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http://hdl.handle.net/1893/34442| Appears in Collections: | Computing Science and Mathematics Journal Articles |
| Peer Review Status: | Refereed |
| Title: | Validated analysis of modulated signals: From de Prony to Padé and beyond |
| Author(s): | Cuyt, Annie Hou, Yuan Lee, Wen-shin |
| Contact Email: | wen-shin.lee@stir.ac.uk |
| Keywords: | Exponential analysis Modulation Validation Prony polynomial Padé approximant Froissart doublet |
| Issue Date: | 15-Oct-2022 |
| Date Deposited: | 22-Jun-2022 |
| Citation: | Cuyt A, Hou Y & Lee W (2022) Validated analysis of modulated signals: From de Prony to Padé and beyond. Journal of Computational and Applied Mathematics, 413, Art. No.: 114346. https://doi.org/10.1016/j.cam.2022.114346 |
| Abstract: | The spectral analysis of modulated signals has attracted quite some research, mainly because of the fact that Fourier methods are not particularly suitable. Among the challenges, we mention the separation of close components that differ significantly in magnitude, the limitation of the sampling duration, the probable ill-conditioning of certain structured matrices. We show how a validated exponential analysis add-on, for use with any standard exponential analysis method, offers a lot of advantages in the context of these challenges. The add-on uses an alias-free decimation technique and essentially combines the basics of de Prony’s method for exponential fitting with the theory of Padé approximation theory. |
| DOI Link: | 10.1016/j.cam.2022.114346 |
| Rights: | This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Accepted refereed manuscript of: Cuyt A, Hou Y & Lee W (2022) Validated analysis of modulated signals: From de Prony to Padé and beyond. Journal of Computational and Applied Mathematics, 413, Art. No.: 114346. https://doi.org/10.1016/j.cam.2022.114346 © 2022, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| Licence URL(s): | http://creativecommons.org/licenses/by-nc-nd/4.0/ |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| CAM_114326.pdf | Fulltext - Accepted Version | 510.23 kB | Adobe PDF | View/Open |
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