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BY-NC-ND 4.0 license Open Access Published by De Gruyter September 7, 2017

Removing noise in biomedical signal recordings by singular value decomposition

  • Thomas Schanze EMAIL logo

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.

Published Online: 2017-09-07

©2017 Thomas Schanze, published by De Gruyter

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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