removing noise in biomedical signal recordings by singular value decomposition
Clicks: 148
ID: 257759
2017
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.
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thomas2017currentremoving
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| Authors | ;Schanze Thomas |
| Journal | materials science and engineering c |
| Year | 2017 |
| DOI | 10.1515/cdbme-2017-0052 |
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