removing noise in biomedical signal recordings by singular value decomposition

Clicks: 168
ID: 257759
2017
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Abstract
Noise reduction or denoising is the process of removing noise from a signal. If some signal properties are known linear filtering is often useful. Fourier, wavelet and similar transform approaches remove unwanted signal components in the codomain. For this, predefined eigen-functions, e.g. wavelets, are used. Here we use singular value decomposition in order to compute a signal driven re-presentation (eigendecompositon). By removing unwanted components of the representation the signal can be denoised. We introduce the new method, apply it to signals and discuss its properties.
Reference Key
thomas2017currentremoving Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Schanze Thomas
Journal materials science and engineering c
Year 2017
DOI
10.1515/cdbme-2017-0052
URL
http://www.degruyter.com/view/j/cdbme.2017.3.issue-2/cdbme-2017-0052/cdbme-2017-0052.xml?format=INT
Keywords
transformation noise reduction signal processing computation Signal

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