dc.contributor.author | Mert, Ahmet | |
dc.contributor.author | Akan, Aydın | |
dc.date.accessioned | 2021-06-05T19:57:07Z | |
dc.date.available | 2021-06-05T19:57:07Z | |
dc.date.issued | 2014 | |
dc.identifier.issn | 1051-2004 | |
dc.identifier.issn | 1095-4333 | |
dc.identifier.uri | https://doi.org/10.1016/j.dsp.2014.06.006 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12960/438 | |
dc.description | 0000-0003-4236-3646 | en_US |
dc.description | 0000-0001-8894-5794 | en_US |
dc.description | WOS:000339458600006 | en_US |
dc.description.abstract | Signal decompositions such as wavelet and Gabor transforms have successfully been applied in denoising problems. Empirical mode decomposition (EMD) is a recently proposed method to analyze non-linear and non-stationary time series and may be used for noise elimination. Similar to other decomposition based denoising approaches, EMD based denoising requires a reliable threshold to determine which oscillations called intrinsic mode functions (IMFs) are noise components or noise free signal components. Here, we propose a metric based on detrended fluctuation analysis (DFA) to define a robust threshold. The scaling exponent of DFA is an indicator of statistical self-affinity. In our study, it is used to determine a threshold region to eliminate the noisy IMFs. The proposed DFA threshold and denoising by DFA-EMD are tested on different synthetic and real signals at various signal to noise ratios (SNR). The results are promising especially at 0 dB when signal is corrupted by white Gaussian noise (WGN). The proposed method outperforms soft and hard wavelet threshold method. (C) 2014 Elsevier Inc. All rights reserved. | en_US |
dc.description.sponsorship | Research Fund of Istanbul UniversityIstanbul University [36196, 38262, 35830] | en_US |
dc.description.sponsorship | This work is supported by the Research Fund of Istanbul University, Project Numbers: 36196, 38262 and 35830. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Academic Press Inc Elsevier Science | en_US |
dc.relation.ispartof | Digital Signal Processing | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Empirical Mode Decomposition | en_US |
dc.subject | Detrended Fluctuation Analysis | en_US |
dc.subject | Signal Denoising | en_US |
dc.subject | Thresholding | en_US |
dc.title | Detrended fluctuation thresholding for empirical mode decomposition based denoising | en_US |
dc.type | article | en_US |
dc.department | Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü | en_US |
dc.department-temp | [Mert, Ahmet] Piri Reis Univ, Dept Elect & Elect Engn, TR-34940 Istanbul, Turkey; [Akan, Aydin] Istanbul Univ, Dept Elect & Elect Engn, TR-34320 Istanbul, Turkey | en_US |
dc.contributor.institutionauthor | Mert, Ahmet | |
dc.identifier.doi | 10.1016/j.dsp.2014.06.006 | |
dc.identifier.volume | 32 | en_US |
dc.identifier.startpage | 48 | en_US |
dc.identifier.endpage | 56 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |