Publication
Title
VEXPA : Validated EXPonential Analysis through regular sub-sampling
Author
Abstract
In signal processing data are traditionally sampled according to the Shannon-Nyquist theorem in order to prevent aliasing effects. Here we focus on parametric methods and introduce a procedure that allows these methods to work with sub-sampled data. We actually make use of the aliasing effect to regularize the problem statement rather than that we avoid it. The new approach adds a number of features to a standard exponential analysis, among which output validation, the automatic detection of the exponential model order, robustness against outliers, and the possibility to parallelize the analysis. In Section 2 the standard exponential analysis is described, including a sensitivity analysis. In Section 3 the ingredients for the new technique are elaborated, 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 in Section 5 illustrate 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 the comparison to the CRLB of the underlying method, for which we here choose ESPRIT.
Language
English
Source (journal)
Arxiv
Publication
2018
Volume/pages
17 p.
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Source file
Record
Identification
Creation 15.11.2018
Last edited 15.07.2021
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