Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/8547
Title: Noise cancellation on low-frequency signals using empirical mode decomposition
Authors: Elbi, Mehmet Doğan
Kızılkaya, Aydın
Keywords: Empirical Mode Decomposition
Estimation performance
Intrinsic modes
Least squares support vector machines
Low frequency
Low-frequency signals
Noise cancellation
Savitzky-Golay filter
White Gaussian Noise
Frequency estimation
Signal processing
Support vector machines
Gaussian noise (electronic)
Abstract: In this study, the noise cancellation problem on noise corrupted low-frequency signals by using the Empirical Mode Decomposition (EMD) method is considered. For this aim, the Intrinsic Mode (IM) functions of the low-frequency signal corrupted by white Gaussian noise are obtained by applying EMD on this signal. Savitzky-Golay filter and Least Squares Support Vector Machine (LS-SVM) regression are separately applied to the signal reconstructed using the low-frequency ones of the IM functions, and the estimation performance of the original noiseless signal is examined. It is observed from the simulations that a satisfactory result is achieved via LS-SVM regression. © 2012 IEEE.
URI: https://hdl.handle.net/11499/8547
https://doi.org/10.1109/SIU.2012.6204684
ISBN: 9781467300568
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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