Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/31526
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: VEXPA: Validated EXPonential Analysis through regular sub-sampling
Author(s): Briani, Matteo
Cuyt, Annie
Knaepkens, Ferre
Lee, Wen-shin
Contact Email: wen-shin.lee@stir.ac.uk
Keywords: Exponential analysis
sub-Nyquist sampling
uniform sampling
noise handling
Padé-Laplace
Froissart doublets
Issue Date: Dec-2020
Citation: Briani M, Cuyt A, Knaepkens F & Lee W (2020) VEXPA: Validated EXPonential Analysis through regular sub-sampling. Signal Processing, 177, Art. No.: 107722. https://doi.org/10.1016/j.sigpro.2020.107722
Abstract: We present a procedure that adds a number of desirable features to standard exponential analysis algorithms , among which output reliability, a divide-and-conquer approach, the automatic detection of the exponential model order, robustness against some outliers, and the possibility to parallelize the analysis. The key enabler for these features is the introduction of uniform sub-Nyquist sampling through decima-tion of the dense signal data. We actually make use of possible aliasing effects to recondition the problem statement rather than that we avoid aliasing. In Section 2 the standard exponential analysis is described, including a sensitivity analysis. In Section 3 the ingredients for the new approach are collected, of which good use is made in Section 4 where we essentially bring everything together in what we call VEXPA. Some numerical examples of the new procedure illustrate in Section 5 that the additional features are indeed realized and that VEXPA is a valuable add-on to any stand-alone exponential analysis. While returning a lot of additional output, it maintains a favourable comparison to the CRLB of the underlying method, for which we here choose a matrix pencil method. Moreover, the output reliability of VEXPA is similar to that of atomic norm minimization, whereas its computational complexity is far less.
DOI Link: 10.1016/j.sigpro.2020.107722
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: Briani M, Cuyt A, Knaepkens F & Lee W (2020) VEXPA: Validated EXPonential Analysis through regular sub-sampling. Signal Processing, 177, Art. No.: 107722. https://doi.org/10.1016/j.sigpro.2020.107722 © 2020, 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/

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