Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/7437
Title: Statistical multirate high-resolution signal reconstruction using the empirical mode decomposition based denoising approach
Authors: Ükte, Adem
Kızılkaya, Aydın
Elbi, Mehmet Doğan
Keywords: empirical mode decomposition
high-resolution signal reconstruction
multirate statistical signal processing
signal denoising
Gaussian noise (electronic)
Iterative methods
Signal analysis
Signal processing
Signal reconstruction
White noise
Additive White Gaussian noise
Alternative solutions
Denoising approach
Empirical Mode Decomposition
High resolution
Low resolution
Statistical signal processing
Wiener filter theory
Signal denoising
Publisher: IEEE Computer Society
Abstract: High-resolution signal reconstruction from a set of its noisy low-resolution measurements is considered. As an alternative solution to this problem, a method employing the empirical mode decomposition (EMD) based denoising approach is proposed. In the framework of the proposed method, iterative EMD interval-thresholding based denoising procedure is applied to each noisy low-resolution measurement so as to filter the additive white Gaussian noise effect on it. We then synthesize the noise-reduced low-resolution signals to form the high-resolution signal. Unlike the method using the Wiener filter theory for high-resolution signal reconstruction, the proposed method does not require knowledge of any correlation information about the desired high-resolution signal and its low-resolution versions. The validity of the proposed method is demonstrated by an audio signal reconstruction application. © 2014 University of West Bohemia.
URI: https://hdl.handle.net/11499/7437
https://doi.org/10.1109/AE.2014.7011725
ISBN: 18037232 (ISSN)
9788026102779
9788026102762
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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