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.
| Original language | English |
|---|---|
| Title of host publication | 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings |
| Publisher | IEEE - Institute of Electrical and Electronics Engineers Inc. |
| Pages | 246-250 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781728155494 |
| DOIs | |
| Publication status | Published - 2019 |
| Event | 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Le Gosier, Guadeloupe Duration: 2019 Dec 15 → 2019 Dec 18 |
Publication series
| Name | 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings |
|---|
Conference
| Conference | 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 |
|---|---|
| Country/Territory | Guadeloupe |
| City | Le Gosier |
| Period | 2019/12/15 → 2019/12/18 |
Subject classification (UKÄ)
- Mathematical Sciences
- Signal Processing
Free keywords
- computational efficiency
- Lorentzian and Voigt line shapes
- Mismatched estimation
- NMR spectroscopy
Fingerprint
Dive into the research topics of 'Mismatched Estimation of Polynomially Damped Signals'. Together they form a unique fingerprint.Research output
- 1 Doctoral Thesis (compilation)
-
Modeling and Sampling of Spectrally Structured Signals
Elvander, F., 2020, Centre for the Mathematical sciences, Lund University. 256 p.Research output: Thesis › Doctoral Thesis (compilation)
Open AccessFile
Projects
- 1 Active
-
Statistical Signal Processing Group
Anderson, R. (Researcher), Brynolfsson, J. (Researcher), Elvander, F. (Researcher), Reinhold, I. (Researcher), Svärd, J. (Researcher), Kronvall, T. (Researcher), Lei, S. (Researcher), Sandsten, M. (Researcher) & Jakobsson, A. (Researcher)
1990/01/01 → …
Project: Research
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