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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Biomedical Signal Pr...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Biomedical Signal Processing and Control
Article . 2019 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
DBLP
Article . 2019
Data sources: DBLP
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Local means denoising of ECG signal

Authors: Chunqiang Qian; Honghong Su; Helong Yu;

Local means denoising of ECG signal

Abstract

Abstract Electrocardiograph (ECG) signals denoising by Non-Local Means (NLM) method can achieve high signal-to-noise ratio improvements with less waveform distortion. But, computational complexity constraints its potential application in ECG signal real-time denoising. In this paper, firstly we present a simple method to determine standard deviation of additive white Gaussian noise in the ECG signal. Then, a fast ECG signal denoising method, Local Means (LM) method, which is a “local” version of the NLM method is introduced. LM method has about 2 order of magnitude lower computational cost than NLM method due to the “local search.” In a low SNR level condition, the signal-to-noise (SNR) improvement increases via LM method, by 21% compared to NLM method.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
19
Top 10%
Top 10%
Top 10%
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