Review and comparison of smoothing algorithms for one-dimensional data noise reduction
The paper considers the choice of parameters of smoothing algorithms for data denoising. The impact of the window size on smoothing accuracy was analyzed. The parameters of denoising filters were selected with respect to the mean-square error between the computed linear regression and the noisy sign...
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| Veröffentlicht in: | 2018 International Interdisciplinary PhD Workshop (IIPhDW) S. 277 - 281 |
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| Sprache: | Englisch |
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01.05.2018
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| Abstract | The paper considers the choice of parameters of smoothing algorithms for data denoising. The impact of the window size on smoothing accuracy was analyzed. The parameters of denoising filters were selected with respect to the mean-square error between the computed linear regression and the noisy signal. Finally, we have compared mean, median, Savitzky-Golay, Kalman and Gaussian filter algorithms for the data from the digital sensor. The figure of merit was also the algorithm execution time. |
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| AbstractList | The paper considers the choice of parameters of smoothing algorithms for data denoising. The impact of the window size on smoothing accuracy was analyzed. The parameters of denoising filters were selected with respect to the mean-square error between the computed linear regression and the noisy signal. Finally, we have compared mean, median, Savitzky-Golay, Kalman and Gaussian filter algorithms for the data from the digital sensor. The figure of merit was also the algorithm execution time. |
| Author | Kowalski, Pawel Smyk, Robert |
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| Snippet | The paper considers the choice of parameters of smoothing algorithms for data denoising. The impact of the window size on smoothing accuracy was analyzed. The... |
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| SubjectTerms | denoising filters Gaussian filter Kalman filter Kalman filters Kernel kernel smoothing least-square mean filter median filter Microsoft Windows Noise reduction Savitzky-Golay signal processing Signal processing algorithms smoothing smoothing algorithms Smoothing methods |
| Title | Review and comparison of smoothing algorithms for one-dimensional data noise reduction |
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