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Current Directions in Biomedical Engineering

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering

Editor-in-Chief: Dössel, Olaf

Editorial Board: Augat, Peter / Buzug, Thorsten M. / Haueisen, Jens / Jockenhoevel, Stefan / Knaup-Gregori, Petra / Kraft, Marc / Lenarz, Thomas / Leonhardt, Steffen / Malberg, Hagen / Penzel, Thomas / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Stieglitz, Thomas / Urban, Gerald A.


CiteScore 2018: 0.47

Source Normalized Impact per Paper (SNIP) 2018: 0.377

Open Access
Online
ISSN
2364-5504
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Removing noise in biomedical signal recordings by singular value decomposition

Thomas Schanze
  • Corresponding author
  • Technische Hoch-schule Mittelhessen, Dept. Life Science Engineering, Wiesenstr. 14, D-35390 Gießen, Germany
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Published Online: 2017-09-07 | DOI: https://doi.org/10.1515/cdbme-2017-0052

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.

Keywords: Signal; Signal processing; Noise Reduction; Transformation; Computation; Eigendecomposition

About the article

Published Online: 2017-09-07


Citation Information: Current Directions in Biomedical Engineering, Volume 3, Issue 2, Pages 253–256, ISSN (Online) 2364-5504, DOI: https://doi.org/10.1515/cdbme-2017-0052.

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©2017 Thomas Schanze, published by De Gruyter. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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