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Keywords = Lorentzian peaks matching pursuit

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14 pages, 2539 KiB  
Article
Modified OMP Algorithm for Exponentially Decaying Signals
by Krzysztof Kazimierczuk and Paweł Kasprzak
Sensors 2015, 15(1), 234-247; https://doi.org/10.3390/s150100234 - 24 Dec 2014
Cited by 10 | Viewed by 6361
Abstract
A group of signal reconstruction methods, referred to as compressed sensing (CS), has recently found a variety of applications in numerous branches of science and technology. However, the condition of the applicability of standard CS algorithms (e.g., orthogonal matching pursuit, OMP), i.e., the [...] Read more.
A group of signal reconstruction methods, referred to as compressed sensing (CS), has recently found a variety of applications in numerous branches of science and technology. However, the condition of the applicability of standard CS algorithms (e.g., orthogonal matching pursuit, OMP), i.e., the existence of the strictly sparse representation of a signal, is rarely met. Thus, dedicated algorithms for solving particular problems have to be developed. In this paper, we introduce a modification of OMP motivated by nuclear magnetic resonance (NMR) application of CS. The algorithm is based on the fact that the NMR spectrum consists of Lorentzian peaks and matches a single Lorentzian peak in each of its iterations. Thus, we propose the name Lorentzian peak matching pursuit (LPMP). We also consider certain modification of the algorithm by introducing the allowed positions of the Lorentzian peaks’ centers. Our results show that the LPMP algorithm outperforms other CS algorithms when applied to exponentially decaying signals. Full article
(This article belongs to the Section Sensor Networks)
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