shapes; Mismatched estimation; NMR spectroscopy}}, language = {{eng}}, pages = {{246--250}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings}}, title = {{Mismatched Estimation of Polynomially Damped Signals}}, url = {{http://dx.doi.org/10.1109/CAMSAP45676.2019.9022668}}, doi = {{10.1109/CAMSAP45676.2019.9022668}}, year = {{2019}}, }